• Introduction
• Chapter 1: Understanding Work IQ
• Chapter 2: Establishing trust: How we govern Work IQ
• Chapter 3: How our employees experience Work IQ day-to-day
• Chapter 4: Work IQ beyond Microsoft 365
• Chapter 5: Working with Work IQ: The Customer Zero impact
• Conclusion: Where we’re heading: Work IQ, Fabric IQ, and Foundry IQ

Improving agentic workplace results with Work IQ

Adding deeper contextual intelligence to Microsoft 365 Copilot responses

Enterprise knowledge is perhaps a company’s most valuable asset, but for AI and agents, it can be difficult to take advantage of. Years of emails, documents, chats, meeting recordings, and workflows have created enormous volumes of rich data, scattered across systems and teams in a fragmented way. This data captures how work actually happens, but harnessing it broadly—especially in ways that support better decision making—has traditionally been almost impossible.

Enter the power of agentic AI tools.

In the modern agentic workplace, employees and teams here at Microsoft and elsewhere are finally able to take advantage of all that rich, unstructured knowledge. Microsoft 365 Copilot and AI agents can now access all this data and not simply retrieve information but also reason over it—learning how work gets done and then providing rich contextual responses and guidance.

“By giving AI the ability to reason across the vast repositories of unstructured data that our enterprise possesses, Work IQ fundamentally changes what’s possible for Copilot, agents, and employees alike.”

Brian Fielder, vice president, Microsoft Digital

We’ve given this new, dynamic way of leveraging your enterprise data to boost productivity a special name: Work IQ.

Work IQ represents a big step forward.

For us, it’s enabling the concept of “intelligence on tap” across our enterprise, making our organizational knowledge and work context accessible in real time, grounded in the signals employees generate every day. This transforms unstructured data from a challenge into a strategic resource—one that can support workflows at scale.

“Work IQ represents the next phase of the agentic workplace of the future—and it’s here,” says Brian Fielder, vice president of Microsoft Digital. “By giving AI the ability to reason across the vast repositories of unstructured data that our enterprise possesses, Work IQ fundamentally changes what’s possible for Copilot, agents, and employees alike.”

“It’s not really a brand-new capability, but more an evolution of what users already know, which is access to the grounding data in their Microsoft tenant. The difference is that Work IQ adds an additional layer to provide more context, allowing for richer and more relevant results.”

Aisha Hasan, principal product manager, Microsoft Digital

Internally here at Microsoft, Work IQ is having a tangible effect on how we work every day. A few simple scenarios that illustrate the power of Work IQ—described in greater detail in Chapter 3—include:

• Helping our employees understand which emails require their immediate attention, so they can focus on what matters
• Connecting meeting transcripts to the people involved in a meeting, accelerating actions through a deeper understanding of the participants and their work patterns
• Enabling our employees to create, organize, and publish Microsoft 365 content more quickly and with higher quality

This is just the beginning. As AI continues to permeate our business workflows, nearly every day-to-day task at Microsoft will be simplified, expedited, and improved by the intelligence of Work IQ. This includes the agents that are managing routine business and operational processes, giving them critical business context that helps their reasoning abilities.

This guide explores the ways that Work IQ is impacting how work gets done at Microsoft, and how Microsoft Digital—the company’s IT organization—has played a key role as Customer Zero, validating how Work IQ behaves under real enterprise conditions. It also examines the challenges and considerations that IT organizations will face as we enter an era where AI agents have access to unstructured data to complete workflows.

Chapter 1: Understanding Work IQ

Providing deeper insights through the power of context

Before we can fully explore the implications of Work IQ, it’s important to start with a clear understanding of what it is.

Work IQ is not a new application or service that users interact with directly. Rather, it’s a shared intelligence layer that continuously interprets work happening across the tenant. Understanding this distinction is critical, because it explains why Work IQ shows up everywhere Microsoft 365 Copilot works—and why it must be treated as foundational infrastructure, not as optional, add‑on functionality.

“It’s not really a brand-new capability, but more an evolution of what users already know, which is access to the grounding data in their Microsoft tenant,” says Aisha Hasan, a principal product manager in Microsoft Digital. “The difference is that Work IQ adds an additional layer to provide more context, allowing for richer and more relevant results.”

Work IQ is built on three layers:

• Data: It unifies signals from files, emails, meetings, chats, and business systems.
• Memory: It builds persistent understanding of how people and teams work.
• Inference: It combines models, skills, and tools to reason and act.

At a high level, Work IQ consists of the systems that collect and interpret signals from everyday work. These signals come from many familiar Microsoft 365 applications—Word, Outlook, PowerPoint, Teams, SharePoint, and more—as well as structured data sources (such as those contained in Power Apps and Dynamics 365 resources).

The fact that Work IQ unifies unstructured and structured data into a shared ontology is a key differentiator from traditional search tools. This combination, referred to as semantic unification, means that it can combine the authoritative data contained in structured sources with the intent, nuance, and narrative found in unstructured data.

Work IQ draws from a broad range of work data from your Microsoft tenant. The unstructured data includes:

• SharePoint sites, files, and other content
• OneDrive activity that reflects individual work and collaboration patterns
• Teams content, including chats, channels, and meeting data
• Outlook emails and attachments

In addition, calendar signals—such as meeting participation, recency, and frequency—add time-based context that helps Work IQ understand priority and relevance of different data. This is what it means to go beyond simple information retrieval.

When all these are combined, it provides rich context that allows Work IQ to reason across all our employees’ work in a way that would be impossible if each signal were evaluated independently.

In practice, this means that when an employee asks a question about a current work project in Copilot, the tool’s response is not simply informed by the model’s capabilities or general source material. Responses are shaped by Work IQ’s understanding of the employee’s role, recent work, collaboration patterns (who they work with), and the larger enterprise context and conversations surrounding the question.

How our employees interact with and understand Work IQ depends on their role in the organization.

Our personas and their relationship with Work IQ

End user

Gains richer, context-aware agent conversations

IT admin

Enables and governs Work IQ access

Agent builder

Manages data connectors quickly and easily

Security professional

Knows that sensitive data stays protected with Work IQ

AI agents using Work IQ behave similarly. They use the intelligence to ground their reasoning in real organizational data, ensuring that their actions and recommendations are aligned with how work is happening inside the tenant. Although there are differences in how they are configured, all agents in a Microsoft tenant can be set up to take advantage of the power of Work IQ.

The impact of Work IQ on our company has been dramatic—we’re seeing agentic responses and actions that go deeper than surface-level answers. Our ability to reason over both our structured and unstructured data is producing richer, more nuanced contextual results that are boosting our productivity.

As your organization assesses your level of AI readiness, think of Work IQ not as an abstract concept but as critical infrastructure. It’s the key to connecting enterprise knowledge, trust, and productivity in a single, shared foundation.

Work IQ versus Microsoft Graph

Work IQ does not replace what we call the Microsoft Graph, the general term for unified, API-enabling, secure, permission-aware access to Microsoft 365 data, insights, and services. While the Microsoft Graph provides our employees with access to all their work data, Work IQ turns those signals into meaningful context that AI can reason over. In other words, Graph answers the general question “what info exists,” while Work IQ interprets what that information means and weaves it into responses to make them better.

Key takeaways

As you prepare for Work IQ, these points can help frame how to think about its role in your organization:

• Work IQ is foundational infrastructure, not a user-facing feature. It operates as a shared intelligence layer across the tenant, continuously interpreting signals from everyday work.
• Work IQ draws its power from context, not isolated data. By combining signals from email, meetings, documents, calendars, and collaboration patterns, it enables Copilot and agents to reason about work in a way that goes beyond simple search or retrieval.
• Better agentic outcomes depend on Work IQ being in place. When agents and Copilot are grounded in Work IQ, their responses and actions align more closely with real enterprise work, delivering better relevance and measurable productivity gains.

Learn more

How we did it at Microsoft

• Discover how Work IQ is supercharging our AI usage at Microsoft. This post delves into the ways that Work IQ is boosting agentic response and changing the way we work at the company.  
• See how we’re embracing this agentic moment at Microsoft. This story covers how we use the power of Copilot and AI agents to boost employee productivity.
• Explore our IT playbook for the AI era and learn how we’re becoming a Frontier Firm. This article shares our journey as an IT organization toward the AI-powered future.

Further guidance for you

• Learn more about Work IQ with this post from the Microsoft 365 Copilot Blog.
• Check out this Microsoft Learn overview of the different Work IQ agent tools.
• Read all about the Microsoft Graph on the Microsoft Learn site.

Chapter 2: Establishing trust: How we govern Work IQ

Building on an existing foundation of solid governance and security

Like all Microsoft products, Work IQ was built with security foremost in mind. As the IT team at Microsoft, it is our responsibility to work in tandem with the product groups to ensure that all data that Work IQ has access to is well governed and secure.

The fact that Work IQ does not introduce new data into Microsoft 365 makes meeting this commitment easier. Embedded directly into the Microsoft 365 intelligence stack, Work IQ inherits the same compliance, security, and access controls that already govern the tenant.

“With great power comes great responsibility, and it’s up to your IT team to think about what it means to give your users full access to all this Work IQ data. It can greatly accelerate what people can build and what they can do.”

David Johnson, principal PM architect, Microsoft Digital

For Microsoft 365 Copilot–native agents, Work IQ is enabled to provide governed, context‑aware access to Microsoft 365 work data without requiring developers to build or manage individual data connectors.

As our governance experts note, this represents an inherent trade-off. Giving an agent access only to certain isolated data types reduces risk but also limits its value. Granting access through Work IQ means an agent can reason across everything the employee can access. This simplifies enablement but also requires stronger confidence in governance foundations.

Microsoft 365 intelligence stack

As our governance experts note, this represents an inherent trade-off. Giving an agent only access to certain isolated data types limits risk, but it also limits its value. Granting access through Work IQ means an agent can reason across everything the employee can access. This simplifies enablement but also requires stronger confidence in governance foundations.

“With great power comes great responsibility, and it’s up to your IT team to think about what it means to give your users full access to all this Work IQ data,” says David Johnson, a principal PM architect in Microsoft Digital. “It can greatly accelerate what people can build and what they can do. At the same time, organizations will want to think about the downstream implications of access.”

Exposing underlying governance issues

Our overall solution was to anchor Work IQ to our governance and security policies that already existed for our data. Sensitivity labels, data protection rules, and data-loss prevention policies remain the primary guardrails, as they do for all data across our enterprise. All these controls live at the data layer.

A critical aspect of this governance model is how sensitivity labels propagate through Work IQ experiences. In Microsoft 365, the label that is applied to a source document determines the label of any derived outputs, including summaries, insights, or AI-generated responses. This ensures that users have immediate context about the information’s sensitivity and how it should be handled. The label effectively travels with the data, reinforcing both user awareness and policy enforcement.

Labels also play a key role in controlling access beyond simple permissions. Even if a user has baseline access to a location, sensitivity labels can further restrict whether content can be extracted, shared, or surfaced through AI experiences. In some cases, organizations can configure policies so that content with specific labels is not returned at all in Work IQ or Copilot responses. This gives IT teams an additional layer of control to prevent exposure of particularly sensitive information.

These labeling principles extend across collaboration scenarios as well. For example, meeting labels determine the classification of all downstream artifacts—including recordings, transcripts, and notes. Sensitive discussions remain governed consistently, even as Work IQ helps make them more discoverable and actionable.

For example, even with Work IQ enabled, a document labeled Highly Confidential cannot be exposed through Copilot to someone without access, even if it is referenced in a Teams meeting transcript or included in an AI-generated summary. Copilot may understand that the document played a role in a particular decision, but it cannot extract or reveal its contents beyond what permissions allow.

This distinction—discoverable versus extractable—proved critical in our deployment of Work IQ. The intelligence layer makes data relationships visible, but it does not override protection. In one internal scenario, a sensitive document was found to be accessible through a Copilot query. The root cause was not Work IQ, but a missing sensitivity label—the AI tool simply honored what governance allowed. We treated the incident as a governance signal and corrected labeling at the source.

Remember that Work IQ can only access data that:

• Exists inside your Microsoft 365 tenant or is explicitly connected via approved connectors
• The current user already has permission to access
• Is allowed by tenant‑level admin policy, compliance, and sensitivity controls

The security and governance considerations also extend to how new agents are released across our enterprise. For example, an agent created for use within one internal team has lighter governance controls than one that is published to our internal Microsoft agent portal, which offers companywide access. The latter requires additional review, approval, and monitoring as part of our due diligence for governance and security.

Ultimately, Work IQ adheres to all of the security and governance policies and procedures in our tenant, preserving the trust that our security-first approach creates and maintains.

Key takeaways

The following are important considerations for data governance and security when you consider adopting Work IQ for your organization:

• With Work IQ, governance and security are top-line priorities. We made sure that Work IQ would always inherit the same compliance, access controls, and data protection policies that already govern Microsoft 365 data.
• Work IQ doesn’t introduce new data access—it changes how existing access functions. By packaging tenant data into a single intelligence layer, it facilitates easier agent builder access to the data you already have in your Microsoft 365 tenant.
• The distinction between discoverable and extractable data is central to safe AI deployment. Copilot and other agents can understand how work information is connected and referenced without exposing protected content beyond existing permissions.
• IT admins and leaders should consider the ramifications to their tenant. Work IQ makes agents more powerful and context-aware by opening up access to vast quantities of Microsoft 365 data, but IT professionals should always think through downstream effects on data security and governance.
• Work IQ surfaces governance gaps instead of masking them. When issues arise—such as misapplied sensitivity labels—the solution is not to restrict intelligence, but to strengthen data governance at the source.

Learn more

How we did it at Microsoft

• See how we’re governing AI agents at scale internally. This readiness guide explains how we approach security and compliance for AI agents at Microsoft.
• Read about our experience tackling Microsoft 365 Copilot governance. This guide details our internal governance efforts for Microsoft 365 Copilot as we rolled the tool out across our organization.
• Explore how we’re powering data governance at Microsoft with Purview Unified Catalog. This story explains how Purview is helping us redefine our internal approach to data governance.

Further guidance for you

• Learn more about governance and security for AI agents and find out how to keep your AI initiatives secure.

Chapter 3: How our employees experience Work IQ day to day

Transforming the way work happens at Microsoft

To understand how Work IQ shows up and impacts the workflows of people across our organization, we spoke to several Microsoft employees. They explained how Work IQ makes a difference in the results they’re getting from Copilot and other agentic AI tools and how the intelligence is supercharging their work.

Work IQ in Outlook    

Outlook email and calendars are the space where many of our employees feel the heaviest cognitive load of their day‑to‑day work. It’s also where Work IQ is surfacing some of the most innovative ways to help employees accomplish more.

“You open your Outlook in the morning and Copilot—by drawing on Work IQ context and through features like priority scoring and summarization—can help you see which messages need your attention first.”

Matthew Marzynski, principal product manager, core experiences, Microsoft Digital

Rather than treating messages and meetings as isolated items, Work IQ allows Copilot in Outlook to reason across email signals, conversation history, meeting patterns, and calendar behavior to deliver responses that reflect how work actually unfolds.

This means Copilot goes beyond keywords or unread status indicators to determine importance. Through Work IQ, it understands the context of each conversation—which threads are more urgent and relevant to your work and which are less vital.

“You open your Outlook in the morning and Copilot—by drawing on Work IQ context and through features like priority scoring and summarization—can help you see which messages need your attention first,” says Matthew Marzynski, a principal product manager for core experiences in Microsoft Digital. “Copilot is now beginning to offer proactive nudges to help you stay on top of what matters, surfacing what’s changed and what you need to focus on.”

The deeper context also aids Outlook in generating rich summaries of lengthy threads, which can highlight owners, decisions made, and next steps. This allows employees who are added to the thread or who have been away to quickly catch up on complex conversations without manually digging through seemingly endless past messages or related documents.

Marzynski frames Work IQ as an invisible intelligence layer that quietly reshapes how Outlook behaves over time. His core thesis is simple: Users never have to think about Work IQ; they just observe that Outlook is more helpful than before, and that their work gets easier.

“There are no complex commands to learn or rules to create. The intelligence works behind the scenes as you use Outlook,” he says. “Your inbox just gradually feels more relevant. Outlook adapts to how you work, rather than the reverse, and becomes more like an assistant instead of a filing cabinet of communications.”

Work IQ in Teams + Researcher Agent

Another immediate and tangible way our employees experience Work IQ is in Microsoft Teams meetings. The value begins the moment a meeting is recorded. Transcripts, speaker contributions, shared content, and AI‑generated summaries are automatically captured and folded into the attendees’ ongoing work context—without requiring manual note‑taking or follow‑up documentation.

Ray Peer is a senior product manager in Microsoft Digital who observed the power of Work IQ in a recent project he completed with our internal legal team. According to Peer, the team was struggling to find specific content in their data lake, which contains tens of thousands of documents, articles, and other content items.

“Based just on what people shared in that meeting, and what it knows about their work and about SIPOC diagrams, Researcher was able to generate a fully formed, detailed solution for me. That’s the intelligence layer at work.”

Ray Peer, senior product manager, Microsoft Digital

So, he facilitated a Teams meeting for a free-form process‑mapping discussion with a few members of Microsoft Legal. Days later, he put the meeting transcript into the Copilot Researcher agent and asked it to generate a structured SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagram and accompanying documentation.

He was amazed by the results.

“Based just on what people shared in that meeting, and what it knows about their work and about SIPOC diagrams, Researcher was able to generate a fully formed, detailed solution for me,” Peer says. “That’s the intelligence layer at work. It reasoned over what we said—there were no visuals shared or anything—and it came up with something that I could cut and paste into the final format. I used to have to do that manually, and it took hours.”

Work IQ connected the meeting transcript to the people involved, the SharePoint sites they used, and similar work done elsewhere in the organization. Copilot was able reason across different tools and unstructured data, rather than just treating the meeting transcript as a static artifact.

Note that this works differently from third‑party meeting tools, because the data never leaves the tenant. Work IQ treats Teams meetings as part of a continuous Microsoft 365 workstream—honoring permissions and sensitivity labels throughout—so conversations can become durable inputs for future work without adding risk or effort for employees.

Work IQ in SharePoint

In SharePoint, Work IQ is helping employees create, organize, and publish content by drawing on the rich context of their Microsoft 365 data. Rather than starting from a blank page or text block, content development is sped up as Copilot draws on their relationships, collaboration history, and metadata to help produce sites and documents.

“Copilot will recommend text changes, but also layout suggestions, image and graphic options, and other helpful assistance. It makes it easy to create more compelling content, more rapidly.”

Sam Crewdson, principal product manager, Microsoft Digital

For example, when you ask Copilot to create a new section in a SharePoint site—such as a project overview, status update, or other material—Work IQ enables the tool to look deeper than the prompt itself. When generating the content, it can draw on documents you’ve recently edited, your emails and Teams conversations, and related work happening across the organization. The output you get from Copilot is highly relevant and grounded in real work.

Sam Crewdson is a principal product manager at Microsoft Digital who has been a part of the SharePoint team for more than two decades. He’s excited about what Work IQ is enabling users to accomplish in the product using Copilot, as well as other agentic tools like Knowledge Agent (a domain-specific agent that can drill down on SharePoint sites and libraries).

“Copilot in SharePoint is now able to not only help you produce better written content, it’ll also offer more contextual and visual help,” Crewdson says. “Copilot will recommend text changes, but also layout suggestions, image and graphic options, and other helpful assistance. It makes it easy to create more compelling content, more rapidly.”

Another emerging scenario Crewdson described is conversational agentic authoring in SharePoint. In these workflows, employees refine their SharePoint pages by interacting directly with an agent—asking it to add sections, adjust tone, or suggest visuals. Over time, these agents will reduce repetitive setup steps and help teams move from draft to publish faster.

Across these experiences, Work IQ is helping shift SharePoint from a manual content creation tool to an application where agents automate everyday content tasks based on your overall work context and related Microsoft 365 data.

Key takeaways

Here are some things to remember when thinking about how Work IQ can impact your employee workflows:

• Work IQ reduces cognitive load in Outlook by understanding work context. By recognizing decision‑driven threads, collaboration patterns, and urgency over time, Copilot helps employees focus on what truly needs their attention without relying on manual rules or keyword searching.
• Email and calendar intelligence improves prioritization, summaries, and follow‑through. Work IQ allows Copilot to highlight owners, decisions, and next steps in long threads and nudge users toward timely action, based on how they typically work with colleagues.
• Teams meetings become durable inputs for future work when powered by Work IQ. Copilot and the Researcher agent can reason across meeting content, people, and related SharePoint work—creating structured outputs while honoring tenant security and permissions.
• Work IQ helps Copilot speed up and enrich content creation in SharePoint. By drawing on Microsoft 365 data, Copilot can generate more relevant content for your SharePoint sites and offer helpful layout and graphics suggestions that accelerate the site development process.

Learn more

How we did it at Microsoft

• See how to pick the right Copilot for the job. This post explores different Copilot agents and modules and discusses how to choose the correct one for your task.
• Discover how we deployed Copilot internally at Microsoft. This step-by-step guide breaks down the deployment and adoption process we followed to roll out this groundbreaking technology across our entire organization.
• Find out how we’re using AI to redefine work in Outlook. This blog post explores the latest AI features that our employees are using to work smarter in Microsoft Outlook.
• Learn five ways we’re getting more out of Teams in the era of Copilot and AI. This article details different Teams features that take advantage of the latest in AI technology.
• Read about the lessons learned using SharePoint agents at Microsoft. This post covers some of the insights gleaned through our deployment of different SharePoint agents.

Further guidance for you

• Check out the Microsoft Copilot Success Kit and learn how to accelerate your Copilot implementation with templates, onboarding guides, and technical readiness resources.
• Explore the company’s essential guide to Copilot adoption for practical steps to onboard, engage, and measure impact in your organization.

Chapter 4: Work IQ beyond Microsoft 365

Integrating Work IQ across the enterprise

As organizations adopt Copilot and other AI agents at scale, the question arises: How does Work IQ show up in different contexts? Is it something that only impacts your work in Microsoft 365 applications, or does it also play a role in external applications and other areas of your IT enterprise?

Based on our experience here at Microsoft, the answer is that Work IQ shows up differently depending on where it’s consumed, and those differences matter for admins, agent developers, and other IT professionals.

For most of our employees, Work IQ operates entirely behind the scenes inside Microsoft 365. It is not something users configure, enable, or interact with directly. By reasoning over your entire Microsoft 365 data graph, Work IQ improves the results that Copilot generates in apps like Outlook, Teams, Word, SharePoint, Copilot Chat, and GitHub Copilot.

In this mode, Work IQ is:

Built directly into the Microsoft 365 intelligence stack

Governed by existing permissions, sensitivity labels, and compliance policies

Invisible to users, with no new controls or UI to manage

Continuously learning from signals across emails, meetings, and files

You don’t “implement” Work IQ—it’s already present in first-party Microsoft products by default. If you have enabled Copilot, you are getting the benefits of Work IQ across all of these applications. 

Similarly, any agents you build for Microsoft 365 apps (such as using Agent Builder in Microsoft 365 Copilot) are scoped for use specifically in these apps, rather than outside of them. These agents do not require separate connectors, such as APIs or Model Context Protocol (MCP) servers, to access Work IQ. In fact, Work IQ MCP is a great tool to make your context ubiquitous to whichever agentic experience can be imagined.

Extending Work IQ beyond Microsoft 365: explicit by design

Implementation works somewhat differently outside of native Microsoft 365 experiences. When it comes to custom agents, line‑of‑business applications, or Azure‑hosted solutions, Work IQ does not show up automatically. In these contexts, it is intentionally enabled by our builders and governed by our administrators.

In these scenarios:

• Developers access Work IQ through APIs or MCP servers
• Admins explicitly control which capabilities are enabled or disabled
• Work IQ provides rich enterprise context without duplicating data
• Permissions and governance remain enforced at the tenant level

For us, this design is deliberate and has advantages. Rather than asking our developers to configure dozens of individual connectors for mail, calendars, files, and meetings, Work IQ offers them a single-entry point for enterprise context. Builder tools like Microsoft Foundry and Copilot Studio allow our teams to take the same Work IQ intelligence that Copilot uses and apply it to workflows that live outside Microsoft 365. Examples include automating newsletters, generating insights for account teams, or powering custom agents to handle specific scenarios.

The key distinction is accountability. Inside Microsoft 365, Work IQ is ambient. Outside it, Work IQ is a conscious architectural choice, one that requires actions upfront to enable.

Work IQ does not “open up new data” when used externally. It ports intelligence, not raw access, applying the same rules no matter where it’s consumed. At the same time, it gives organizations flexibility to decide when and how far that intelligence should travel.

This continuum—from implicit use inside Microsoft 365 to explicit use beyond it—also clarifies our roles:

• Our end users benefit without needing to learn anything new
• Our IT teams retain centralized control at the tenant level
• Our builders gain a faster path to context‑aware solutions

Work IQ works best when treated as a shared intelligence foundation, not a feature toggle. It is present by default where trust is already established, and it can be incorporated deliberately where your organizational requirements or innovation needs demand more reach.

Model Context Protocol servers and Work IQ

For organizations that move beyond native Microsoft 365 experiences and begin building custom agents, Model Context Protocol (MCP) servers are the primary mechanism for connecting those agents to Work IQ. While Work IQ is always available inside Copilot, MCP servers are what make much of that same intelligence accessible to agent builders.

At a high level, MCP servers are an open-standard technology (not proprietary to Microsoft) that act as governed tool interfaces to enterprise context. Each Work IQ MCP server represents a scoped slice of Microsoft 365 signals—such as email, calendar, Teams activity, or SharePoint content—and exposes them in a form that agents can reason over. Rather than wiring individual connectors or APIs for each workload, builders can rely on MCP servers to assemble relevant context automatically, while still honoring permissions, sensitivity labels, and tenant policies.

When we’re building agents, Work IQ becomes explicit, and MCP servers are how our builders declare their intent. This includes determining which types of enterprise context the agent needs, how broadly it should reason across work signals, and where governance boundaries apply.

From an IT perspective, MCP servers also provide a critical control point. Our administrators decide which Work IQ MCP servers are enabled in the tenant and which of our builders are allowed to use them. This ensures that extending intelligence beyond Microsoft 365 remains a deliberate choice rather than an accidental one.

Using these servers to connect with your enterprise data also represents real—but manageable—risk. They make existing permissions more actionable, which can amplify the impact of overshared content or weak data hygiene. The best practice is to treat these servers as governed infrastructure: enable them selectively at the tenant level, start with the minimum set required for defined agent scenarios, restrict usage to approved builders, and pair expansion with regular permission reviews and labeling discipline.

Your readiness plan should be to ensure that governance is in place, then selectively enable MCP servers where agents require deeper context. The servers are the bridge that lets agent builders tap into Work IQ safely, allowing you to bring enterprise intelligence into custom solutions without breaking the trust model that makes Copilot effective at scale.

Key takeaways

Here are some things to remember when thinking about how Work IQ shows up across your organization—especially if you plan to extend this intelligence into custom agents and applications:

• Work IQ is foundational inside Microsoft 365 and intentional outside it. Within Copilot experiences, Work IQ operates implicitly, while custom agents introduce a conscious decision to consume that intelligence through MCP servers.
• Governance principles don’t change when extending Work IQ, but they become more visible. MCP servers enforce existing permissions, labels, and tenant policies, making it critical that governance foundations are solid before agents rely on deeper context.
• Agent builders declare intent through MCP server selection. Choosing which Work IQ MCP servers to use defines what enterprise signals an agent can reason over and how broadly it reflects real work patterns.
• Preparing to extend Work IQ beyond Microsoft 365 is about readiness. Organizations that are already ready for Copilot can selectively enable MCP servers to unlock richer agent scenarios without introducing new security or compliance risk.

Learn more

How we did it at Microsoft

• Learn how we’re shaping AI management at Microsoft with Agent 365. This post discusses how we use the Agent 365 control plane to govern Microsoft 365 Copilot and agents internally.
• Read our complete guide to deploying AI agents internally at Microsoft. This Inside Track readiness guide covers all aspects of how we’ve implemented agentic AI across our organization.
• Discover how we’re unlocking enterprise AI extensibility with Copilot Studio. This story explores how we govern more advanced agents built with Copilot Studio, including connectors, orchestration, and scaled governance.
• Check out how we’re protecting AI conversations at Microsoft with Model Context Protocol security and governance. This article delves into MCP governance through secure-by-default architecture, automation, and inventory for faster, safer agent development.

Further guidance for you

• Read this Work IQ MCP overview on the Microsoft Learn site to find out more about how agents connect using Model Context Protocol servers.
• See the Work IQ Copilot reference on the Agent 365 Microsoft Learn site for further technical detail.

Chapter 5: Working with Work IQ: The Customer Zero impact

Change management lessons from our experience with an ambient intelligence layer

Work IQ wasn’t rolled out across our organization as an abstract platform decision or deployment milestone. Its development has been one aspect of our overall transformation into an AI-first Frontier Firm.

Along the way, Work IQ has been shaped by our long‑standing Customer Zero mission at Microsoft Digital: Using our own products at enterprise scale first, learning directly from how employees experienced it, and allowing those lessons to shape how the technology is refined and extended to customers.

In our tenant, Work IQ benefits emerged gradually through incremental improvements to relevance, context, and intelligence across Microsoft 365. These gains were driven by advances in AI that made it possible to interpret everyday work signals more effectively.

There was no formal product implementation or adoption campaign when we launched Work IQ at Microsoft. As ambient infrastructure, Work IQ is an unseen part of all employee workstreams—nearly every experience benefits from it. At the same time, the power of Work IQ depends on everyone in our organization being effective stewards of their own unstructured data, preserving security, governance, and relevance.

Enablement and adoption

To fully realize the value of Work IQ, we have found that organizations must invest in the foundational behaviors that make their organizational knowledge accessible. One of the key steps in this effort is enabling and encouraging the use of meeting transcripts. Work IQ depends on the artifacts of daily work to build context, and without transcripts, a significant portion of meeting insights and decisions remain inaccessible to the intelligence layer.

Making transcription a standard part of our employees’ everyday collaboration proved essential. Transcripts create a durable, searchable record that Work IQ can connect to documents and actions, helping employees quickly understand what happened, even if they weren’t present. When paired with existing governance controls like sensitivity and meeting labels, organizations can capture this data securely while unlocking great value from this collective knowledge.

This is actually a cultural shift.

We gave our teams clear guidance and encouraged meeting transcription as part of their normal workflow. When paired with the enhancements to meeting recaps in Microsoft Teams, this becomes a powerful tool for preserving and leveraging organizational knowledge.

Of course, Copilot adoption and training efforts were also a vital part of our getting the most from Work IQ. Our employees needed demonstrations of all the things that Copilot could help them accomplish, along with encouragement to jump in and try it out for themselves. Our data shows that internal AI usage has grown significantly over time—from a few thousand users to hundreds of thousands across the company—in large part due to:

• Employee-driven champions programs
• Scenario‑based learning efforts
• Timely and consistent internal communications

Usage also grew internally as our product teams continually refined our AI tools, aided by our collection of user feedback on agentic answers to identify low-quality output and irrelevant detail.

Another major insight we captured was the importance of persistent memory to the Copilot and Work IQ experience. Through our work as Customer Zero, we collected a large volume of feedback from employees indicating that this was a priority—users should not have to repeatedly explain who they are or what they are working on.

The experience was subsequently improved, and Work IQ now helps enable Copilot to remember user history and tailor responses accordingly—delivering summaries for communicators and deeper technical detail for engineers, for example.

Our Customer Zero efforts also validated a critical governance principle for us. As intelligence improved, some teams were surprised by how much context Copilot could surface. In every case, investigation showed that the underlying data access already existed. Work IQ did not change permissions or expose new data—it made existing relationships more visible. This reinforced the importance of strong data hygiene, sensitivity labeling, and permission management as prerequisites for trusted intelligence.

Ultimately, our work as the company’s Customer Zero validated that Work IQ is best understood as shared infrastructure. Its value compounds when organizations focus on readiness—governance, learning, and trust—and allow intelligence to scale naturally across work, rather than treating it as a feature to deploy.

When these conditions are in place, Work IQ quietly raises the quality of Copilot and agent experiences without adding complexity for users or additional burden for IT.

Key takeaways

As you consider how Work IQ might take shape in your own organization, consider these observations from Microsoft Digital’s Customer Zero experiences with this new intelligence layer:

• Meeting transcription is the key. Making sure all meetings are transcribed is essential for Work IQ, so it can build context on how work happens in your organization. This is a technical and cultural change that you need to facilitate and encourage.
• Awareness and learning are keys to usage and feedback. Our internal Copilot adoption grew when employees were shown practical scenarios and encouraged to experiment, supported by champions programs and ongoing internal communication.
• Change management drives results. Use employee champions, role-based immersive learning, and timely internal communications to help your employees understand what Work IQ is and how it can help your enterprise maximize the value of AI.
• Treating Work IQ as shared infrastructure unlocks compound value. When governance, learning, and trust were in place, intelligence could reason across all our rich unstructured data —improving Copilot and agent experiences without adding additional work for users or IT.

Learn more

How we did it at Microsoft

• Read about how we serve as Customer Zero in an AI-powered world. This story describes how Microsoft Digital’s role as Customer Zero has grown and evolved as we move into the Frontier Firm era.
• How to pick the right Copilot for the job. This post explores different Copilot agents and modules and discusses how to choose the correct one for your task.
• Recapping our meetings with Microsoft Teams Premium. This Inside Track story explains how Intelligent Recaps have changed the game when it comes to getting the most out of meetings at Microsoft.

Further guidance for you

• Check out the Microsoft Copilot Success Kit and learn how to accelerate your Copilot implementation with templates, onboarding guides, and technical readiness resources.

Where we’re heading: Work IQ, Fabric IQ, and Foundry IQ

Combining different layers of intelligence to transform the workplace

While impactful on its own, Work IQ is just part of larger story of how we’re using the power of rich data and agentic AI to transform how we work at Microsoft.

“While Work IQ can access your Microsoft 365 data, Fabric IQ will connect to your organizational data, such as analytics. Foundry IQ can leverage both, plus other domain data, to help developers build powerful agentic solutions.”

Naveen Jangir, principal architect, Microsoft Digital

Work IQ is one layer. It allows our AI tools to reason over unstructured data so this powerful resource can be a part of our larger enterprise intelligence system. But it also includes two other aspects of this three-layer system—Fabric IQ and Foundry IQ. Combined, these three capabilities enable organizations to take full advantage of your knowledge estate to forge the AI-powered workplace of the future.

“While Work IQ can access your Microsoft 365 data, Fabric IQ will connect to your organizational data, such as analytics,” says Naveen Jangir, a principal architect in Microsoft Digital. “Foundry IQ can leverage both, plus other domain data, to help developers build powerful agentic solutions.”

Here’s how these capabilities work together in complementary roles to impact how work gets done at Microsoft:

• Work IQ handles unstructured data—like documents, emails, PDFs, and web content—by extracting meaning and context from human language.
• Fabric IQ operates over structured data—like tables, databases, metrics, events, and transactions—to bring consistency and analytic rigor to our work.
• Foundry IQ provides the knowledge-grounding layer, where entities, relationships, and ontologies allow reasoning to stay aligned with enterprise truth.

While each component is powerful on its own, the deeper value is what becomes possible when they are used together.

The intent is to enable agents that can reason across all enterprise knowledge, regardless of where it originated or how it was stored. An agent should be able to read a policy, connect it to operational data, understand who and what is involved, explain its conclusions, and take an action (if desired) through a shared ontology based on organizational context.

That kind of capability can’t emerge just from information retrieval. It requires shared meaning across systems, content, and data types.

This is where the role of Work IQ becomes especially important. We have found that unstructured data contains some of the most critical institutional knowledge an organization has, but it rarely arrives in a form that is ready to be reasoned over. Documents reference people, systems, processes, and timelines in ways that make sense to humans, but not to machines. They can also fall out of date or represent a draft state that was never meant to be presented as verified information.

Work IQ bridges this gap by transforming the raw text into structured understanding, without stripping away nuance.

“Work IQ is already helping us change the way that work gets done. Instead of hunting for information or stitching context together manually, our employees can focus on decisions, creativity, and outcomes—because the intelligence is already there, working with them every day. It’s an integral part of preparing our organization for our agentic AI future.”

Vijaya Alaparthi, principal group product manager, Microsoft Digital

The crucial mechanism for that transformation is entity extraction, paired with a shared ontology. When a document mentions an employee, a system, a regulation, or a product, Work IQ identifies that reference as something concrete and reusable. Over time, those entities become the connective tissue between unstructured content, structured records in Fabric IQ, and the semantic backbone that Foundry IQ relies on to ground reasoning in the agents we create.

We can already see signs of this promised future at Microsoft today. Take a tool like our Employee Self-Service Agent, which we launched late last year. What before was a collection of static HR documents becomes a living knowledge system: policies are parsed, roles and eligibility criteria are extracted, and guidance is grounded in an understanding of employee role and location. The agent can answer a question and explain why the answer applies, because it understands both the document and the organizational context behind it.

This is why Work IQ is such a strategic capability. Improving document quality, normalizing metadata, resolving entities, and establishing governance are not one-off hygiene tasks. They expand what future agents will be able to do safely and reliably. The more coherent your unstructured data becomes, the less guesswork agents must do and the more context they can absorb.

“Work IQ is already helping us change the way that work gets done,” says Vijaya Alaparthi, a principal group product manager in Microsoft Digital. “Instead of hunting for information or stitching context together manually, our employees can focus on decisions, creativity, and outcomes—because the intelligence is already there, working with them every day. It’s an integral part of preparing our organization for our agentic AI future.”

For us, the direction forward is clear. The better your data foundation, the more capable—and trustworthy—your agents become. As unstructured and structured knowledge converges, intelligence stops being a set of isolated features and becomes a system.

Organizations that invest in technology like Work IQ to harness their unstructured data as enterprise knowledge are the ones that will deploy the most capable agents going forward and will be best positioned to take advantage of the agentic future.

Key takeaways

If you want your organization to be able to use Work IQ to propel your own agentic transformation, consider what we’ve learned on our journey:

• Work IQ transforms unstructured enterprise data into actionable intelligence. By reasoning over emails, documents, meetings, and chats, it unlocks institutional knowledge that was previously fragmented and underused.
• The intelligence operates as foundational infrastructure, not a user-facing feature. Work IQ runs continuously behind the scenes across Microsoft 365, improving Copilot and agent responses wherever they appear without configuration.
• Context is what makes Copilot feel truly intelligent. By combining signals from collaboration patterns, conversations, documents, and more, Work IQ enables agents to respond based on how work actually happens, not just what information can be retrieved.
• Security and governance remain intact because Work IQ inherits existing controls. It doesn’t create new access to data; it reveals relationships while fully honoring permissions, sensitivity labels, and compliance policies.
• Employees experience Work IQ as reduced cognitive load, not added complexity. Inbox relevance, richer summaries, and clearer follow-through improve naturally over time.
• Using Work IQ beyond Microsoft 365 is a deliberate, governed choice. MCP servers allow builders to bring enterprise context into custom agents while giving IT teams clear control over scope, access, and risk.
• Work IQ is the foundation for the next generation of agentic intelligence, especially when combined with Fabric IQ and Foundry IQ. The more coherent and well-governed your unstructured data is today, the more capable, explainable, and trustworthy your future agents will become.

Learn more

• Explore how Work IQ is helping supercharge AI usage at Microsoft.
• Discover our chapter-by-chapter internal deployment guide for Microsoft 365 Copilot.
• Check out how we’re embracing this agentic moment at Microsoft.
• Dive into a Microsoft Learn overview of different Work IQ agent tools.
• Read an IT playbook for the AI era and learn how we’re becoming a Frontier Firm at Microsoft.
• See how we’re using Model Context Protocol security and governance to protect AI conversations at Microsoft.
• Learn about our experience governing AI agents at scale in this readiness guide.
• Find out how we’re unlocking enterprise AI extensibility with Copilot Studio.

Try it out

Get a closer look at Work IQ.

The post Intelligence on tap: How Work IQ enables AI and agents at Microsoft appeared first on Inside Track Blog.

As AI capabilities advanced, we saw an opportunity to move beyond individual productivity gains and toward something more transformative: Empowering our developers to build intelligent agents that can automate workflows, streamline operations, and create new business value.

Realizing this vision required more than new tools. We needed to rethink how we foster development, govern innovation, and operate at scale.

“We’ve made a lot of progress enabling our developers to build agents that make us more productive. We’re Customer Zero at Microsoft, which means we’re the first to deploy and use the technology and services that we later sell to our customers. Those learnings give us a unique perspective and story to share about the journey our developers have been on with AI and agents.”

Brian Fielder, vice president, Microsoft Digital

Today, we’re sharing the foundation we built that supports this shift.

We’re driving employees across Microsoft to create and use AI agents—from simple, task-focused solutions to enterprise-grade applications available across the company. It’s all supported by a secure, governed, and extensible platform.

“We’ve made a lot of progress enabling our developers to build agents that make us more productive,” says Brian Fielder, vice president of Microsoft Digital, the company’s IT organization. “We’re Customer Zero at Microsoft, which means we’re the first to deploy and use the technology and services that we later sell to our customers. Those learnings give us a unique perspective and story to share about the journey our developers have been on with AI and agents.”

Within the context of Microsoft Build 2026, we’re sharing what it really takes to move from experimentation to impact. Through this collection of stories and resources, we highlight how we’re empowering our developers to build with agentic AI—from establishing governance and platform capabilities to driving adoption and delivering real-world outcomes. Our goal is to provide practical insights you can use to accelerate your own AI journey.

“We hope you find the journey we’ve been on practical and useful,” Fielder says. “When it comes to agents, we’re accelerating fast and scaling at an enterprise level. As our story continues to evolve, we look forward to sharing it with you.”

Guidance for developers: How we manage agentic AI at Microsoft

These articles outline our vision for agentic AI, showing how we’re building a secure, governed, and extensible foundation for AI agents—from Work IQ and Copilot Studio to Agent 365, Azure DevOps, and Model Context Protocol—so developers can create scalable, high-value solutions across the enterprise.

April 16, 2026

Alex Fleck

Becoming a Frontier Firm: A guide for deploying AI agents based on our experience at Microsoft

May 21, 2026

Alex Fleck

Governing AI agents at scale: Lessons from our journey at Microsoft

• How Work IQ is supercharging our AI usage at Microsoft
• Shaping AI management at Microsoft with Agent 365 and Copilot controls
• Deploying Microsoft Agent 365: How we’re extending our infrastructure to manage agents at Microsoft
• Unlocking enterprise AI extensibility at Microsoft with Microsoft Copilot Studio
• Powering AI value with Microsoft 365 Copilot extensibility at Microsoft
• How our employees are extending enterprise AI with custom retrieval agents
• Transforming our approach to sensitivity labels at Microsoft with Microsoft Entra
• Reclaiming engineering time with AI in Azure DevOps at Microsoft
• Protecting AI conversations at Microsoft with Model Context Protocol security and governance

UPCOMING POSTS

• Intelligence on tap: Our guide for How Work IQ enables Microsoft 365 Copilot to better understand how we work at Microsoft
• Our guide for deploying Agent 365 based on our experience at Microsoft
• Agentic modernization: Securing Python at scale for agentic AI at Microsoft

Our IT guide to becoming a Frontier Firm

These stories share our IT playbook for becoming a Frontier Firm, highlighting a practical path to enterprise AI maturity through agentic transformation, operational scale, responsible innovation, and partnership—showing how IT leaders can balance governance, modernization, and employee engagement while building an AI-first organization.

December 4, 2025

Keith Boyd

Becoming a Frontier Firm: Our IT playbook for the AI era

• Enterprise AI maturity in five steps: Our guide for IT leaders
• The agentic future: How we’re becoming an AI-first Frontier Firm at Microsoft
• AI at scale: How we’re transforming our enterprise IT operations at Microsoft
• Transforming into an AI-first Frontier Firm in partnership with our works councils
• Fast Train to the AI Frontier: Balancing risk and innovation in the era of AI at Microsoft

Working as developer in IT at Microsoft in the era of AI

These stories explore what it means to work in Microsoft Digital during the AI era, showing how developers and knowledge workers are reshaping engineering, the employee experience, and their own career growth through AI-powered tools, new ways of working, and personal journeys that reflect the evolving culture of IT at Microsoft.

May 21, 2026

Matthew Cooke

IT on the cutting edge: Working in Microsoft Digital in the era of AI

• Powering the new age of AI-led engineering in IT at Microsoft – Inside Track Blog
• The Frontier Firm: How knowledge workers are forging their own AI tools at Microsoft – Inside Track Blog
• The future of work is here: Transforming our employee experience with AI – Inside Track Blog
• Olutunde Makinde: From Lagos to Redmond, a Microsoft IT engineer’s journey – Inside Track Blog
• Building from the inside: Anahit Hovhannisyan’s impact on IT at Microsoft – Inside Track Blog

Key takeaways

From our journey enabling agentic AI across Microsoft Digital, several key principles have emerged to help organizations move from experimentation to scalable, enterprise-wide impact.

• Treat your organization as Customer Zero. Use your own AI capabilities first to generate real-world insights, validate scenarios, and build credibility before scaling to customers.
• Build a foundation for scale. Establish a secure, governed, and extensible platform that enables developers to create AI agents—from simple solutions to enterprise-grade applications.
• Empower developers to drive transformation. Move beyond productivity gains by enabling developers to build intelligent agents that automate workflows and unlock new business value.
• Align governance with innovation. Rethink how you enable development, govern AI, and operate at scale to balance flexibility with responsible use.
• Connect tools, platforms, and workflows. Integrate AI capabilities across your ecosystem—linking platforms, governance models, and development tools to support consistent, scalable adoption.
• Translate experimentation into impact. Focus on turning early AI exploration into coordinated, enterprise-wide efforts that deliver measurable outcomes.

Try it out

Learn more about Microsoft Build.

Related links

• Read our guide for deploying AI agents based on our experience at Microsoft.
• Learn about how we’re governing AI agents at scale internally.
• Find out how Work IQ is supercharging our AI usage at Microsoft.
• Check out an IT playbook for the AI era and see how we’re becoming a Frontier Firm.

The post Microsoft Build 2026: Empowering our developers to adopt agentic AI at Microsoft appeared first on Inside Track Blog.

For years, our security groups operated without consistent, policy‑based guardrails. As a result, we couldn’t uniformly control guest access to sensitive resources or apply governance consistently across different group types.

Addressing this required a complex, coordinated effort by our team here in Microsoft Digital, the company’s IT organization, and the Microsoft Entra product team.

“Because IT security is our highest priority at Microsoft, we knew we needed a better approach to limiting access to groups within our tenant. And we realized that Microsoft Entra was a powerful in-house solution that represented our best path forward to solve for this challenge.”

David Johnson, principal product manager architect, Microsoft Digital

The result is a new approach to sensitivity labels across the organization that strengthens our security posture, which benefits Microsoft and our customers.

“Because IT security is our highest priority at Microsoft, we knew we needed a better approach to limiting access to groups within our tenant,” says David Johnson, a principal product manager architect in Microsoft Digital. “And we realized that Microsoft Entra was a powerful in-house solution that represented our best path forward to solve for this challenge.”

Go deeper

Learn how to assign sensitivity labels to Microsoft Entra security groups.

Closing the security gap

Sensitivity labels for Microsoft 365 groups are labels that govern join and access restrictions for membership and sharing. They have been a product feature since 2020. But sensitivity labels for security groups—labels that enforce rules about who can join a group—had no equivalent.

This meant that organizations that wanted to govern who could join a security group or determine if guests are permitted and how group membership is managed had to either lock down the group creation process entirely, or rely on reactive scanning after the fact.

“Security groups are a key piece of our efforts to secure sensitive resources,” says Mohit Bhargava, a principal product manager on the Microsoft Entra team, which manages the Entra family of identity and network access products. “We wanted to apply policies to protect who could be in security groups so that the sensitive resources in those groups would remain secure.”

“Whoever gets into an Azure security group can have access to all the resources associated with the Azure subscription. That’s a potential high-severity threat.”

Basanth Kakumani, software engineer II, Microsoft Digital

The security risk is real. If an unauthorized guest account ends up as a member of a security group that governs access to an Azure subscription, that guest gains access to every resource inside that subscription.

“Whoever gets into an Azure security group can have access to all the resources associated with the Azure subscription,” says Basanth Kakumani, a software engineer II in Microsoft Digital. “That’s a potential high-severity threat.”

Another priority was the need for consistency across experiences.

“Microsoft 365 groups have supported labeling for a very long time,” Bhargava says. “Customers have an expectation that there’s parity across group types, so that they can govern them uniformly. That was another driving factor for this work.”

Security groups reuse the same sensitivity labels already configured for Microsoft 365 groups and SharePoint sites in Microsoft Purview—so admins don’t need to create or manage a separate set of labels. This reuse reduces configuration overhead and supports a more consistent governance model across group types.

Security workarounds, and why they fell short

Without sensitivity label support, we had to make do with alternative solutions. The most common one was simply preventing certain users from creating any security groups at all.

In the Microsoft tenant, this meant that employees who needed a security group had to fill out a form that had custom business logic behind it.

“We had on-premises, Active Directory, synchronization, tooling, and customization,” Johnson says. “This caused latency, from the time you created your group to the time it would show cloud membership. If you wanted to manage your membership, you had to do it on premises, AD, and then wait for it to sync to Entra.”

Neither centralized control nor reactive governance was a satisfying solution to prevent policy violations.

“This is really about making reactive things more proactive. We want to catch problems before they occur.”

John Begley, principal software engineer, Microsoft Digital

Typically, IT is going to manage this in one of two ways: Either we turn off self-service and manage everything on behalf of users, or we do reactive governance, which includes scanning groups and looking for policy violations.

Those aren’t super effective at preempting violations.

“This is really about making reactive things more proactive,” says John Begley, a principal software engineer in Microsoft Digital. “We want to catch problems before they occur.”

A collaborative solution

Coming up with a solution to this challenge required a genuine partnership.

We at Microsoft Digital approached the Entra product team and explained the problem we were trying to solve. Rather than simply handling this as a feature request, the two teams agreed to a co-development arrangement.

“Having access to a very large customer who cares deeply about security was extremely helpful. If it works for Microsoft, which is so complicated and huge, it’s going to work for smaller-sized tenants too.”

Mohit Bhargava, principal product manager, Microsoft Entra

Microsoft Digital team members would work alongside Entra engineers as the feature was built, serving simultaneously as implementation partner, design critic, and test environment—what we like to call our Customer Zero role.

Bhargava found the partnership equally illuminating from the product side.

“Having access to a very large customer who cares deeply about security was extremely helpful,” he says. “If it works for Microsoft, which is so complicated and huge, it’s going to work for smaller-sized tenants too.”

For Begley and his team, working closely with the product team revealed how complex the solution actually was.

“Both the product team and Microsoft Digital walked into this thinking a fix was going to be simpler than what it turned out to be,” Begley says. “It’s been eye-opening to see how the product is built, how it runs, what all the moving parts are. We learned early on that there was significant co‑development happening within Entra itself, across teams with very different areas of expertise.”

That dynamic played out in specific feature decisions. The team’s original plan did not include support for agent access controls and didn’t include the ability to prevent AI agents from joining sensitive security groups. This is something the product group quickly addressed and resolved after our team in Microsoft Digital raised it as a concern.

“One of the first customers who raised it was Microsoft Digital,” Bhargava says. “They said we needed need to start thinking about it ahead of time to get ahead of the problem.”

Sensitivity labels for Microsoft Entra cloud security groups are now in public preview. The same labels you publish in Microsoft Purview for Microsoft 365 groups and sites now apply to Entra security groups. Visit Microsoft Learn for scope, supported scenarios, and current preview behaviors.

Changes afoot for IT admins and employees

The practical impact of this solution lands on both sides of the relationship between Microsoft Digital and the company’s employees.

“Now I can’t accidentally have guests in an internal-only group, which changes the dynamic. Employees can create their own Entra security groups now, without us having to worry that they’ll be inviting guests where they shouldn’t be.”

David Johnson, principal product manager architect, Microsoft Digital

For IT admins, the shift is from reactive remediation to proactive prevention. For employees, it means self-service action with security groups become viable again, without the security risks that made organizations reluctant to enable it before.

“Now I can’t accidentally have guests in an internal-only group, which changes the dynamic,” Johnson says. “Employees can create their own Entra security groups now, without us having to worry that they’ll be inviting guests where they shouldn’t be.”

Johnson underscores the broader ambition behind the shift, which is to allow employees to create and manage groups directly in Entra.

“A company that can unblock self-service action by its employees with confidence, knowing that there’s an additional level of protection—that’s very important,” he says.

Looking ahead: AI and the expanding policy surface

Labeling support for security groups is already being extended across the organization, with AI governance in mind.

Adding the ability to block agents from joining sensitive security groups is our next logical step. Guest membership is enforced via allow-to-add guest policy, but agents won’t join in the same way. Rather, we will set policies in Purview and then use labels to control if an agent can join a group.

The longer-term vision involves extending oversharing prevention beyond Entra itself. This will make it impossible (not just detectable) to accidentally assign a highly confidential resource to an unlabeled or inappropriately scoped security group. The foundation we’ve built with labeling in Entra is what makes this vital step possible.

“We want to get into the preventative aspect,” Johnson says. “The goal is to make it so it’s not possible to overshare in the first place.”

Key takeaways

Here are some tips as you consider ways to address how you manage your own security labeling practices:  

• Reuse existing labels—no extra setup required. Security groups reuse the same sensitivity labels already configured for Microsoft 365 Groups and SharePoint sites in Microsoft Purview, eliminating duplicate configuration and helping admins apply a consistent governance model across group types.
• Understand label immutability at launch. Unlike Microsoft 365 Groups, sensitivity labels on security groups are initially immutable—a deliberate design choice to ensure protections are enforced from the moment a group is created. Controlled label mutability will be introduced in a subsequent update.
• Know what’s in scope today. Labeling currently applies to static, non–mail-enabled security groups. Dynamic membership groups, mail-enabled security groups, and distribution lists aren’t supported at launch, so admins should plan accordingly.
• Shift from reactive cleanup to proactive protection. Label-driven membership controls prevent policy violations—such as unintended guest access—before they occur, reducing the need for post-creation audits and remediation.
• Enable safe self-service with guardrails. With labels enforcing access rules automatically, employees can create and manage security groups without increasing risk, restoring self-service without sacrificing control.
• Lay the foundation for future governance scenarios. Using sensitivity labels as the backbone of access policy creates a scalable framework that can extend to additional protections over time, including broader enforcement and emerging governance needs.

Try it out

Learn more about configuring security with Microsoft Entra.

Related links

• Learn how we’re using sensitivity labels to make Microsoft more secure.
• Get an overview of Microsoft Entra fundamentals documentation.
• Find out how self-service sensitivity labels to help our employees stay productive without exposing sensitive information.
• See what it took to transition our company to a Zero Trust security model.
• Explore how we’re boosting our Secure Future Initiative with a new approach to wired network security.

The post Transforming our approach to sensitivity labels at Microsoft with Microsoft Entra appeared first on Inside Track Blog.

• Introduction
• Chapter 1: Building your agent governance strategy
• Chapter 2: Establishing a solid data foundation for agent governance
• Chapter 3: A matrixed approach to agent governance
• Chapter 4: Tracking, impact, and value
• Conclusion: Governing the frontier

Empowering employees and protecting your organization through agent governance

Welcome to the agentic frontier

Agents are expanding the frontier of enterprise AI. By creating tools that surface knowledge, take actions, and even reinvent workflows, organizations can apply the power of AI to business processes in new and innovative ways.

But this shift raises questions for business and IT leaders: How do you get the benefits of agents without putting your organization and employees at risk? How do you encourage citizen developers to create agents freely while maintaining control, security, privacy, and compliance?

At Microsoft Digital, the company’s IT organization, we’re putting practical governance structures in place to ensure our internal agents are useful, safe, and properly scoped. Through a deliberate strategy of empowerment with established guardrails, we’re unlocking the potential of agentic transformation while maintaining the trust that defines our work.

Read and prepare

Check out our complete guide to deploying and adopting agents across the enterprise, based on our own experience here at Microsoft.

The AI maturity model and frontier transformation

Agentic AI has made a new operational model possible, one that blends machine intelligence with human judgment, creating AI-operated, human-led teams.

We call organizations that enact this model Frontier Firms.

As organizations move toward this new operational state, they progress from foundational AI assistance through escalating levels of agentic maturity and complexity. First, humans operate with help from an AI assistant like Microsoft 365 Copilot. Then, human-agent teams work together. But the future lies with humans leading teams of agent users: AI agents that perform core labor with relative autonomy.

Capturing the benefits of this model relies on many factors, but in our experience as Microsoft Digital, two main tenets are instrumental to a successful transformation:

1. Empowering employees and teams to create and experiment with their own agents
2. Properly governing those agents to protect the enterprise

It’s a balance. If you set agent builders free without the proper guardrails, you risk data overexposure, agent sprawl, and security vulnerabilities. However, being too restrictive about governance stifles individual imagination, workflow reinvention, and innovation that can come from agentic AI.

“At Microsoft, we’ve moved beyond envisioning the agentic future into operating within it every day. Our experience as Customer Zero gives us a unique perspective on what it takes to govern AI agents at scale, turning early lessons into proven practices that help organizations innovate with confidence.”

Brian Fielder, vice president, Microsoft Digital

We’re here to help you find the right balance for your organization.

This guide shares what we’ve learned along the way. As you read, you’ll follow our journey as Customer Zero at Microsoft, and you’ll gain access to tips and resources that we’ve assembled to help you apply our expertise to your own agent governance practice.

Every organization is different, and your experience will differ from ours in terms of risk tolerance, technical capability, resourcing, and more. This guide highlights some principles and best practices you can apply to your own business context, needs, and objectives.

“At Microsoft, we’ve moved beyond envisioning the agentic future into operating within it every day,” says Brian Fielder, vice president of Microsoft Digital. “Our experience as Customer Zero gives us a unique perspective on what it takes to govern AI agents at scale, turning early lessons into proven practices that help organizations innovate with confidence.”

Now is the time to seize this opportunity. Follow along to start your own journey toward frontier transformation and capture the benefits of trusted, connected agentic intelligence.

Learn from our experience governing agents

Within Microsoft Digital, we’ve been acting as Customer Zero for frontier transformation by creating the tools, infrastructure, and processes that power agents at Microsoft.

Our goal is to make it easy for employees to engage with agentic tools freely and adaptably while maintaining safety and responsibility. The path to this objective relies on a three-pronged approach to governance:

• Embedded governance functionality: Agent creation and publishing tools should incorporate good guidance, governance, and guardrails out of the box, making agents people create essentially self-governing.
• IT oversight: This is a new space and a new way of working, so it isn’t feasible for all agents to self-govern at this point. As an IT organization, we fill gaps in governance through reviews and oversight. We establish risk-based policies around types of agents, exposure and sharing, and other pivots.
• User education: It’s almost impossible to predict every governance gap and need, so educating our users helps them avoid accidentally increasing risk. Our Agents at Microsoft team and individual change managers are the guides for these efforts. Employees can also refer to resources like Microsoft Learn courses and the Agent Builders SharePoint hub.

Throughout this journey, we’ve empowered our employees to create all kinds of agents, ranging from simple personal tools built by people working in every function, with every level of technical skill, all the way to AI-powered enterprise tools designed by professional developers for use across lines of business and even the entire company.

As part of the process, we’ve incorporated guardrails to ensure less technical employees are limited to tools that simply retrieve enterprise knowledge, such as SharePoint Agent Builder or Copilot Studio, while software engineers get the full power of any tool they need that can take action or automate workflows, including Microsoft Foundry and Microsoft 365 Agent Toolkit.

Over the course of this journey, we’ve learned valuable lessons about effective agent governance, including:

• How to build an impactful but flexible governance strategy
• Strategies for creating an AI-ready data ecosystem
• Ways to apply appropriate policies and controls for highly diverse agents
• Approaches for tracking the impact and value of agents

Chapter 1: Building your agent governance strategy

Thinking through your organizational needs and building a framework to govern agents

As we’ve incorporated agents into different aspects of our organization, we’ve also deepened their involvement in employees’ daily workflows and core business processes. Because of this, we’re diligent about the governance guardrails and policies that protect our organization.

We’ve accumulated a wealth of knowledge and insights in this area through our efforts governing Microsoft 365 Copilot. Based on this experience, some of the key priorities that we made sure to adhere to included:

• Effectively applying controls to ensure users and apps don’t get access to privileged information
• Preventing employees from creating agents that violate company policies
• Balancing the freedom for employees to share their creations with the need to prevent agent sprawl
• Delineating which agents are authoritative and applicable for enterprise functions and which ones are meant for employees’ own personal use.
• Inventorying agents to provide lifecycle management
• Securing and protecting confidential data while respecting our responsible AI principles: Fairness, reliability and safety, privacy and security, transparency, accountability, and inclusiveness
• Unlocking telemetry that enables us to govern agents effectively

By focusing on each of these dimensions, our governance team has centered its efforts on the value these agents provide to the company while also ensuring organizational safety and trust. To realize this value, we emphasize three key principles that help protect both our employees and the organization:

Security

We’ve established standards for data classification, policies for handling confidential information, and other security measures to protect data from unauthorized access, misuse, and disclosures. Microsoft Purview powers these capabilities through data labeling, rights management, and data loss prevention.

Privacy

Privacy compliance measures keep personal data protected and ensure agents adhere to regulatory frameworks in the regions where we operate. We conduct regular privacy assessments for all applications, including high-impact agents.

Regulation

Regulatory compliance assessments ensure agents meet prevailing legal standards. Our legal and compliance teams carefully monitor AI guidelines, regulations, and laws as they evolve so we can understand and incorporate them into these assessments.

We incorporated elements of our tenant’s minimum bar for governance into how we secure agents. Those include Microsoft Purview Information Protection, a functional inventory, activity logging, lifecycle management, and the ability to properly isolate agents so that they don’t cross data boundaries.

Our overarching tenant governance strategy is to govern items like documents and data at the container level. However, within a SharePoint site, for example, the added functionality of agents demands that we introduce further controls like sharing limits, breadth of knowledge sources, agent metadata, and information about an agent’s behaviors.

Turning priorities into principles

To operationalize governance, we developed six principles that guide our approach to agents. They form the governance foundation for a wide matrix of agent creation and usage opportunities.

1. We ensure a strong data hygiene foundation so we can trust our data estate as employees build and use agents.
2. We empower employees to build personal agents that can access permitted services and data sources to help automate and accelerate their tasks.
3. We empower teams and lines of business to build agents with known lower-risk patterns to accelerate impact.
4. We provide a smooth release path for engineering teams to develop agents designed for enterprise functions so they can access all the services and sources they need. This includes the same software development lifecycle (SDLC) reviews and certifications as other enterprise software, which we outline in Chapter 3.
5. We accelerate innovation through agent and automation templates while maintaining an AI Center of Excellence (CoE) to help teams think through their opportunities.
6. We reimagine employee experiences and task execution to simplify and optimize productivity.

Read and prepare

Powering the technical veracity of AI at Microsoft with a Center of Excellence.

Securing control through agent lifecycles

As we strategized to operationalize good governance, agent lifecycles became one of our most crucial tools. We superimposed the enterprise lifecycle on top of these policies, with both user-based and attestation-based lifecycles.

This means we treat agents owned by individual employees like any other user app and delete them when they leave the organization. Meanwhile, we ensure that agents owned by teams have a lifecycle that’s defined by the tenant and tied to attestation, our internal enterprise SDLC, and accountability confirmations.

This approach helps us combat sprawl by eliminating agents that no longer serve a purpose. It provides a solid foundation for more fine-tuned, matrixed policies and practices.

Governing amid real-time technology acceleration

One recent development illustrates how the rapid advancement of AI technology requires us to stay ahead of policy for new features.

Model Context Protocol (MCP) adds new capabilities, but also new risks and challenges. It’s a simple standard that lets AI systems communicate with the right tools and data without custom integration work. Instead of building a new connection or API every time, teams plug into a common pattern.

That standardization delivers speed and flexibility, but it also changes the security equation. We’ve extended our security and governance practices to account for MCP servers.

Our practices and policies help us govern agents effectively in this new environment. First, we assess security across four layers: Applications and agents, the AI platform, data, and infrastructure. We establish a secure-by-default strategy by positioning every remote MCP server behind our API gateway and establishing practices for vetting, identity management, automation that slows agents at the right moments, context trimming, and server isolation.

As you define policies for governing your own agentic ecosystem, you can take inspiration from our process. Start by asking questions about what you want to accomplish and what you want to protect, then move on to establishing your most important priorities. From there, you can cement those priorities into policies.

Learning from our approach to agent governance strategy

Match policies to progress on your AI journey

The complexity of agent governance depends on the maturity of your organization and where you are in your adoption journey. Start slowly to let that maturity grow over time.

A strong policy framework is the foundation

Lean on existing app governance policies, then layer agent-specific structures on top.

Take your cues from established standards

Global regulations around privacy, security, and responsible AI provide a good baseline for establishing governance policies. Assign teams to work through these regulations and incorporate their insights into your agent governance strategy.

Decide on your comfort level with risk

Bring cross-disciplinary experts together from across your organization to determine what level of risk is acceptable for different agents and their use cases. Put guardrails in place for low-risk scenarios and establish processes for supporting more complex or sensitive use cases. Evaluate what data sources agents can extract information from. Establish whether users have shared sensitive data sources.

Change is constant

Plan to reassess and revise your governance structure regularly. Agents are evolving rapidly, as is the tooling surrounding them, so maintaining good governance policies will be an ongoing practice.

Governance is a value driver for employees

Governance isn’t just about protecting your organization. It also provides the right patterns to make sure your employees are getting value from agents. Establish strong measures of business value and a robust methodology for management and assessment of agents through ongoing tracking. This kind of observation and telemetry is foundational and should be a key part of your governance efforts.

Key takeaways

Use these tips based on what we learned here at Microsoft to build your strategy for agent governance at your company:

• Establish a cross-disciplinary agent Center of Excellence. Bring together stakeholders across the organization to define priorities, goals, and shared practices for agent adoption.
• Right-size oversight based on risk. Determine your organization’s risk tolerance and define which agents require more or less involvement from IT, security, and compliance teams.
• Operationalize agent oversight and management. Establish an oversight model and implement tools that help manage agents at scale.
• Establish change management and adoption. Determine and implement a strategy for driving adoption to educate and empower employees.
• Create a centralized governance and information hub. Provide employees and agent builders with a single place to find guidance, standards, and governance information.

Learn more

How we did it at Microsoft

• Find out how we’re protecting AI conversations at Microsoft with MCP security and governance. This post outlines how we’re streamlining MCP governance through secure-by-default architecture, automation, and inventory.
• Explore our IT playbook for the AI era and learn how we’re becoming a Frontier Firm. This article shares our journey as an IT organization in support of this new operating model.
• Discover how Microsoft is becoming an AI-first Frontier Firm. This story shares how we’re approaching the idea of an agentic future.
• Read our five-step guide for IT leaders who want to drive greater AI maturity. This resource can help you chart a course through AI maturity to reimagine what’s possible for the enterprise.
• Learn from our experience tackling Microsoft 365 Copilot governance. This guide details our governance efforts for Microsoft 365 Copilot and can serve as a starting point for agentic governance.

Further guidance for you

• Secure your agents at scale with Microsoft Agent 365 guidance for unified identity, compliance, and control across platforms.
• Learn about the responsible AI policies and practices that guide our use of AI at Microsoft.

Chapter 2: Establishing a solid data foundation for agent governance

Setting agents up for success using a secure, robust data foundation

Operating according to an escalating maturity model means we’ve done the foundational work to secure and govern our data estate for Microsoft 365 Copilot. Many of the same principles apply to agents, with the added complexity of incorporating additional data sources.

To lead these efforts, we established a cross-functional team of data professionals within our AI CoE. This team is mostly comprised of Microsoft Digital employees who support corporate functions like Corporate, External, and Legal Affairs (CELA) and Global Workplace Services. Together with our AI CoE, this team helped us define what it means to have AI-ready data.

In essence, AI-ready data just means information we’ve certified for AI workloads. We certify those data sources using Microsoft Purview to identify defects in our core data products, and we’ve also built AI-powered assessments to certify which data lakes are AI-ready.

In most ways, governance is tool-agnostic and rooted in basic principles. With robust data labeling, data hygiene, and permissions in place alongside our AI tools, which respect labels by default, we can confidently give every employee the ability to build basic agents and trust in our governance guardrails. For decades, the challenge of data analysts and engineers was maintaining a consistently reliable source of truth despite inconsistent data quality, insufficient governance, and years of collecting data in silos. Microsoft Fabric and Microsoft Purview can help resolve these issues.

We’re embracing a more balanced, federated approach to data management today. We call this approach a data mesh. Rather than allowing unchecked decentralization or forcing all our data into a single centralized system, the data mesh formalizes domain ownership while embedding governance, quality, and interoperability directly into shared platforms.

The data mesh connects and distributes, data products across domains, enabling shared data access and compute while scaling beyond centralized architectures.

Platform services are standardized blueprints that embed security, interoperability, policies, standards, and core capabilities — providing guardrails that enable speed without fragmentation.

Data management zones provide centralized governance capabilities for policy enforcement, lineage, observability, compliance, and enterprise-width trust.

With this approach, our domain teams publish data as well-defined, discoverable products, while common standards for security, metadata, and compliance are enforced through automation rather than manual processes. This model preserves enterprise trust and consistency without sacrificing speed or autonomy. By adopting a data mesh mindset, we can scale analytics and AI more effectively across the organization while still keeping ownership closely connected to the business focus.

Confidentiality labels, the practical framework for data protection

To operate according to Zero Trust principles, we needed a coherent system that lets us see, label, and protect data. Otherwise, the burden of data loss prevention would fall solely on employees, who would have to exercise individual discretion whenever they decided how to house and share potentially sensitive content.

With labeling, it’s important to strike a balance between the depth necessary for supporting an array of data governance controls and the simplicity to ensure labeling isn’t burdensome for users.

We decided on four overarching labels for container and file classification, each with its own sub-labels. The highest-level schema looks like this:

1. Highly confidential: We only share our most critical data with named recipients.
2. Confidential: Any items crucial to achieving our goals feature limited distribution.
3. General: Employees can share daily work–like personal settings and postal codes–internally throughout Microsoft.
4. Public: We share unrestricted data meant for public consumption freely. That includes information like publicly released source code and openly announced financials.

For our risk tolerance and organizational needs, we made the decision to protect data designated confidential or higher. As a result, we contain data flows to their tenants and only trust suitable storage destinations for content. That suitability depends on a storage location’s ability to gate which connectors can work with particular source data and sensitivity labels.

The administrators responsible for workspaces like SharePoint sites set default labels. These labels serve as a foundation for appropriate access and circulation for objects within those containers. It takes the burden of labeling off of employees. The sensitivity labels that administrators apply map to several different categories of policies that can anticipate and help to mitigate data loss and risk.

They communicate four key areas:

1. Breadth of availability: Labels determine whether the workspace is broadly available internally or is a private site.
2. External permissions: We administer guest allowance via the group’s classification, allowing specified partners to access teams when appropriate.
3. Sharing guidelines: We tie important governance policies to the container’s label. For example, can an employee share this workspace outside of Microsoft? Is this group limited to a specific division or team? Is it restricted to specific people? The label establishes these rules.
4. Conditional access: While we haven’t implemented this policy at Microsoft, tying identity and device verification to container labels can introduce additional governance controls.

Within Microsoft Digital, we’ve put a lot of thought into how each of our labels aligns with relevant policies. You can see more of the logic behind our sensitivity labels and their policies in this graphic:

If a container owner needs different policies for a set of files to provide greater external access, they can self-service new groups without accidentally violating our governance practices.

At Microsoft, we use Microsoft Purview, which is our suite of data estate management tools, but you can use your tool of choice to apply labels in your environment. Microsoft tools will respect them. Microsoft Purview helps us accomplish three important tasks: mapping our labeling structure onto the relevant policies, verifying them against our standards, and backstopping self-service data loss prevention practices through automation.

Automation is particularly useful. We’ve configured Microsoft Purview Information Protection to scan automatically for wayward credentials, malicious user behaviors, and other sensitive information in items without the proper protections. When Purview detects a violation, our governance team receives alerts that prompt them to contain the risk by upgrading an item’s sensitivity label or requiring employees to remedy the issue.

The result is a system that allows flexibility for employees to self-manage their digital workspaces while providing guardrails that help our governance experts take appropriate actions without overtaxing their time and resources.

Our approach within Microsoft Digital is just one way to create an AI-ready data estate, but aspects of our story will hold true for almost any organization. Consider establishing a body to take over responsibility for AI-ready data, developing your primary goals for AI-ready data, unifying your data estate, and implementing a system of confidentiality labels.

Learning from our approach to agent governance strategy

Define the responsibility for AI-ready data

Identify and assign enterprise data owners to implement and oversee the processes that guarantee data quality.

Create intuitive labels

Your employees will be the ones applying labels, so make those labels intuitive. For example, “highly confidential” is easy to understand, while “business-critical” could be interpreted in many ways from a sensitivity standpoint.

Don’t overwhelm your users

Make labeling simple and intuitive to ensure it isn’t overwhelming. Employees should have a limited set of choices to keep things comprehensible.

Use existing defaults

Identify the security needs and regulatory compliance that are specific to your organization and use built-in governance controls available through Microsoft tools.

Key takeaways

You can use these tips based on what we learned here at Microsoft to tackle agent governance at your company:

• Establish a cross-functional data council. Form a data council to help promote a culture of AI-ready data with professionals from all relevant disciplines, including human resources, legal, security, IT, and anyone else who can share relevant expertise.
• Certify datasets for AI workloads. Limit agents to datasets that have been certified as “AI-ready” to minimize hallucinations and reasoning errors.
• Define your labeling parameters. Keep the number of labels to five main labels with five sub-labels each. The fewer you use, the better.
• Align your sensitivity labels with policies. Consider how your labels line up with breadth of availability, external permissions, sharing guidelines, and conditional access.

Learn more

How we did it at Microsoft

• Follow our journey as we transform our data culture with AI-ready data. This story highlights how we’re using Microsoft Fabric and Microsoft Purview to revolutionize our approach to data governance and AI readiness here at Microsoft.
• Discover how a data council is powering our unified data strategy at Microsoft. This post tells the story of how the Microsoft Digital Data Council is leading our efforts to adopt an AI-ready data strategy.
• See how we’re conditioning our unstructured data for AI at Microsoft. This article explains our internal strategies for handling unstructured data, which can be surfaced by AI agents.

Further guidance for you

• Learn about governance and security for agents and how to keep your AI initiatives secure across your organization.
• Establish responsible AI policies for AI agents to support ethical, transparent, and accountable AI agent deployment across your organization.

Chapter 3: A matrixed approach to agent governance

Governing different types of agents for different contexts, built with different toolsets

Our customers have expressed a strong desire to start building agents, but they’re concerned about where to begin and how to manage those agents once they’re built. They worry about persistent problems such as hallucinations and agent sprawl. These concerns are especially pronounced on IT teams.

During our Customer Zero journey, we’ve learned that the diversity of agent types and creation methods means there’s no one-size-fits-all approach to governance. Generalized approaches will only get you so far.

We’ve found it helpful to think about different kinds of agents along an escalating spectrum of development complexity:

There’s an entire matrix of different parameters that apply to an agent at any level of this spectrum, and they all require different policies. Those parameters include:

• Level of reach: Personal agents, limited sharing (like development environments or team boundaries), or enterprise-wide distribution
• Agent-building tool: SharePoint agent builder, Agent Builder in Microsoft 365 Copilot, Microsoft Copilot Studio, or tools geared to more professional developers (such as Microsoft Foundry or Microsoft 365 Agent Toolkit)
• Knowledge sources and content accuracy: Public sites, SharePoint and OneDrive, directly uploaded files, enterprise apps and systems, or third-party knowledge bases

Each of these parameters creates a pivot that we need to govern, and we’ve carefully assembled a set of policies and controls to account for them. As our understanding and use of agents advances, we’re continually updating how we match their characteristics and capabilities with relevant policies and any applicable reviews.

Within Microsoft Digital, we’ve adopted a risk-based approach that helps us establish a matrixed model for agent governance. The foundational idea is that we identify potential harms for each kind of agent, then assign policies for the level of review and oversight they require.

For example, simple agents that can only read and present data tend to be low risk. Because their access is tied to their creators’ identities and access, our data governance structures and guardrails can prevent overexposure. But for agents that have capabilities like writing data, taking action, or creating items, more reviews are necessary.

A matrix of agent governance policies, pivoted by parameter

The following matrix enumerates the factors that determine how we govern different kinds of agents created using different tools. This matrix helps our employees understand the agent creation process and helps us maintain safety and control.

In addition to mapping out our policies for governing agents, the matrix illustrates how we see their relative utility across the organization. It demonstrates an escalation from personally useful to organizationally useful agents. Their governance policies and controls escalate accordingly.

Regionality is an additional concern. Regulatory compliance might vary, but it’s important to keep in mind that certain kinds of data access and actions might be perfectly permissible in one region, but not in another.

One example is our Employee Self-Service Agent, a central resource employees can turn to for help with IT support, HR questions, and facilities requests. Because it can access potentially sensitive personal information, this agent required additional review from European works councils to ensure it met all relevant workplace standards.

As you facilitate the experimentation and innovation with agents across your workforce from citizen developers to pro developers, consider adopting a similar matrixed approach to agent governance. It starts with understanding your organization’s needs, your risk tolerance, and the different employee populations you want to equip with agent-building capabilities.

Learning from our matrixed approach to agent governance

Figure out your building environment strategy

Decide which scenarios match up with specific environments and make those environments available to the relevant employees.

Design governance structures that scale from low-code to more advanced agentic tools

With the proliferation of AI agents, platform-level approvals similar to the Power Platform model at Microsoft can ensure rapid innovation while requiring review for individual high-impact scenarios.

Build trust through transparency and structure

A clear, well-documented approval process helps internal regulatory advisors understand new AI technologies and establishes the trust needed for productive, long-term collaboration.

Treat regional partners as strategic allies in the agentic future

Early feedback on digital agents from regional partners like works councils helps improve product design, accelerate approvals, and reduce fear or misconceptions about AI in the workplace.

Don’t forget that Copilot Studio is part of Power Platform

You can use what you’ve learned empowering citizen developers in Power Platform to guide your work with agents.

Key takeaways

Use these tips based on what we learned here at Microsoft to tackle agent governance at your company:

• Establish your tolerance for risk. Determine where the most prevalent risks emerge across different populations and kinds of agents. Remember, you control the guardrails in your environment.
• Determine what agent-building tools you want to roll out and who can use them. Different populations benefit from different agent-building capabilities. Put thought into what individuals and teams can create and the degree of partnership each level will need from IT.
• Define your governance parameters for different kinds of agents. Determine the best ways to hedge against risk at every level. For example, you might choose to trust in tenant governance for simple agents and establish reviews for more complex tools.

Learn more

How we did it at Microsoft

• See how we’re empowering employees with the Power Platform. This article explains how our Power Platform governance model influenced our matrixed approach to agent governance.
• Learn how our employees are building their own AI tools. This article describes how knowledge workers at Microsoft are forging their own agents to help improve efficiency and get more done.
• Check out our lessons learned using SharePoint agents at Microsoft. This post shows how we approached governance for low-risk, knowledge-only agents through our deployment of SharePoint agents.
• Read how we’re unlocking enterprise AI extensibility with Copilot Studio. This story explores how we govern more advanced agents built with Copilot Studio, including connectors, orchestration, and scaled governance.

Further guidance for you

• Explore governance and security for AI agents across the organization with Microsoft Learn content.
• Check out this industry-standard framework that validates matrixed, risk-based governance approaches for AI systems.

Chapter 4: Tracking, impact, and value

Managing agents and assessing their business impact for the organization

It’s clear that agents bring astonishing capabilities to the enterprise. For many organizations, what remains unclear is exactly how to measure their impact. Without that information, businesses are at a loss for ways to articulate value and drive improvement.

Tracking agents is also a crucial component of preventing sprawl: We need to understand what agents we have, how employees are using them, what critical processes they’re supporting, and if they’re contributing value or need to be retired.

We’re at the beginning of our impact-tracking journey, but our work can provide a starting point for your own efforts to measure the value of AI initiatives at your organization.

Managing our agent catalog through comprehensive tracking

Microsoft Digital partners with other internal organizations to ensure we’re prioritizing the right agents and avoiding agent sprawl. Ideally, these engagements take place before teams start building their agents so we can avoid wasted effort or duplicated work.

Still, ongoing management efforts are crucial to keeping our agent ecosystem healthy. Telemetry is the key to assessing usage and ensuring compliance. We’ve developed our own internal tooling to ensure that:

• Metadata is complete and available
• The tooling tells us the right information about our agents
• The tools connect properly with other compliance tooling, like Microsoft Purview

This telemetry also reveals agent behaviors, shows how agents do their work, and tracks events, actions, and policy baselines.

These capabilities help us gain visibility into policy adherence and violations, and then to conduct enforcement actions. We also track the speed of reaction and mitigation. AI-ready data and robust guardrails mean we head off most violations before they occur.

A robust inventory, an agile policy framework, and an automated workflow for enforcement are cornerstones for successfully governing agents at scale.

The release of Microsoft Agent 365, now in early access, represents the next step in agent observability and management, two key aspects of agent governance and sprawl mitigation. This control pane for agents incorporates many of our learnings as we’ve bridged governance gaps through IT intervention.

Some of the key aspects of the control pane:

The registry

Provides a complete view of agents, and the enterprise agent store makes it easy to find the right agents for each role and business process within familiar workflows in Microsoft 365 Copilot and Teams.

Visualization

Delivers the observability layer, including role-specific oversight, compliance and audit features, and performance measurements that can help organizations track their agents’ impact and see where they contribute value.

Interoperability

Ensures Agent 365 is open to any Microsoft-built or partner ecosystem, while delivering work intelligence through access to data and Microsoft 365 apps.

Security features

Provide crucial confidence through visibility into security posture, detection and response capabilities, and intelligent runtime defense.

As Customer Zero for Agent 365, we’re excited to have a platform for observability and telemetry that encompasses everything from agentic creation through usage.

Tracking governance from agent inception

Professionally developed agents add a new dimension of tracking and governance, because we need standards in place for ensuring compliant agent-building and to remediate any issues.

We use our Azure DevOps instance to catalog apps on our tenant, and we’ve applied this practice to agents created professionally for lines of business and enterprise agents. This tool contains our service tree with product and app log registration, which is tied to our KPI dashboard and scoring system that validates agent data against our policies.

Our expectation is that all new apps and agents start from a place of compliance. Any new agent is registered through this platform, and we expect adherence within the first 14 days. In our experience, the introduction of new metrics, policies, or timeframes as our governance policies evolve is where agents tend to drop out of compliance. The priority is restoring compliant status.

We’ve established a series of metrics to help track and manage these expectations:

• Enablement velocity
• Renewal velocity
• Agents in compliance
• Time to remediation of noncompliance

Through a DevOps process built on our preexisting software development lifecycle practices, we’ve applied governance not only to agents themselves, but to the process of building them professionally.

Measuring progress and unlocking value

Properly measuring value depends on concrete definitions of success and metrics that support it. Articulating AI’s impact came with several challenges. First, we had to land on a consistent taxonomy for different measurement areas. Then we needed to make the relevant data accessible, ensure its quality, and confirm it made sense.

The Microsoft Digital AI Value Framework is our flexible, modular tool for measuring the impact of our AI initiatives. With tools for measurement firmly in place, we can effectively demonstrate value and guide further decision-making.

We plan to use the following capabilities to improve the overall ecosystem:

• Filtering our agent inventory on specific criteria like the type of agent or how it was built
• Enhancing governance-specific actions we can take with agents in areas like ownership and quarantining
• Gaining visibility into trends like agent usage
• Ingesting agent blueprints and defining policy templates

We’re still in the midst of our agentic measurement journey at Microsoft, but the blueprint for tracking already exists. Your organization might be in the early stages of agent readiness and deployment. If that’s the case, it could be helpful for you to internalize the lessons we’ve learned as Customer Zero and apply them as early as possible in your own journey toward AI maturity.

Learning from our agent adoption experience

Think proactively, not retroactively

If you put effort into tracking agentic impact early in your AI maturity journey, you’ll be poised to start capturing insights immediately instead of applying your methodology retroactively.

Involve a wide array of stakeholders

This workstream needs oversight from different kinds of stakeholders, including your leadership team, IT, Microsoft 365 administrators, agent developers and builders, and employee champions. That will provide the sponsorship, expertise, and perspective you need for success.

Different measurements will be appropriate for different phases of your initiatives

These measurements include monthly, weekly, or daily active usage; consider which metrics make sense at each phase of an AI initiative.

Establish a continuum of value

Agents need to tie into real business goals, so it’s important to establish metrics that actually speak to those objectives. Cascade business goals to concrete KPIs with well-defined timelines and track those diligently.

Embrace the red

Try to think of underperformance not as failure, but as data. Performance data over time helps you course correct or pivot, making sure you invest where it matters.

Key takeaways

Here are some important steps to keep in mind as you embark on your own tracking and measurement efforts for agents:

• Establish priorities and parameters for tracking agents. Consider measurements that relate to sprawl, usage, and coverage, and build them into your telemetry tooling.
• Pull your stakeholders together to establish measurement parameters. Cascade business priorities into measurable value.
• Conduct ongoing tracking. Establish a cadence for tracking and reviewing progress with your team.

Learn more

How we did it at Microsoft

• Learn how we’re measuring the impact of Microsoft 365 Copilot and AI at Microsoft. Discover our framework for tracking the impact of the investments in AI that we’re making internally.
• Find out how we’re deploying Microsoft Agent 365 internally. This story shares our intentions for using our unified control pane for agents.
• See how we’re building an AI-powered continuous improvement culture at Microsoft. This article outlines our approach to continuous improvement.
• Check out how we’re reshaping Microsoft with continuous improvement and AI. This post discusses the importance of continuous improvement for accelerating AI at Microsoft, including three initiatives already underway.

Further guidance for you

• This Microsoft Learn guidance helps organizations align AI investments with strategic goals and measurable outcomes over time.
• Explore a cloud adoption framework that provides practical guidance for defining success metrics, tracking ROI, and tying AI initiatives to business outcomes.

Governing the frontier to scale innovation

AI agents are rapidly becoming core contributors to how work gets done. As our experience within Microsoft Digital demonstrates, realizing their full potential demands more than powerful tools or enthusiastic builders. It requires thoughtful governance that evolves alongside your AI maturity, protects what matters, and gives employees the confidence to innovate responsibly.

As you consider your own strategy for managing agents, it can be helpful to keep one truth in mind: Governance is a catalyst for progress, not a barrier. By embedding guardrails into tools, grounding agent creation in AI‑ready data, applying risk‑based and matrixed policies, and reinforcing all of it through adoption and education, we’ve been able to expand agentic capability without sacrificing security, privacy, or trust.

From our experience, we’ve learned that governance works best when it’s:

• Proportional, scaling with risk and agent complexity
• Embedded, not bolted on after the fact
• Human‑led, recognizing that accountability and judgment remain essential
• Iterative, adapting as technology, regulations, and business needs evolve

When you design governance this way, it allows experimentation, learning, and impact at scale. Employees feel empowered to build agents that solve real problems, while IT and compliance teams gain visibility and control without becoming bottlenecks. Crucially, leaders can measure value, manage risk, and make informed decisions about where to invest next.

“At Microsoft, we believe the future of agentic AI depends on governance that empowers people first. The structures should be invisible when they’re working, intentional when they’re needed, and trusted by everyone they serve.”

Vijaya Alaparthi, principal group product manager, Microsoft Digital

This is the foundation of the Frontier Firm: Organizations where humans lead and agents operate, guided by clear principles and trusted systems.

As you continue your AI maturity journey, remember that there is no single, correct governance model. Your approach will reflect your risk tolerance, regulatory environment, data maturity, and organizational culture. The practices outlined here provide a proven starting point informed by real-world deployment at enterprise scale.

“At Microsoft, we believe the future of agentic AI depends on governance that empowers people first,” says Vijaya Alaparthi, principal group product manager in Microsoft Digital. “The structures should be invisible when they’re working, intentional when they’re needed, and trusted by everyone they serve.”

Now is the moment to act. Start with strong foundations. Empower your builders. Measure what matters. And treat governance not as a constraint, but as a strategic advantage that allows your organization to move faster, innovate safely, and lead confidently on the agentic frontier.

Key takeaways

Here are the high-level learnings and insights that you need to consider as you embark on your own agent governance journey, based on what we’ve learned here at Microsoft:

• Treat governance as an enabler of innovation, not a brake. Effective agent governance is what makes large‑scale innovation possible. When you embed guardrails into platforms, data, and processes, employees can build and experiment confidently without exposing the organization to unnecessary risk or slowing progress.
• Match governance rigor to agent risk and maturity. Not all agents need the same level of oversight. A risk‑based, matrixed approach lets organizations trust lightweight, personal agents while applying deeper reviews to agents that write data, take actions, or operate across business‑critical systems.
• Start with AI‑ready data and zero‑trust foundations. Strong agent governance rests on secure, well‑labeled, high‑quality data. Clear ownership, intuitive sensitivity labels, default protections, and automation reduce reliance on user judgment and allow agents to operate safely at scale.
• Embed governance where agents are built and used. The most effective governance is built into tools and workflows, not enforced through manual reviews alone. Defaults, limits, identity‑based access, lifecycle controls, and telemetry should apply automatically so agents are governed by design.
• Plan for the full agent lifecycle to prevent sprawl. Agent inventories, ownership models, attestation, and retirement processes are essential. Governance needs to account for how you create, share, evolve, audit, and ultimately decommission agents, whether individuals or enterprise teams are responsible for building them.
• Reinforce governance through adoption and education. Guardrails work best when employees understand them. Targeted adoption programs, clear guidance, prerequisites for advanced tools, and visible leadership sponsorship can help employees build responsibly and recognize their role in protecting the organization.
• Measure what matters to prove value and drive improvement. Visibility drives trust. Telemetry, observability, and clear metrics that span productivity, quality, risk reduction, and experience allow organizations to track impact, course‑correct early, and continuously improve their agent ecosystem.

Learn more

• Discover our IT playbook for becoming an AI-driven Frontier Firm.
• Learn how to secure your agents at scale with Microsoft Agent 365 guidance.
• Read a guide to governance and security for AI agents at your organization.
• Check out this detailed guide to our governance process for the internal rollout of Microsoft 365 Copilot.  
• Explore ways to establish responsible AI policies for agents across the organization.  
• Find out how a data council is powering our unified data strategy at Microsoft.

Try it out

Get started building and managing agents at your company with Microsoft Agent 365.

The post Governing AI agents at scale: Lessons from our journey at Microsoft appeared first on Inside Track Blog.

These innovations have come in many different forms across every group and function at the company. It’s impossible to capture them all in a single concept or story, but one of the ways that we’ve activated the power of AI for our workforce is Work IQ.

Work IQ isn’t a product.

It’s a shared intelligence layer that enables Microsoft 365 Copilot and AI agents to reason over and understand your organization’s work data, then use that context to generate more relevant responses and actions. This means that the entire Microsoft Graph—including rich unstructured data from your Teams chats and meetings, Outlook emails, Word documents, PowerPoint presentations, and more—is now part of your AI-powered work experience.

“It’s not really a brand-new capability, but more an evolution of what users already know, which is access to the grounding data in their Microsoft tenant. The difference is that Work IQ adds an additional layer to provide more context, allowing for richer and more relevant results.”

Aisha Hasan, principal product manager, Microsoft Digital

Work IQ enables Copilot to not only tailor answers to your role and responsibilities, but also to understand who your most frequent collaborators are, comprehend details about your latest projects, surface deliverables and deadlines, and intuit next steps. Additionally, Work IQ makes it easy for any AI agent to take advantage of the same rich enterprise data to return and act on more contextual results.

“It’s not really a brand-new capability, but more an evolution of what users already know, which is access to the grounding data in their Microsoft tenant,” says Aisha Hasan, a principal product manager in Microsoft Digital. “The difference is that Work IQ adds an additional layer to provide more context, allowing for richer and more relevant results.”

At Microsoft Digital, the company’s IT organization, we’ve seen firsthand how this intelligence layer is accelerating employee adoption of Copilot and agentic AI as outputs become more perceptive and valuable. Work IQ is a foundational step toward a future where AI has moved beyond isolated assistance and become a trusted professional helper—sometimes described as a digital colleague—that carries out tasks and anticipates needs in every aspect of daily work.

How Work IQ impacts everyday work

One of the most instructive aspects of Work IQ’s impact across our organization is that it happened without a traditional deployment. There was no enablement event for employees or operational playbook distributed to administrators. It didn’t require any changes to the application interfaces. Yet over time, our employee Copilot interactions improved in measurable ways.

“There was a period where we weren’t adding new content to Copilot, and yet I noticed our metrics for quality and user satisfaction kept going up. Why was that? It was because of all these incremental improvements that we refer to as Work IQ.”

Dodd Willingham, principal product manager, Microsoft Digital

This was a direct consequence of introducing a shared intelligence layer into a Microsoft environment that was already rich in work signals. Those work signals are extremely valuable data that was difficult to extract meaning from before the advent of AI. As the technology advanced, we could take full advantage of this data to inform and improve agentic responses.

As Customer Zero for the company, Microsoft Digital was at the forefront of measuring the impact of Work IQ. Our employees saw significant gains in relevance, grounding, and answer coherence in Copilot that were visible in the metrics, even during times when the underlying content remained relatively static. That’s the Work IQ difference.

“There was a period where we weren’t adding new content to Copilot, and yet I noticed our metrics for quality and user satisfaction kept going up,” says Dodd Willingham, a principal product manager in Microsoft Digital. “Why was that? It was because of all these incremental improvements that we refer to as Work IQ.”

At a systems level, Work IQ reasons across a broad cross-section of Microsoft 365 data, including:

• Outlook email content, thread structure, and interaction patterns
• Teams chats, channels, and meeting transcripts
• Calendar events and scheduling metadata
• Documents and files across Word, PowerPoint, Excel, OneDrive, and SharePoint
• Signals that show who collaborates with whom, how often, and in what context

Work IQ can also access structured data in tools like Dynamics 365, Power BI, Power Apps, and other business applications. The ability to extract context and interpret structured and unstructured data in a unified intelligence layer is the reason why Work IQ is making such a difference for our employees.

Making Outlook better

Outlook provides a useful lens on how Work IQ functions because it’s both heavily used by our employees and a highly contextual tool. Although the application hasn’t outwardly changed, the way Copilot interacts with inbox and calendar data has evolved, in part due to richer context provided by Work IQ.

“The intelligence works behind the scenes as you use Outlook. Your inbox just gradually feels more relevant. Outlook adapts to your work patterns, making your inbox feel more like an assistant, instead of a filing cabinet of communications.”

Matthew Marzynski, principal product manager, core experiences, Microsoft Digital

Now when you turn to Copilot in Outlook to summarize email threads, it can surface decision points, action owners, and unresolved issues. Instead of treating email as a collection of messages and providing rote summaries, Copilot perceives it as a record of decisions and commitments over time.

Calendar-related experiences are on a similar trajectory. Meeting preparation and follow‑up suggestions are now drawing on prior interactions with the same participants, relevant documents that were previously shared, and historical patterns around similar meetings.

Work IQ isn’t rule-based automation layered on top of Outlook. Users aren’t configuring new filters or workflows. Instead, the system is adapting based on observed patterns, meaning user behavior can remain the same while output quality improves

“The intelligence works behind the scenes as you use Outlook,” says Matthew Marzynski, a principal product manager for core experiences in Microsoft Digital. “Your inbox just gradually feels more relevant. Outlook adapts to your work patterns, making your inbox feel more like an assistant, instead of a filing cabinet of communications.”

Applying persistent memory

Another important aspect of Work IQ is the ability to retain persistent memory of each employee’s role, responsibilities, and work context. Copilot and other agents no longer need to be continually prompted with details about who the user is and what they’re working on. It learns that information and remembers it going forward.

This feature, also called persistent understanding, builds trust and increases efficiency each time an employee turns to AI for help with their work. AI systems that depend on manual context-setting don’t scale well across large organizations, which we at Microsoft Digital learned as we tested and deployed Copilot across the company.

“The user no longer has to tell the agent, ‘I work in this area, so please tailor your response to that’ every time,” says Anishkumar Ramakrishnan, a principal PM manager in Microsoft Digital. “With Work IQ, Copilot and agents recall it going forward. It remembers things that the user doesn’t even remember themselves about their past work and actions. This is the promise of intelligent context.”

From answers to action: Work IQ and AI agents

As organizations move toward integrating AI agents into all aspects of their day-to-day work, the value of Work IQ increases. Any agent—not just a general-purpose agent like Copilot—that can interpret vast amounts of your unstructured work data is going to produce results that are far more relevant than one that simply draws on general knowledge about a topic or process.

“Before, a builder had to go connector by connector and be very prescriptive—calendar read, email read, meeting access—just to build an agent. Now they can simply point the agent to Work IQ, and it gains contextual access across mail, calendar, meetings, and files through a single connector (API or MCP server).”

Naveen Jangir, principal architect, Microsoft Digital

Early agent implementations relied on narrower task-specific access to data. For each agent, a developer would have to build connections to a particular document library, mailbox, or set of calendar data. Each connection required separate consent and management, which generally resulted in a more limited scope.

But with Work IQ, builders can create agents using Microsoft Copilot Studio or other development platforms (such as Microsoft Foundry) that use APIs or Model Context Protocol (MCP) servers to connect to Microsoft Graph data. This enables them to bring the full power of enterprise data to any agentic creation, not just Microsoft 365 agents.

“Before, a builder had to go connector by connector and be very prescriptive—calendar read, email read, meeting access—just to build an agent,” says Naveen Jangir, a principal architect in Microsoft Digital. “Now they can simply point the agent to Work IQ, and it gains contextual access across mail, calendar, meetings, and files through a single connector (API or MCP server).”

This shift doesn’t just simplify agent development—it fundamentally expands what agents are capable of. Instead of operating within narrow, predefined tasks, agents can now reason across a broader work context to deliver better outcomes. For example, an agent supporting a project manager can surface relevant email threads, identify key stakeholders from meeting activity, reference the latest project documents, and highlight upcoming deadlines—all within a single interaction.

Intelligence without bypassing governance

From a governance perspective, Work IQ doesn’t introduce a new security model. Instead, it operates entirely within the existing Microsoft 365 data protection boundaries that our company and our customers already rely on.

The intelligence layer can access this enterprise data, but it does so while honoring permissions, sensitivity labels, access policies, and compliance controls defined at the source. Work IQ can only surface or act on information that the user—or an agent identity acting on the user’s behalf—is already authorized to access.

This inheritance model is intentional. Governance remains rooted in the data layer, not in the AI layer. Work IQ respects established controls such as identity‑based access and tenant policies, which means agents are generally given less access than human users.

“An agent user only gets access to what is explicitly shared with it,” Jangir says. “Human users typically have broader default access. By design in Work IQ, agents can usually see less than people, not more.”

For IT and security teams, this places the emphasis squarely on data discipline and identity controls, which are complementary security layers. Work IQ amplifies the value of well‑governed data and exposes weaknesses where governance is inconsistent. Admins remain in control of access and can turn off APIs and MCP server connections if they want to limit an agent’s data access.

Work IQ, Fabric IQ, and Foundry IQ

As we’ve scaled up Copilot and agentic AI internally, one lesson has become clear: Intelligence works best when it’s part of a layered infrastructure rather than working on its own.

That’s why Work IQ is just one context layer we’re using at Microsoft. We’ve also developed Fabric IQ and Foundry IQ, which are complementary layers in our overall data strategy. Each of these addresses a different aspect of enterprise intelligence.

The three layers serve distinct but connected purposes:

• Work IQ focuses on unstructured productivity data, helping AI understand how people work across email, meetings, documents, and collaboration signals.
• Fabric IQ applies similar reasoning to analytical and structured data, adding context and explanation to metrics, trends, KPIs, and other business signals.
• Foundry IQ provides the foundation for builders to create agents that draw from both worlds, connecting intelligence across Microsoft 365, analytics platforms, and line‑of‑business systems.

Taken together, these layers also contribute to something deeper: the emergence of a shared business ontology. By extracting and aligning business entities—such as people, projects, and processes—from both structured data in Fabric IQ and the unstructured signals captured by Work IQ, the system perceives meaningful connections that previously were hidden. This unified understanding allows agents to reason across domains with greater precision, linking metrics to the real work and making insights more actionable in context.

This architecture matters because it removes artificial seams. Agents shouldn’t need to shift between separate contexts for work content, enterprise data, or application logic. The IQ layers make it possible to deliver a single agentic experience that reasons consistently, applies governance uniformly, and moves with users across environments. Just as importantly, the same controls—identity, permissions, labeling, and policy—flow through each layer, keeping trust intact as capability expands.

At Microsoft, Work IQ and the other context layers are helping Copilot and agents to accelerate beyond AI experimentation. They are now vital operational tools that make everyone more productive across the global enterprise. Context and intelligence in agentic tools are a key part of the future of work, at Microsoft and for our customers as well.

Key takeaways

Here are some things to keep in mind as you prepare your own organization to take full advantage of Work IQ:

• Treat the technology as infrastructure, not a feature. We didn’t formally roll out Work IQ. Its value emerged gradually as it improved Copilot responses and as our agent builders could more easily tap into unstructured enterprise data.
• Expect improvements in AI quality without changes to your data. We saw measurable gains in relevance and user satisfaction even when underlying content remained the same, driven by better contextual reasoning across existing work signals.
• Focus on how employees work, not just what content exists. Work IQ improves AI outcomes by connecting people, relationships, and activity patterns, resulting in more actionable and grounded responses.
• Use Work IQ to move from assistance to action with agents. By giving agents access to contextual enterprise data through a unified layer, we enabled more automated workflows without requiring developers to manage dozens of connectors manually.
• Invest in data governance early to maximize AI value. Because Work IQ inherits permissions and policies from the data layer, its effectiveness—and safety—relies on clear labeling, intentional access design, and disciplined data management.
• Enable self-service collaboration data so it’s available for Work IQ. WorkIQ can only ground on data that is both available and not purposefully hidden. We make sure that our meetings are AI-enabled (and often recorded) and allow self-service in Teams and SharePoint, so the data is not hidden from Work IQ.
• Build toward a unified intelligence model across work and data. Combining Work IQ with Fabric IQ and Foundry IQ means agents can operate seamlessly across different kinds of data and incorporate more intelligence into their output and actions.

Try it out

Get a closer look at Work IQ.

Related links

• Check out how we’re embracing this agentic moment at Microsoft.
• Explore a Microsoft Learn article for more technical details about how Work IQ works.
• Learn how to get started building agents with Microsoft tools.
• Discover our detailed guide on how we deploy AI agents internally at Microsoft.
• Read an IT playbook for the AI era and learn how we’re becoming a Frontier Firm at Microsoft.
• See how we’re using Model Context Protocol security and governance to protect AI conversations at Microsoft.

The post How Work IQ is supercharging our AI usage at Microsoft appeared first on Inside Track Blog.

At Microsoft Digital, the company’s IT organization, we shape and propel many of our groundbreaking products through our role as the company’s Customer Zero—and we want to tell that story. At this year’s Microsoft 365 Community Conference, we hosted a variety of sessions focused on change management, AI adoption, and how we manage governance in the era of the Frontier Firm.

As Customer Zero for Microsoft 365 Copilot, we embedded the technology into our employees’ daily workflows and carefully monitored the results. That journey from early experimentation to broad adoption of the tool across our organization continues to guide the company as we explore what comes next.

Today, that’s agents.

“Copilot changes how our employees work. Agents are changing how the work gets done. Our focus is to make the technology practical and valuable, so people want to use it daily.”

Stephan Kerametlian, senior director, business program management, Microsoft Digital

We’ve reached a level of maturity with Copilot that allows us to move from individual productivity to systems that can reason and collaborate on our behalf. Our focus now is on driving the adoption of agents across the company, grounding them in our workflows to solve problems.

“Copilot changes how our employees work,” says Stephan Kerametlian, a senior director in Microsoft Digital. “Agents are changing how the work gets done. Our focus is to make the technology practical and valuable, so people want to use it daily.”

Adoption doesn’t happen without trust

As we’ve empowered employees with more capable AI tools that can help automate tasks and make decisions, we’ve been equally focused on making sure the right safeguards are in place.

Innovation and safety are extremely important—the challenge is to enable both at the same time. And this is where governance comes in.

“We’ve spent a lot of time getting governance right. This means giving people confidence, not slowing them down. When employees know the guardrails are there, they feel empowered to experiment and innovate safely.”

David Johnson, principal PM architect, Microsoft Digital

At Microsoft, good governance is what makes innovation sustainable. It’s how we protect the company, our data, and our customers, while still giving employees the freedom to build and push boundaries with AI.

“We’ve spent a lot of time getting governance right,” says David Johnson, a principal PM architect in Microsoft Digital. “This means giving people confidence, not slowing them down. When employees know the guardrails are there, they feel empowered to experiment and innovate safely.”

How Microsoft does IT: Managing and governing agents—empower with risk-aligned oversight

Session description: See how Microsoft Digital empowers employees with tools to build and manage agents. From agent management with Microsoft Agent 365, to securing our environment with Microsoft Defender, to managing our productivity estate with Microsoft Purview, this session offers broad insights into how we use our own technology to accelerate agentic innovation while mitigating risk.

Speakers: David Johnson, Naveen Jangir, and Mike Powers

David Johnson leads our internal Microsoft 365 and productivity services with responsibility for tenant strategy, architecture, and governance. He manages how we empower employees with guardrails and manages our capability onboarding and tenant configuration.

Naveen Jangir is a principal architect in Microsoft Digital. He drives Microsoft 365 security and compliance strategy and leads tenant architecture and capability onboarding, while overseeing secure adoption of services across the enterprise.

Mike Powers is a senior service engineer and AI administrator in Microsoft Digital who manages Copilot features, Agent 365, and enterprise AI operations. He partners with internal product groups and security stakeholders to make sure AI tools and agents are deployed responsibly and governed effectively.

More on AI agents and governance at Microsoft

• Read the guide to how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.
• See how we’re embracing the agentic future to become a Frontier Firm.
• Learn how we deployed the Employee Self-Service Agent at Microsoft. 

Inside Microsoft: Reclaiming engineering time with AI in Azure DevOps

Session description: AI tools embedded directly into Azure DevOps (ADO) are changing how engineering teams work, eliminating manual tasks without creating separate tools or increasing cognitive load. This session explores how ADO AI Chat and the AI Work Item Assistant accelerate coding workflows at Microsoft. You’ll learn how to improve your backlog quality, sprint hygiene, and downstream effectiveness of GitHub Enterprise and Copilot, helping your teams reclaim capacity and focus on the work that moves products forward.

Speakers: Gopal Panigrahy and Sumit Dutta

Gopal Panigrahy is a product leader and member of our product management team in Microsoft Digital. He’s an advocate for our customer-first approach to product development and is passionate about helping people overcome challenges in the era of AI.

Sumit Dutta is a product-minded technology leader working at the intersection of AI, enterprise platforms, and scalable product design. Offering a strong blend of engineering knowledge and product strategy, he focuses on building systems that are not just functional but also extensible and reliable.

More on AI and IT engineering at Microsoft

• Learn how we’re reclaiming engineering time with AI in Azure DevOps at Microsoft.
• Read about powering the new age of AI-led engineering in IT at Microsoft.
• Discover how we’re streamlining engineering at Microsoft with Azure DevOps.

How Microsoft does IT: Microsoft 365 governance in the age of Copilot and agents

Session Description: Microsoft 365 Copilot and Copilot agents are powerful tools, but without proper governance, you could be putting your company at risk. In this lightning talk, you’ll learn how Microsoft Digital protects our enterprise while enabling employee innovation with Copilot and agents.

Speaker: David Johnson

Johnson brings hands-on experience operating Copilot and AI-powered agents inside Microsoft, with a focus on identity, permissions, data boundaries, and real-world misuse prevention. He takes real-world lessons and makes them practical for others.

More on governance at Microsoft

• Learn about how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.
• Check out our guide to deploying Microsoft 365 Copilot in five chapters.
• Read how we’re powering data governance with Purview Unified Catalog.

Accelerating AI adoption with Copilot controls: Lessons from Microsoft Digital

Session description: Microsoft 365 Copilot and AI agents unlock productivity gains, but without careful oversight they can also introduce security and compliance risks. The session covers how the Copilot Control System helps scale AI safely, including adoption insights and satisfaction signals. You’ll also see demos of popular agents, including the Employee Self-Service Agent and the Admin agent.

Speakers: Amy Ceurvorst and Reshma Kapoor

Amy Ceurvorst is a director of business programs In Microsoft Digital. She’s worked extensively with Copilot controls and evangelizes a unified way to view Copilot health reports that help administrators understand Copilot health.  

Reshma Kapoor is a senior product manager in Microsoft Digital with 20 years of experience leading and shipping products at scale. She is customer‑obsessed, grounding product decisions in real customer signals to deliver intuitive, high‑impact experiences.

More on AI and Copilot adoption and deployment

• Read how we’re shaping AI management at Microsoft with Agent 365 and Copilot controls.
• Explore our five-chapter guide to deploying Microsoft 365 Copilot internally.
• Learn how we deployed Microsoft 365 Copilot in Viva Engage at Microsoft.

How Microsoft does IT: Driving adoption of Microsoft 365 Copilot and agents across Microsoft

Speakers: Cadie Kneip and Stephan Kerametlian

Session description: Our team at Microsoft Digital led the first enterprise-scale deployment of Microsoft 365 Copilot, launching to more than 300,000 employees and vendors worldwide. Learn how the team drove adoption using change management strategies to encourage employees to thread Copilot into their daily work. Now we’re doing the same for agents across the enterprise. Learn best practices for accelerating adoption and maximizing value while guiding your own journey with Copilot and AI agents.

Cadie Kneip is a senior business program director and the Copilot Champs community lead in Microsoft Digital. She specializes in turning complex AI initiatives into confidence-building pathways that help employees thrive in an AI-powered workplace. 

Stephan Kerametlian is a senior director in Microsoft Digital, where he leads our global change management efforts for Copilot and agents. He thrives on learning how people use AI and on finding ways to get more people to embrace the technology.

More on adoption and deployment of Copilot and agents

• Explore our guide on how we deployed Microsoft 365 Copilot internally.
• Find out how we’re skilling up for the future of work at Microsoft with Agent Launchpad.

Real-world adoption stories: A fireside chat with a key customer

Session description: Pull back the curtain on the customer experience with Copilot adoption. Join this fireside chat with a Microsoft customer to hear about lessons learned and the real impact that Copilot is delivering across their organization. You’ll glean practical insights you can apply immediately at your own company. 

Speakers: Karuana Gatimu and Sam Crewdson

Karuana Gatimu is a director of Customer Advocacy – AI & Collaboration in Microsoft Digital and a solution architect driven by a passion for people, storytelling, and leadership. With 30 years of experience at the intersection of technology and human impact, she turns complex innovation into compelling narratives that help organizations adopt change and deliver business value.

Sam Crewdson, a principal product manager in Microsoft Digital, is passionate about turning user insights into product improvements. His work focuses on driving adoption of the latest SharePoint features and helping users take advantage of the power of both SharePoint and OneDrive. Working at the intersection of IT, users, feedback, and strategy, he translates real‑world business needs into collaborative experiences that scale.  

More insights on Copilot adoption

• Learn about how we’re tackling Microsoft 365 Copilot governance internally at Microsoft
• Check out our guide for deploying Microsoft 365 Copilot in five chapters.
• Read our executive-level guide covering our Copilot deployment.

Try it out

• Learn more and sign up for the 2027 Microsoft 365 Community Conference.
• Start using Microsoft 365 Copilot.
• Learn how to build your own AI-powered agents and workflows.

Related links

• Find out about the keynote presentations that happened at the 2026 Microsoft 365 Community Conference.
• See how we’re serving as Customer Zero at Microsoft in the era of AI.
• Read about Copilot Control System security and governance.
• Learn about deploying Microsoft Agent 365: How we’re extending our infrastructure to manage agents at Microsoft.
• Discover how the Employee Self-Service Agent helps employees quickly complete IT and HR tasks.

The post Unfolding our AI-in-IT story: What to expect at the 2026 Microsoft 365 Community Conference appeared first on Inside Track Blog.

Moving forward, the winners will be the companies that prioritize technological and operational excellence. Microsoft Digital, our company’s IT organization, is seizing this moment by reinventing processes for agentic workflows powered by continuous improvement (CI).

We believe that AI-powered agents, Microsoft 365 Copilot, and human ambition are the key ingredients for unlocking opportunity across every industry.

“Continuous improvement is a natural, formal extension of our culture that applies rigor, structure, and methodology to enacting a growth mindset through understanding waste and opportunities for optimization.”

David Laves, director of business programs, Microsoft Digital

By combining our AI capabilities with continuous improvement, we’re executing initiatives that increase our productivity and improve our performance. We’re forging a new path for how companies operate in the era of AI.

Welcome to the age of AI-empowered continuous improvement.

Our vision for continuous improvement, turbo-charged by AI

At Microsoft Digital, we’re embracing continuous improvement to unlock greater operational excellence and better employee experiences.

“One of the main tenets of our culture at Microsoft is a growth mindset, and that involves experimentation and curiosity,” says David Laves, director of business programs within Microsoft Digital. “Continuous improvement is a natural, formal extension of our culture that applies rigor, structure, and methodology to enacting a growth mindset through understanding waste and opportunities for optimization.”

Our capacity to drive process improvements has been crucial to our AI transformation as a company. We’ve adopted a “CI before AI” approach to ensure that we don’t end up automating inefficient processes. By engaging in activities that focus on continuous improvement, our teams can better identify which problems to address with AI and prioritize meeting customer needs.

“Continuous improvement is really about understanding your business, its needs, and where you can find value,” says Matt Hansen, a director of continuous improvement at Microsoft. “It gives us the language to scale our efforts out across everything we do.”

This process isn’t just another way to enable AI. In fact, AI is essential to enabling continuous improvement itself.

“When leaders stay actively engaged and partner through these Centers of Excellence, we can create alignment, accelerate decisions, and ensure both CI and AI help to deliver measurable business outcomes.”

Don Campbell, senior director, Microsoft Digital

Operationalizing continuous improvement and AI

Operationalizing continuous improvement and AI enablement is a leadership imperative at Microsoft, and one that doesn’t just happen organically. As an organization, we are deliberate about turning business strategy into measurable outcomes through clear sponsorship, disciplined prioritization, the right resourcing, and sustained investment in change management and employee skilling.

“The difference between strategy and real business impact is execution,” says Don Campbell, a senior director in Microsoft Digital. “That execution requires strong leadership sponsorship and clearly designed continuous improvement efforts and AI Centers of Excellence (CoEs), which translate business strategy into operational reality. When leaders stay actively engaged and partner through these CoEs, we can create alignment, accelerate decisions, and ensure both CI and AI help to deliver measurable business outcomes.”

To support leadership’s vision, we’ve put organizational resources in place to manage our continuous improvement investments, guide practices, and support teams. There’s an overarching continuous improvement CoE within Microsoft Digital, which works in close partnership with the AI CoEs, forming an integrated model which connects enterprise priorities with frontline execution.

Together, these CoEs establish shared standards, provide clarity on where to invest, and help us move faster with confidence, turning ambition into sustained business impact.

“Continuous improvement is about process, but it’s also about people.”

Becky West, lead, Continuous Improvement Center of Excellence, Microsoft Digital

Continuous improvement and people

As we build out the organizational structures that underpin our investment in continuous improvement, we’re approaching the people side of change with intention.

Currently, we’re undertaking skilling efforts and communicating with every employee about how their role fits into core continuous improvement tools, including bowler cards, Gemba walks, Kaizen events, and monthly business reviews. We’re also demonstrating how “CI + AI” is a powerful combination.

The roadmap is there, the structure is in place, and we’re already seeing progress.

“Continuous improvement is about process, but it’s also about people,” says Becky West, lead for the Continuous Improvement CoE within Microsoft Digital. “A guiding hand like the Continuous Improvement CoE is how you make sure those two components align.”

Three Microsoft Digital continuous improvement initiatives

As we negotiate the early days of the company’s continuous improvement journey, Microsoft Digital is becoming a proving ground for the larger CI framework we want to deploy across the company. Our teams are spearheading projects to bring this framework to diverse functions like asset management, incident response (with a designated responsible individual), and third-party software licensing.

Enterprise IT asset management

Microsoft Digital’s Enterprise IT Asset Management team oversees the 1.6 million devices that power the company, from servers and IoT devices to labs, networks, and 800,000 employee endpoints. Safeguarding this vast landscape is critical to enterprise cybersecurity.

Three security pillars form the foundation of our security efforts: protect, detect, and respond. All of these depend on a complete, accurate device inventory.

Unified visibility enables proactive protection through enforced security controls, improves detection by spotting anomalies and misconfigurations, and accelerates responses by reducing investigation and remediation time. Without this foundation, security teams lack the precision to execute effectively.

To reach the goal of a unified inventory, the team initiated a continuous improvement initiative to build a consolidated source of truth for Microsoft Digital IT assets. Grounded in the principle of “progress over perfection,” the team initially narrowed its focus to Microsoft Lab Services (MLS) and IoT devices, with a vision to eventually expand to networks, employee devices, conference rooms, and printers. The ultimate goal is to move toward a truly comprehensive inventory.

This foundation will not only enhance security but also deliver enterprise-wide value through consistent policy enforcement, more resilient infrastructure, and comprehensive lifecycle management. By applying continuous improvement processes to help prioritize high-impact opportunities and using AI to accelerate outcomes, the program is enhancing Microsoft’s operational excellence and security posture.

“It’s better to do step A than wait until you’re ready to do steps A, B, C, and D,” says Aniruddha Das, a principal PM in Microsoft Digital.

As the team progressed from Gemba walks to Kaizen events under the guidance of the Continuous Improvement CoE, they dug deeper into areas of waste. Then they identified potential actions, breaking them down into “value-add,” “non-value-add-but-essential,” and “non-value-add.”

“For every action item, we were always asking ourselves how we could make these things better through AI. We’re looking for ways to expedite our core outcomes with minimal human involvement.”

Ashwin Kaul, senior product manager, Microsoft Digital

This exercise helped them prioritize their activities and land on a starting point: A device security index that would provide an overview of our hardware environment’s security posture. Essentially, it would represent a list of device security statuses.

The team identified distinct improvement areas for IoT and Microsoft Lab Services (MLS) devices. For IoT devices, they needed to build the inventory from the ground up. MLS already had a fairly complete inventory of devices, so the team set a goal to improve data quality. Although each of these challenges is different, they’re excellent opportunities for AI-empowered continuous improvement.

Now that the project is underway, the team plans to use an AI agent to automate device registration for IoT devices, which currently relies on manually uploaded spreadsheets. It’s a prime example how streamlining a process with continuous improvement enables AI to automate and accelerate our work.

On the MLS side, the team is creating an AI-driven normalization tool to automate the de-duplication and correction of inaccuracies in device data. The goal is to get from less than 50% data quality to 100%, dramatically improving our security posture through greater accuracy.

“For every action item, we’re always asking ourselves how we can make these things better through AI,” says Ashwin Kaul, a senior product manager within Microsoft Digital. “We’re looking for ways to expedite our core outcomes with minimal human involvement.”

Continuously improving the designated responsible individual experience

On the Digital Workspace team, designated responsible individuals (DRIs) are in charge of maintaining the health of our production systems. When technical emergencies arise, they’re the rapid-response point people who take the lead.

“We asked ourselves, ‘How can AI elevate the designated responsible individual (DRI) experience to the next level?’”

Ajeya Kumar, principal software engineer, Microsoft Digital

That process itself can be incredibly stressful, and time is of the essence. When every moment counts, efficiency is key. Meanwhile, a big part of a DRI’s work is just finding out what’s gone wrong so they can fix the incident.

But their job isn’t just about crisis management. When there are no active incidents, they work on engineering enhancements to improve the efficiency of production systems and clear backlog projects.

There’s also a handover process that takes place when one DRI finishes their rotation and another goes on-call. That involves a report about any incidents that have occurred, active issues, actions taken, key metrics, and other important information.

With these two priorities in mind, our Digital Workspace team initiated a continuous improvement process review. Their Gemba walk provided a crucial starting point.

“The planning stage is all about figuring out what the process is, what it should be, and what we can do to improve it,” says Ajeya Kumar, a principal software engineer on the Digital Workspace team within Microsoft Digital. “We asked ourselves, ‘How can AI elevate the designated responsible individual (DRI) experience to the next level?’”

Collectively, the team decided to tackle these challenges with a multifunctional AI agent they call the Smart DRI Agent. This agent’s primary role would be synthesizing and presenting information to its human counterparts to help them save time in context-heavy situations.

The AI elements that the team has planned can be broken out into the following capabilities:

• Text summarization: Going through logs and identifying key insights.
• Data correlation: Tracking and collating error logs.
• Automation: Updating the status of issues, keeping abreast of communications, and providing point-in-time, daily, and weekly summaries of system health.
• Identifying patterns: Building troubleshooting guides based on frequency patterns.

The Smart DRI Agent is already in its pilot phase and producing results. It conducts four main activities:

• AI-generated summaries of DRI actions.
• Proactive notifications with AI-generated insights.
• Chat support to assist with all kinds of DRI queries.
• AI-generated handover reports.

“The continuous improvement framework that enables these pieces is the key to unlocking value,” says Aizaz Mohammad, principal software engineering manager on the Digital Workspace team. “It may seem process-heavy, but once you work through it, you’ll see the value.”

That value is apparent in their results.

In the first 30 days of the Smart DRI Agent’s pilot, there were 301 incidents, and the agent provided insights on 101 of them. That led to an approximate 100 hours of time savings for DRIs and a 40% improvement in our key network performance metric.

Third-party software license audits

Within Microsoft Digital, the Tenant Integration and Management team is responsible for a range of services, including third-party software licensing. This space is all about managing liability from both a security operations and an auditing perspective.

“It takes a tremendous amount of data and traversals through multiple sources to get us to the actionable data we need. The goal for this project is to reduce that time to increase operational efficiencies.”

Anahit Hovhannisyan, principal group product manager, Microsoft Digital

Without the proper security insights, the company could find itself with risks associated with third-party software vulnerabilities. And without thorough auditing, we might experience license overuse and contractual issues that can lead to waste or expensive license reconciliations.

“It takes a tremendous amount of data and traversals through multiple sources to get us to the actionable data we need,” says Anahit Hovhannisyan, a principal group product manager within Microsoft Digital. “The goal for this project is to reduce that time to increase operational efficiencies.”

“It’s tough to be honest about what isn’t working, because it ties into people’s personal value and worth, but it’s essential to the process.”

Kathren Korsky, team lead, Software Licensing, Microsoft Digital

The team decided to target the auditing process first. Currently, the software licensing team performs audits manually by looking at entitlements, contracts, purchase orders, and more while liaising with suppliers and our Compliance and Legal teams. That’s incredibly time-consuming.

During the software licensing team’s planning phase, they developed an ambitious goal of reducing the time to insights on third-party software license data from 154 days down to 15 minutes. During their continuous improvement Kaizen event, the team uncovered opportunities for AI-powered process improvements that eliminate waste.

“It required a lot of courage as we were identifying waste,” says Kathren Korsky, Software Licensing team lead within Microsoft Digital. “People are very invested. It’s tough to be honest about what isn’t working, because it ties into people’s personal value and worth, but it’s essential to the process.”

Now, they’re building and implementing solutions, including an AI and data platform that provides business intelligence with custom reporting abilities, an AI agent that provides audit support and ticket creation, and another that automatically generates audit reports. The team has been using Azure Foundry and Azure AI services to create their agents because these tools have the flexibility to switch between different models and fine-tune their parameters.

As these agents emerge, they’ll take the most tedious and error-prone aspects of the process out of human auditors’ hands, freeing them up to focus on solving problems, not endlessly searching for them.

Realizing continuous improvement at scale

These are just a small selection of the many continuous improvement initiatives underway within Microsoft Digital and the company as a whole.

“What continuous improvement gives us is the macro vision and the micro actions we can do to accomplish our goals.”

Kirkland Barret, senior principal PM manager, Microsoft Digital

At Microsoft, most of our continuous improvement initiatives are in their initial stages. As they progress through the measurement and adjustment phases, two benefits will emerge.

First, we’ll iterate and improve the value that each individual initiative provides. Second, we’ll continue to build our discipline and cultural maturity around a growth mindset we’re operationalizing through continuous improvement.

“What continuous improvement gives us is the macro vision and the micro actions we can do to accomplish our goals,” says Kirkland Barrett, senior principal PM manager for Employee Experience in Microsoft Digital. “It’s about knowing our objectives, identifying upstream root causes, and rippling them throughout a mechanism of progress.”

Key takeaways

These tips for implementing a continuous improvement framework come from our own experiences at Microsoft Digital:

• Be inclusive: Have the right subject matter experts at the table from the start. Sponsors need to be present as well.
• Cultivate maturity and transparency: Objective analysis about how things are going requires honesty.
• Sponsorship matters: Make sure you have sponsorship at the highest levels. This is a cultural change, and leadership is the core of culture.
• No half-measures: If you’re going to identify opportunities for continuous improvement, commit to having budget and resources in place.
• Process, then technology: Focus on what you need to simplify processes first, then apply AI. This will keep you from automating waste and inefficiency into your operations.

Try it out

Create and deploy an agent.

Related links

• Discover how we’re building an AI-powered continuous improvement culture at Microsoft.
• How being Customer Zero in an AI-powered world works internally at Microsoft.
• Read about how we unleashed API-powered agents at Microsoft in this step-by-step guide.
• Learn more about how we measure the impact of Microsoft 365 Copilot and AI at Microsoft.
• Supercharge your business transformation with Microsoft Viva.

The post Accelerating transformation: How we’re reshaping Microsoft with continuous improvement and AI appeared first on Inside Track Blog.

Maybe you’re a product manager with a backlog that you can’t ever get to. Perhaps you’re a designer who can never seem to get engineering resources assigned to you. Or maybe you’re a program manager who routinely gets stuck copying data between systems by hand.

These are common challenges knowledge workers face everywhere, including here at Microsoft. A year ago, AI enthusiasts knew agents with tools could fix these problems—they just didn’t know where to start.

Some of our employees in Microsoft Digital, the company’s IT organization and Customer Zero for the company, took a grassroots approach to solving this problem. They built something called the Frontier Forge, our pro‑code “harness” that enables our less-technical employees to get work done with agents. They use it to quickly build agentic instructions and instantly share their solutions with peers, which accelerates our productivity across the company.

The Frontier Forge represents a cultural shift in how our product managers, designers, program managers and other “I’m not an engineer but I want to build stuff” employees now apply AI tools directly to their work.

What first began as a hackathon experiment has evolved into a thriving Microsoft-internal community with nearly 100 engaged contributors, an active Teams channel, and a GitHub repository filled with templates, learning modules, and ready-to-use AI agents. The impact is measurable: Forecasting, backlog grooming and communication tasks that collectively took weeks now take hours or minutes.

“I saw myself and others spending too much of our time on data wrangling and admin tasks when we wanted to be strategizing. Nobody was building what felt truly agentic. So, we did it ourselves.”

Brett Reifers, senior product manager, Microsoft Digital

Employees who never saw themselves as technical are now building sophisticated data visualizations, automating workflows, creating prototypes, and generating learning modules. These were capabilities previously reserved for specialized engineering teams.

The “Forge” is where it’s all happening now.

From a hackathon to a movement

In early 2025, Brett Reifers, a senior product manager in Microsoft Digital, spotted a problem he couldn’t ignore. His peers, smart and driven product managers, kept asking the same question: “How do I use agents for my actual work?”

Beginner tutorials about prompt engineering felt trivial. Advanced agents with tools assumed engineering expertise. The middle ground, where AI meets real jobs, didn’t exist.

“I saw myself and others spending too much of our time on data wrangling and admin tasks when we wanted to be strategizing,” Reifers says. “Nobody was building what felt truly agentic. So, we did it ourselves.”

So, Reifers partnered with colleague Humberto Arias, a senior product manager in Microsoft Digital whose work explores the intersection of AI and productivity. Arias had been independently researching agentic solutions that could click through interfaces, open applications, and complete tasks autonomously.

The insight that unlocked everything came from a deceptively simple observation:

“Everything on the internet is a form—every site, mobile app, every click,” Reifers says. “If agents could fill out my forms in Azure DevOps, they could handle any web-based task.”

They pitched the concept of Copilot fulfilling form-based processes as an entry for Microsoft’s annual hackathon to Sean MacDonald, partner director of product management in Microsoft Employee Experience. MacDonald immediately recognized its potential.

“My reaction was simply, ‘This sounds amazing,’” MacDonald says. “This solution was exactly what we needed.”

The event proved agents could automate PM workflows: managing Azure DevOps items, generating summaries, and querying data systems. After the hackathon validated the concept, Arias suggested pushing the project to GitHub for wider exposure. Reifers then used GitHub Copilot itself, recursively using the very tools they were building, to open source the first Frontier Forge repository in 15 minutes.

A pro-code environment with natural language accessibility

The Forge combines GitHub Copilot, Visual Studio Code (VS Code), and MCPs into a framework that makes professional development tools easily accessible to non-engineers.

“The Frontier Forge is a place where you can learn regardless of your skill level. You can adopt what’s out there, even if you don’t know where to start.”

Sean MacDonald, partner director of product management, Microsoft Employee Experience

The core idea: Give employees a workspace seeded with community-created templates, learning modules, and custom agents tailored to Microsoft Digital contexts. Then let them build from there.

For MacDonald, the Forge has proven to be an accessible entry point for almost anyone, regardless of experience.

“The Frontier Forge is a place where you can learn regardless of your skill level,” MacDonald says. “You can adopt what’s out there, even if you don’t know where to start.”

An architecture for context-first AI

The technical architecture of The Frontier Forge leverages three layers simultaneously:

• VS Code provides the enterprise managed workspace where everything happens.
• GitHub Copilot offers chat functionality and AI assistance, with access to multiple models including Claude, GPT, and Gemini.
• Tools like Model Context Protocols (MCPs) act as standardized connectors that let agents access tools, data, and services locally. This unlocked what Copilot could decide and do with user approval.

“With GitHub Copilot and MCPs, there are literally no boundaries. It’s hard to explain just how transformational this can be for a product manager. Whatever you ask is transformed into code with a purpose, allowing you to do something you couldn’t before.”

Humberto Arias, senior product manager, Microsoft Digital

The MCPs connect to services like Azure DevOps (for roadmap planning and backlog management), Microsoft Documentation, Figma (for design work), and dozens of other platforms that are essential to product manager workflows. New MCPs appear daily, expanding capabilities organically as the community builds them.

Employees can even ask GitHub Copilot to build custom MCPs for services lacking official integrations. When Arias needed a PowerPoint creator that didn’t exist, he asked GitHub Copilot to create one.

“With GitHub Copilot and MCPs, there are literally no boundaries,” Arias says. “It’s hard to explain just how transformational this can be for a product manager. Whatever you ask is transformed into code with a purpose, allowing you to do something you couldn’t before.”

The shift from prompt engineering towards context engineering is another reason why the Forge works. Its workspace settings, agent instructions, skills and hooks provide a harness with guardrails that help colleagues adopt and use this.

The Forge provides a curated starting point: Microsoft Digital-specific templates, governance frameworks, security guidelines grounded in Microsoft’s Responsible AI framework, and working examples employees can immediately use and modify.

Transformational impact

The productivity gains generated by The Frontier Forge are very real. Our employees report saving weeks or even months on certain projects, especially those that previously required extensive manual work or specialized technical skills.

Case in point: Laura Oxford, a senior content program manager in Microsoft Digital, had four years’ worth of Excel files and communication metrics reports. She had always intended to use the data to create marketing forecasts, but she could never find the necessary time or resources to perform the analysis.

“The key to creating the agent was going deep into the context. It was an iterative conversation, going back and forth to fine-tune the agent until I was consistently getting the output I wanted. But it truly was just a conversation—no tech skills needed.”

Laura Oxford, senior content program manager, Microsoft Digital

Through iterative, conversation-based prompting, Oxford’s agent analyzed patterns, created projections, and produced visualizations. Oxford now has a robust historical analysis that enables prediction of future campaign performance.

“The key to creating the agent was going deep into the context,” Oxford says. “It was an iterative conversation, going back and forth to fine-tune the agent until I was consistently getting the output I wanted. But it truly was just a conversation—no tech skills needed.”

Drafting clear, executive-ready communications for complex initiatives was what brought Mark Stratford, a senior product manager with the email and calendaring service team in Microsoft Digital, to the Forge.

Before the Forge, communicating status updates to leadership meant he had to manually synthesize data from CSVs, track several approval chains at once—often in messy emails—and iterate on visualizations for what seemed like days and days.

Put more succinctly, these tasks are time-consuming chores that are perfect for AI.

“The Forge’s architecture changes how you think about the problem,” Stratford says. “Instead of iterating on prompts, you declare intent and desired outcome. The Forge’s architecture handles the rest.”

Using this pattern, Stratford created:

• Over a dozen interactive dashboards for portfolio roadmaps, migration tracking, and service health monitoring.
• Approval matrix visualizations mapping multi-stakeholder sign-off dependencies.
• Data analysis pipelines transforming raw telemetry into executive-ready narratives.

“I didn’t need to fight ambiguity or handhold the model. The architecture gave the agent a stable, skills-driven foundation from the start, which dramatically accelerated development time and improved clarity.”

Mark Stratford, senior product manager, Microsoft Digital

The Forge’s clean separation between intent, constraints, tools, and data inputs eliminated the prompt-tuning loop. Stratford mapped his objectives into the agent framework once, relying on built-in structure and guardrails.

His analysis and drafting time dropped from days to minutes. Outputs like roadmaps and data visualizations went directly into decision workflows with no manual cleanup required.

“I didn’t need to fight ambiguity or handhold the model,” Stratford says. “The architecture gave the agent a stable, skills-driven foundation from the start, which dramatically accelerated development time and improved clarity.”

Building community and sharing knowledge

A simple continuously improving repository has grown into something larger: a community of nearly 100 enthusiasts. Contributors are building templates, learning modules, and specialized MCPs tailored to their job functions. Teams are sharing wins and unlocked achievements.

“At its core, The Frontier Forge is an open-source, community‑driven experience. It’s a safer environment that will help people learn and apply Microsoft’s AI at work.”

Brett Reifers, senior product manager, Microsoft Digital

The Forge succeeds because of its emphasis on community and knowledge sharing. Its GitHub repository serves as collaborative workspace where employees contribute agents, templates, and learning resources.

This sharing culture creates a compounding cycle. One employee’s outcome becomes another’s starting point. Contributors share useful agents immediately, without lengthy approvals. This grassroots approach lets innovation spread at the pace of curiosity.

“At its core, The Frontier Forge is an open-source, community‑driven experience,” Reifers says. “The Forge is a safer environment that will help people learn and apply Microsoft’s AI at work.”

Building a safe-to-fail path

For IT leaders looking to replicate something like the Forge, MacDonald’s guidance starts with reframing the challenge.

“Find the people who are super curious and who want to learn. They will be the ones who drive innovation with AI agents and other newly developed tools.”

Sean MacDonald, partner director of product management, Microsoft Employee Experience

The barrier to agent adoption for non-engineering roles isn’t access to tools. It’s all about giving them the confidence needed to build them and then put them to work. Providing a safe, hands-on environment where people can learn at their own pace, regardless of skill level, has been an essential key to success.

Another key has been to empower the people in your organization who are eager to innovate and try new things. The Forge began with two curious product managers who decided to experiment and then shared their idea with peers.

“Find the people who are super curious and who want to learn,” MacDonald says. “They will be the ones who drive innovation with AI agents and other newly developed tools.”

For IT leaders currently trying to prepare their organizations for an AI-driven future, the story shows that the answer isn’t to wait around for perfect tools or comprehensive employee training.

“The leaders that create safe spaces for non-engineers to build with AI now will compound that advantage for years,” Reifers says. “The ones that wait will spend 2027 trying to catch-up.”

Our knowledge workers don’t need to wait for help any longer, now they can forge their own path with an agent or other AI tool they build themselves.

Key takeaways

Here are some insights your leaders can use to build grassroots-led, AI-forward communities in your organization:

• Start with volunteers, not mandates. The Forge grew to 100 contributors with zero top-down requirements. Organic growth from curious employees creates sustainable adoption.
• Highlight your quick wins. Reifers’ and Arias’ live demos of MCPs, Oxford’s 90-minute forecast and Stratford’s 20-minute drafts became the recruiting pitch for the next wave of adopters. Show your people results like these, then hand them the tools.
• Lower barriers without lowering standards. Accessibility and quality aren’t mutually exclusive. Governance and security are non-negotiable. Configure it all into the harness.
• Prioritize knowledge sharing and attribution. When one person solves a problem and shares it, dozens benefit immediately. Reward provenance.
• Ship fast, improve later. The Forge repo was built in 15 minutes. Four months later, it contained 50+ templates and agents. As much of 80% what is produced in the Forge is rewritten every other week as tools evolve. Ship MVPs and evolve based on real usage.
• Reframe outcomes > tools. Shifting from “developer tool” to “Copilot workspace” helps knowledge workers see they belong.

Try it out

Start building and sharing AI agents today with GitHub Copilot.

Related links

• See how we enable Microsoft employees to build AI agents that help them complete important tasks.
• Learn more about GitHub Copilot for Azure.
• Discover how we’re transforming our employee experience with AI. 
• Take a course on building AI agents for beginners in GitHub Copilot.
• Follow our step-by-step guide to building API-powered agents. 
• Find out how continuous improvement helps us identify agentic opportunities, and how it can help your company, too. 

The post The Frontier Firm: How knowledge workers are forging their own AI tools at Microsoft appeared first on Inside Track Blog.

Generative AI has captured the world’s attention, and businesses are taking notice.

According to our annual Microsoft Work Trends report, 70% of people would delegate as much work as possible to AI to lessen their workloads.

Capitalizing on this trend will mean the difference between surging ahead or getting left behind, including here at Microsoft, where we were the first enterprise to fully deploy Microsoft 365 Copilot.

“I’m inspired by the transformative power of AI,” says Andrew Osten, general manager of Business Operations and Programs in Microsoft Digital, the company’s IT organization. “I’ve been impressed with how quickly our employees have put it to work for them.”

He would know. His team is responsible for driving usage and adoption of Copilot and any new features to more than 300,000 employees and vendors across the world.

“Customers are looking to us to share what we’ve learned as the first enterprise to deploy Copilot. Our team has a unique opportunity to help them deploy and get to value as quickly as possible.”

Andrew Osten, general manager, Microsoft Digital

Our mission in Microsoft Digital is to empower, enable, and transform the company’s digital employee experience across devices, applications, and infrastructure. We provide a blueprint for our customers to follow as Customer Zero for the company, and as such, we’ve created this guide for deploying and adopting Microsoft 365 Copilot that’s based on our experience here at Microsoft.

“Customers are looking to us to share what we’ve learned as the first enterprise to deploy Copilot,” Osten says. “Our team has a unique opportunity to help them deploy and get to value as quickly as possible.”

Are you an IT pro?

View the full version of this deployment and adoption guide here.

Chapter 1: Getting your governance right

Before you even begin your Microsoft 365 Copilot implementation, you’ll want to consider how this tool impacts your data. Copilot uses Large Language Models (LLMs) that interact with data and content across your organization and uses information your employees can access to transform user prompts into personalized, relevant, and actionable responses.

Giving your employees this level of access means proper data hygiene is a priority. At Microsoft Digital, we use sensitivity labeling to empower our employees with access while also protecting our data. Microsoft 365 Copilot was designed to respect labels, permissions, and rights management service (RMS) protections that block content extraction on relevant file labels. That ensures private or confidential information stays that way.

This chapter outlines the highly robust, best-case scenario we created for Microsoft, but we know not every organization has a fully deployed data governance strategy. If you’re in that position, don’t worry! You can use Restricted SharePoint Search to provide instant value and protection without exposing Copilot to all of your internal SharePoint sites.

Laying the groundwork with proper labeling

We’ve developed four data labeling practices that make up our foundation for appropriate policies and settings.

Responsible self-service

Enable your employees to create new workspaces like SharePoint sites, ensuring your company data is on your Microsoft 365 tenant. That enables your people to take full advantage of Copilot in ways that align with your organizational data hygiene while you keep your company’s information safe.

Top-down defaults

Label containers for data segmentation by default to ensure your information isn’t overexposed. At Microsoft, we default our container labels to “Confidential\Internal Only.” We use Microsoft Purview to manage this process.

Consistency within containers

Derive file labels from their parent containers. Consistency boosts security and reduces the administrative burden on your employees for labeling every file they create. Copilot will reflect file labels in chat responses so employees know the level of confidentiality of each portion of AI-created responses.

Employee awareness

We train our employees to understand how to handle and label sensitive data. By making your employees active participants in your data hygiene strategy, you increase accuracy and improve your security posture.

Self-service with guardrails

The data hygiene practices above form a foundation for compliance and security, but backstopping those efforts through Microsoft 365 features adds an extra layer of protection. Here’s how:

Trust, but verify
Empower self-service with sensitivity labels, but verify by checking against data loss prevention standards, then use auto-labeling and quarantining when necessary. We’ve configured Microsoft Purview Data Loss Prevention to detect and control sensitive content automatically.

Expiry and attestation
Put strong lifecycle management protocols in place that require your employees to attest containers to keep them from expiring. We don’t keep items that don’t have an accountable employee or that might not be necessary for our work.

Controlling the flow
Limit oversharing at the source by enabling company-shareable links instead of forcing employees to grant access to large groups. To enforce these behaviors, you can set default link types based on labels through Purview.

Oversharing detection
Even under the best circumstances, accidents happen. When one of our employees does overshare sensitive data, we use Microsoft Graph Data Connect extraction in conjunction with Microsoft Purview to catch and report oversharing.

International compliance: No size fits all

Europe has extra requirements in the form of EU Data Boundary regulations and works councils, organizations that provide employee co-determination on workers’ rights or regulatory issues. Our Microsoft 365 Copilot deployment meant we needed to partner closely with our Microsoft works councils to address complex data and privacy implications.

Your experience will vary depending on your industry and where you operate, but we’ve learned that it’s best to work closely with local subsidiaries to ensure you have a complete picture of a region’s regulatory situation. Local insiders are poised to liaise with works councils or other bodies through direct relationships. Start the process early so you can manage feedback cycles effectively and resolve any concerns through configurations that work for your employees.

Learning from our governance, security, and compliance practices

Bring the right people into the conversation

Don’t keep this conversation in the IT sphere alone. Bring in all the relevant security, legal, and compliance professionals.

Build a foundation for automation

Microsoft Purview Data Loss Prevention has powerful intelligent detection, but it relies on establishing good defaults.

Think about how your employees will use Copilot

Determine the primary use cases. The kinds of collaboration and access employees need will affect your labeling architecture.

Take this opportunity to train employees

If you’ve been looking for an excuse to refresh employee knowledge around data privacy, let this moment be your milestone.

Don’t overwhelm your users

Make labeling easy and intuitive and ensure it isn’t overwhelming.
Employees should have a limited set of choices to keep things simple.

Key takeaways

Use these tips to tackle governance, security, and compliance at your company. It’s based on what we learned deploying Copilot internally here at Microsoft.

• Establish a clear labeling framework that defines classification levels, maps labels to the right policies (such as access control, encryption, DLP, and storage rules), sets container defaults, and ensures employees understand how to apply labels correctly.
• Implement comprehensive data loss prevention controls by configuring Microsoft Purview DLP standards and quarantines, defining lifecycle and attestation processes, and using Microsoft Graph Data Connect to identify and remediate oversharing.
• Engage globally to meet international compliance needs by partnering with local subsidiaries and works councils, addressing regional requirements and concerns, and determining where segmented or region‑specific deployments are necessary.

Key actions

How we did it at Microsoft

• Read our guide to governing Microsoft 365 Copilot. This step-by-step resource, based on our internal experience at Microsoft, will help you adapt your existing governance standards to reflect the new realities of AI.

Further guidance for you

• Conduct the Microsoft 365 Copilot Optimization Assessment to understand your level of AI adoption and chart your course.

Chapter 2: Implementation with intention

At the time of our deployment, we were the first company to roll out Microsoft 365 Copilot and agents at scale, and our implementation team had to choose from different licensing strategies. We’ve learned from experience that it makes sense to start with pilot groups who can validate the experience and enable the rest of your organization. For us, that looked like:

Phase zero

We provided early access to our Copilot engineering team to test-drive the tool from an insider’s perspective. 

• Product engineers

Phase one

We issued a limited number of on-demand licenses in core scenarios to get validation and feedback for key use cases.

• Sales
• Marketing

Phase two

We extended licenses to teams who needed to understand and support Copilot or provide approval for use.

• Support
• HR
• Legal
• Security
• Works councils

Phase three

We deployed Copilot and started working on adoption across the entire company.

• Advancing in phases, we deployed Copilot to more than 300,000 Microsoft employees and external staff.

Scaling out your licenses

After you decide on the general shape of your rollout, you can begin building your licensing strategy. In Microsoft Digital, we started with individual licenses at the single-user level. As our implementation scaled, we tied licensing automation to Microsoft 365 groups to implement targeted licensing changes at scale. Those groups could include subsets of employees or entire organizations within Microsoft, and we keyed our automation logic to their expanding and contracting eligibility.

We highly recommend defining a phased rollout strategy and structuring your groups accordingly. That creates accountability and gives your IT admins a crucial point of contact for understanding the licensing needs of different groups within your organization.

There are three primary benefits to using groups:

Optimize licensing costs: Create groups that reflect your business needs and goals that align with your respective business sponsors. Sync your licensing status changes with your group membership changes. That way, you can assign the right licenses to the right users and adjust easily if you require frequent changes (e.g., in your early initial validation phase) and avoid paying for licenses you don’t need or use.

Refine admin costs: Group-based licensing enables your admins to assign one or more product licenses to a group. This depends on your rollout strategy and progress—your admins will be able to streamline your group setup at scale, reducing your admin overhead, which is helpful considering all the licenses you likely need to manage.

Enhance compliance and security: This ensures that only authorized users are licensed and have access to resources, enhancing your security and compliance. Your admins can use audit logs and other Microsoft Entra services to monitor and manage your group-based licensing activities.

Pre-adoption communications

Given the excitement around AI, one of the biggest challenges during our phased implementation was support requests from employees not within our initial pilot groups. Most of our support requests at this stage were essentially asking, “When do I get access?”

You can easily avoid the issue through clear and honest communication. For example, when you alert your initial implementation groups about their Copilot access, you could simultaneously deploy “Coming soon” emails to the rest of your organization. That will help you avoid any confusion while simultaneously generating excitement.

Your IT implementation team can’t work in isolation. Communication, especially with organizational leadership, is a key part of your licensing and implementation strategy.

Learning from our implementation

Design for the “who”

When you determine your initial cohorts, base your decisions on which roles have the largest coverage and will provide the most relevant feedback.

Get your groups in place

Be thoughtful about your Microsoft 365 groups and make sure everyone knows who owns them and who’s responsible.

Engage your support team from the start

This is a new technology, so your support teams will receive requests. Ensure they’re ready by giving them early access.

Manage expectations to minimize blowback

Proactively help users understand why they have licenses or don’t. Note that your rollout strategy might be subject to change.

Bring leadership on board early

Executive sponsorship isn’t just useful for adoption. Leaders will also help you identify the key use cases within their organizations.

Product feedback at every level

Encourage feedback for employees in your early implementation phases because that will guide your wider adoption efforts.

Key takeaways

Use these tips to help you with your internal implementation and admin process. They are based on our experience here at Microsoft.

• Prepare your organization for Copilot by performing the Microsoft 365 Copilot optimization assessment, defining implementation phases and audience groups, securing leadership sponsorship, and mapping your rollout plan to a clear licensing strategy.
• Onboard users and activate your environment by assembling the right security groups, building an automated licensing workflow, enabling roles for Copilot reports and dashboards, assigning and configuring licenses, and gathering early signals from pilot usage and feedback.
• Drive engagement through targeted communication by analyzing in‑app and qualitative pilot feedback, reviewing usage data, and delivering clear, ongoing communications aligned with your adoption strategy.

Key actions

How we did it at Microsoft

• Learn about the councils steering our AI projects here at Microsoft.
• Find out how we’re unlocking the value of Microsoft 365 Copilot at Microsoft.

Further guidance for you

• Use the Copilot Success Kit to accelerate your implementation with templates, onboarding guides, and technical readiness resources.

Chapter 3: Driving adoption to accelerate value

The fact that your employees are excited about trying out Copilot isn’t enough. We found that you need strategic, coordinated change management to drive usage and adoption.

To do this effectively, you will need to empower change agents in your organization. These are not part-time roles; they are dedicated resources across your company who are responsible for the change management function, including creation of a deployment and adoption plan, facilitating principled change management practices, communicating and engaging with employees, preparing employee readiness and learning opportunities, and then measuring the success of your deployment across the enterprise. At a high level, your strategy should consist of the following five steps.

Microsoft 365 Copilot change management

How we drove adoption in Microsoft Digital

At Microsoft, we broke our company-wide adoption efforts into cohorts, for example, subsidiaries or business groups. Depending on the size of your enterprise, you may benefit from this approach as well. We divided our adoption along two vectors: internal organizations like legal or sales and marketing, and regions like North America or Europe. Different cohorts have different focuses, but the strategy is similar. At Microsoft, we did this in four phases:

Get ready

Effective change management requires careful planning. Begin by identifying and then working with company-wide change management leads. Next, identify members of your target cohorts who will support the adoption, including change managers, leadership sponsors, and employee champions.

Champions will be crucial to your adoption by filling several powerful roles:

• Pinpointing key usage scenarios for Copilot based on their cohort’s culture or processes.
• Providing insights that help adoption leaders build out their rollout plans.
• Most importantly, demonstrating the value of Copilot and showing their peers how powerful this tool can be in their day-to-day work.

When champions socialize their tips and tricks, our experience at Microsoft Digital has revealed that it’s best to share specific prompts and the value they provided as a concrete entry point for users. For example, a champion could say, “I saved three hours drafting this sales script in Microsoft Word using this prompt,” then share their Copilot prompt as a place for peers to start.

Works councils also play a key role at this stage. They offer the benefit of local cultural expertise and can help you identify the challenges employees face in their jurisdiction. Even something as simple as understanding proper modes of address helps smooth the road to adoption through effective communication.

Each of these sets of stakeholders has a role to play in leading your own rollout. We recommend using Microsoft 365 Copilot adoption resources to build out your own adoption plan.

Onboard and engage

At Microsoft, we implemented this phase across each adoption cohort. Because every group will have its own champions and leadership sponsors, it’s important to treat each of them as its own organization, with its own unique adoption needs.

In advance of our general rollout, we created “jump-start” communications with links to learning opportunities:

Localized training took the form of Power Hours in different languages and time zones. These training sessions demonstrated key Copilot scenarios across Microsoft 365 apps.

Self-learn assets included user quick-start guides, demo videos, and Microsoft Viva Learning modules to accommodate different learning styles and preferences.

Pre-rollout communications fulfill two needs. First, this messaging is a great opportunity to launch your champion communities. Second, these communications build your employee population’s desire and excitement for their incoming Copilot licenses, then prepare them to hit the ground running when they get access.

After your Copilot licenses are live, your launch-day welcome comms are straightforward. Invite employees to access Copilot and to start experimenting with how it can fit into their work. There are many possible vectors for deploying these communications, but a multi-pronged effort that includes Microsoft Viva Amplify will deliver the maximum impact.

For support in building out your own communication plan, our adoption team has created a user onboarding kit for Copilot. These ready-to-send emails and community posts can help you onboard and engage your users.

Deliver impact

After everyone has access, it’s time to promote Copilot usage and ensure all employees are having the best possible experience and gaining the most value. For our cohorts, employee champions and leadership sponsors were essential levers.

It’s important to remember that Copilot isn’t just another tool. It introduces a whole new way of working within employees’ trusted apps. At Microsoft, we took great care to encourage employees to adapt a mindset to see it as part of their daily work—not just something they play with when there’s time.

Microsoft Viva Engage, or a similar employee communication platform, is a helpful forum for peer community support. In our case, it provided an organic space for champions to share their expertise and change managers to provide further recommendations and adoption content. For employees who explore best on their own, Copilot Lab provides in-the-flow learning opportunities to build their prompt skills.

Meanwhile, leadership sponsors diversified our communications strategy by deploying and amplifying messaging through executive channels like org-wide emails or Viva Engage Leadership Corner posts.

Extend and optimize

Understanding overall usage patterns and impact is crucial to optimizing usage. Our Microsoft Digital team used a combination of controlled feature rollout (CFR) technology while tracking usage through Microsoft 365 admin center and the Copilot Dashboard in Viva Insights. Together, these tools gave us the visibility and tracking we needed to establish and communicate adoption patterns.

Meanwhile, IT admins and user experience success managers can access simple in-app feedback through Microsoft 365 admin center. And to really maximize value, our Microsoft Digital employee experience teams conducted listening sessions and satisfaction surveys.

All these insights are helping us establish a virtuous cycle to drive further value and better adoption for future rollouts, extend usage to new and high-value scenarios, incorporate Copilot into business process transformation, and understand custom line-of-business opportunities.

Driving user enablement with Microsoft Viva

Our team in Microsoft Digital used Microsoft Viva to help enable our 300,000-plus global users. Microsoft Viva is an Employee Experience Platform that brings together communication and feedback, analytics, goals, and learning in one unified solution. Our team used Viva across a range of change management scenarios, including building awareness, communicating with our employees, providing access to readiness and learning resources, and measuring the impact of our deployment.

You can see a few of the specific ways we used Viva to accelerate employee adoption below.

Accelerating Microsoft 365 Copilot with Viva

Viva Connections

Sharing key news related to deployment and enablement, generating “buzz,” and tying Copilot to Microsoft culture.

Viva Amplify

Producing and efficiently distributing employee communications to build awareness and excitement.

Viva Learning

Courses and training for our employees on how to maximize value from Copilot, inclusive of building effective prompts.

Viva Engage

Actively engaging employees, providing leader updates, listening to feedback, and enabling Champs community.

Viva Insights

Using the Microsoft 365 Copilot Dashboard beta to identity actionable insights and usage trends.

Viva Pulse

Instant feedback from employees on their Copilot experience to fine-tune our landing and adoption approach.

Viva Glint

Understanding employee sentiment and gauging the overall effectiveness of our Copilot deployment effort.

Learning from our adoption of Copilot

Cascade adoption efforts through localization

Regional differences, priorities, even time zones—they can all block your centralization efforts. Your insider adoption leaders within each adoption cohort can help.

Empower your employee champions with trust

Monitor your user-led adoption communities at the start to provide support. As this community of power users becomes product experts, they’ll take over.

Empower employees as innovators

You’ll be surprised by what your employees dream up. Provide every opportunity for them to share their favorite tips and usage scenarios.

Create excitement, but set expectations

Encourage a healthy mindset around what Copilot can accomplish and where it fits. Don’t overpromise.

Gamify learning to build engagement and experience

Friendly competitions or cooperative challenges like prompt-a-thons generate excitement and invite creativity.

Understand that for many, AI is emotional

Overcome AI hesitancy by encouraging employees to tackle easy tasks with Copilot assistance. That will help minimize reluctance.

Use Microsoft Viva to accelerate time to value

Viva supports user enablement through learning, effective communication, usage tracking, and employee sentiment.

Key takeaways

Use these tips as your guide as you build out and implement your adoption plan. They are based on our own experience internally at Microsoft.

• Prepare your organization for adoption by identifying your adoption lead, building a cross-functional cohort-based team, defining personas and key usage scenarios, establishing communication preferences and success metrics, completing enablement training, and creating a localized communications and asset library.
• Engage your cohorts and activate readiness by deploying targeted onboarding communications, launching champion communities, running live and self-paced learning experiences, and elevating visibility with digital materials that help employees understand how Copilot improves their daily work.
• Drive measurable impact across cohorts by promoting usage through internal channels, reporting on KPIs at planned intervals, gathering employee sentiment through surveys and listening sessions, spotlighting success stories, applying learnings to refine adoption activities, and nurturing champions through deeper technical training.
• Extend and optimize your deployment by exploring new high‑value scenarios, identifying opportunities for business process transformation with agents, Copilot Studio, plugins, and connectors, and sourcing custom line‑of‑business use cases that advance your organization’s Copilot maturity.

Key actions

How we did it at Microsoft

• Learn how we boosted our Copilot adoption with a companywide expo.
• Explore how we created a Center of Excellence to guide our adoption and use of AI.

Further guidance for you

• Access the Copilot scenario library to understand different user needs and opportunities.
• Deepen Copilot engagement through the Microsoft Modern Collaboration Architecture (MOCA).

Chapter 4: Building a foundation for support

Empowering employees means making sure they have access to the right support channels. The fact that Copilot operates across a wide spectrum of Microsoft 365 apps adds complexity to support scenarios. As a result, it’s important to get your support teams early access along with your earliest pilot implementations.

For us in Microsoft Digital, four principles define high-quality support:

Available

Highly available and in-context support should deliver both self-help and assisted experiences wherever and however the user needs it.

Consistent

Coherent and seamless access to support across the entire journey eliminates frustration and keeps the experience consistent.

Contextual

Base your support experience on where the user is and what they’re trying to accomplish.

Personal

Anchor support in a user’s goals and preferences.

Strategizing for support

Building experience and knowledge is one thing, but coming up with your approach to support requires planning and a strong idea of your users’ ideal experience. At Microsoft Digital, we take a “shift-left” approach. That means we save our human support staff time by attempting to create excellent self-service options for our users.

Shift-left principles can apply to many different support contexts, but with Copilot, we’ve found that the most important upfront action is ensuring your employees have accessible self-service support channels and communicating their availability. Work with your adoption teams to ensure they include self-service support options in their rollout communications.

Seven things we learned prepping to support Microsoft 365 Copilot

Preliminary access

Select your initial support specialists. Include people with different Microsoft 365 app focuses, support tiers, and service audiences.

Communication hub

Establish a community space where your support team can connect and collaborate on issues. Invite non-support professionals as needed.

Knowledge base

Start a collaborative document and add learnings. This will eventually evolve into your knowledge base for internal support.

Widen access

Host information sessions with the wider support team and extend access so all relevant support professionals can ramp up.

Rehearse

Conduct role-playing and shadowing sessions so support teams can build practical knowledge and confidence.

Support go-live

Get your support resources and processes ready and push them live in advance of your Copilot deployment. Consider a dry run.

Track

Determine a tracking cadence and gather data on Copilot issues that arise so support teams can identify trending issues and tickets.

Common questions, issues, and resolutions

We’re getting questions about why particular employees don’t have licenses.

Use employee change management communication waves to solve for this issue by alerting employees when they’ll have access to licenses.

Users are coming to us with questions that would be better served by adoption and employee material, and that isn’t our role as support.

Work with your adoption team to preempt these issues with proactive communications. Update your self-help content and provide your support agents with ready access to different employee education resources.

Teams are looking for integration support. Where do I send them?

Share this list of pre-built connectors to help your users integrate various data sources to Microsoft Graph. This list shares the types of content supported.

Can employees put confidential information into Copilot?

If employees are signed into Copilot with their Entra ID, they can enter confidential information.

My organization has concerns about who owns the IP that Copilot generates. Does the Microsoft Customer Copyright Commitment apply to Copilot?

Microsoft does not own the IP generated by Copilot. Our universal terms state “Microsoft does not own customers’ output content.”

What’s the best way to verify the accuracy of the information Copilot provides?

Copilot is transparent about where it sources responses. It provides linked citations to these answers so the user can verify further.

Key takeaways

Use these tips to manage your Copilot support efforts. They are based on our experience here at Microsoft.

• Enable and align your support team by starting with a core group of support leaders, establishing shared communication spaces and a collaborative knowledge base, expanding access to the full Copilot support team, training them through information sessions and role‑playing exercises, defining escalation paths, and partnering with internal communications to finalize user‑facing support materials.
• Deliver meaningful user impact by signaling support availability across employee communities, publishing a clear and accessible user-facing knowledge base, and standing up self-service automations where appropriate to empower users and reduce friction.
• Optimize and mature your support services by reviewing ongoing support issues and product feedback, and continually refining support workflows to drive efficiency, accuracy, and a better user experience.

Key actions

How we did it at Microsoft

• Read how we’re using AI to transform our Support business at Microsoft. This article shares how our Support team in Microsoft Digital is using AI to overhaul the business from end to end.
• Learn how we deployed the Employee Self-Service Agent here at Microsoft. This blog post shares how we’re using this agent to help our employees with their support needs in the flow of where they work in Copilot.

Further guidance for you

• Follow the Microsoft IT admin guide for Copilot onboarding, enablement, and support resources to ensure a smooth rollout.
• Access the Copilot Success Kit for launch day assets, support templates, and troubleshooting guides.

Chapter 5: Extending Copilot through agents

As organizations and employees have matured with respect to AI, agentic extensibility is expanding the frontiers of this technology. By using and even creating agents that surface knowledge, take actions, and reinvent workflows, employees can personalize AI’s capabilities to fulfill more specific needs.

At Microsoft, our goal has been to provide access and enable agents at appropriate levels for our employees and the company as a whole. To make that happen, we’ve adopted a maturity model for agentic AI deployment. Early phases focus on using Copilot, grounded in enterprise data, to enhance knowledge discovery and retrieval. Later phases will enable our employees to act on that knowledge and even fully automate business workflows.

Agentic AI at Microsoft

Each of these levels of agentic capability requires different tools to create and depends on different policies to govern. Because retrieval agents don’t require special tooling, we allow employees to create them at will through Copilot Chat and simplified agent builders in Copilot Studio and SharePoint.

For more complex agents intended to meet enterprise needs across lines of business or the company as a whole, our developers use more full-featured tools like Copilot Studio or Azure AI Foundry. For these kinds of agents, we apply the same rigor, reviews, and software development lifecycle (SDL) we use as part of our standard internal app development.

As you explore the different kinds of agents available to your users and decide how and where to enable them, adoption.microsoft.com provides an excellent place to start. It provides three different approaches to creating agents: Microsoft 365 Copilot Chat, Azure AI Foundry, and Copilot Studio.

All of this choice adds complexity, so maintaining visibility and control over the agents your employees create can be a challenge. As a result, we take a matrixed approach to creating and governing agents based on different parameters. They include the type of agent, how the user creates it, its knowledge sources, the need for custom tooling, sharing and publishing permissions, and more.

Keeping agents safe and effective through good governance

At Microsoft, we incorporated elements of our tenant’s minimum bar for governance into our policies for managing agents. These measures include Microsoft Information Protection, a functional inventory, activity logging, lifecycle management, and the ability to properly isolate agents against crossing data boundaries.

To govern agentic capabilities, we introduced further controls like sharing limits, breadth of knowledge sources, agent metadata, and information about an agent’s behaviors. The result is a proactive approach to governance backstopped by reactive structures that catch any issues.

As you think about governing your own agents, consider the four core principles we’ve established at Microsoft Digital.

We empower employees to create and share simple, low-risk agents

 We provide a safe space and personal flexibility that allows individual employees to experiment without implicating company data or content users don’t own.

We capture and vet sensitive data flows at the enterprise level 

More complex or far-reaching agents owned by teams or lines of business need enterprise documentation to account for external audits or security and privacy validation.

We protect data designated confidential or higher 

We contain data flows to tenant mandates and only trust suitable storage destinations for content.

We honor the enterprise lifecycle 

We treat agents that individual employees own like any other user-created app and delete them when that individual leaves the organization. Agents owned by teams have a lifecycle defined by the tenant and tied to attestation, the SDL, and accountability confirmations.

Once you have your governance policies and procedures in place, you can begin your rollout to users through many of the same strategies and processes we’ve discussed in this guide.

Learning from our experience with agents

Connect with relevant stakeholders

Establish early communication and collaboration with members of your security, legal, compliance, IT, and other teams who can help you define ways to configure Copilot Studio agent builder safely.

Trust and empower

Provide safe spaces with appropriate guardrails for individual employees to experiment with simple agents. Copilot Studio agent builder is a great place to start.

Expand enterprise capabilities

Empower a small number of trusted creators to experiment with more powerful agent-building tools under the close watch of IT, Governance, Security, Privacy, Data, and HR teams. This will reveal gaps in process and policy and inform future reviews.

Solidify labeling and data

Revisit your labeling structures and data flows. It will be important to have these structures in place to support this new agentic environment. Start by learning from our experience governing Copilot at Microsoft.

Extend your review process

Adapt any review processes you already have in place to agents, including security, privacy, and accessibility. Embed those reviews into your publishing workflow for agents operating above the individual level. Consider adding reviews for Responsible AI.

Prevent agent sprawl

Establish a reasonable enterprise lifecycle for agents that includes attestation. That will keep agents from sprawling or remaining in place after employees have left your organization or simply no longer need a particular agent.

Key takeaways

Use these tips to manage your Copilot support efforts. They are based on our experience here at Microsoft.

• Plan and refine your governance approach by aligning with Security, Legal, Compliance, HR, and IT; updating existing governance and labeling policies for agents; defining your review process; building a matrix that maps agent capabilities to governance controls; and determining how your SDL procedures apply to agents.
• Pilot with targeted teams to validate your controls by selecting groups such as Security, HR, and IT; establishing clear feedback and monitoring channels; and iterating on your review and remediation procedures based on insights from early adopters.
• Enable agents responsibly across the organization by ensuring foundational protections like Purview DLP and Microsoft Information Protection are in place, deploying adoption and change‑management communications, enabling simple agent‑builder capabilities for broad users, and unlocking advanced agent development scenarios for IT and line‑of‑business developers.

Key actions

How we did it at Microsoft

• Read about how embracing the agentic future is enabling us to become an AI-first Frontier Firm. This article shares our vision for using agents to transform the workplace.
• Find out more about our deployment of Microsoft Agent 365 at Microsoft. This post shows how we’re using this new platform to manage our agent ecosystem. 

Further guidance for you

• Follow the Microsoft 365 Copilot Agents Deployment Blueprint to enable agents at scale with security, governance, and measurement strategies.
• Learn about the Responsible AI policies and practices that we use to guide our use of AI at Microsoft.

Applying our lessons to your own Copilot deployment

Embarking on your Microsoft 365 Copilot deployment and agentic extensibility journey might seem daunting, but by capitalizing on the lessons that Microsoft Digital has learned from our internal deployment, you can both speed up the process and avoid any pitfalls.

“Deploying Copilot internally has inspired us to dive deeper into the power of AI assistance, which is enabling us to enhance our employee experience.”

Stephan Kerametlian, business program management senior director, Microsoft Digital

By anchoring your work in careful planning and making use of the steps and resources provided in this guide, you can unleash a new era of productivity through Copilot.

We’ve learned a lot on our journey with Copilot, and we’re happy that we get to share our experiences with you—hopefully they help you on your journey.

“Deploying Copilot internally has inspired us to dive deeper into the power of AI assistance, which is enabling us to enhance our employee experience,” says Stephan Kerametlian, a business program management senior director in Microsoft Digital.

You’re not in this alone. If you’re looking for support or knowledge on any aspect of your deployment, reach out to our customer success team.

Key takeaways

This guide reflects our learnings and the processes we followed during our internal rollout of Microsoft 365 Copilot. This last set of tips summarizes the major actions you can take to get started with Copilot at your company. 

• Start with strong governance: Build a clear labeling and data protection strategy before deploying Copilot to safeguard sensitive information and meet compliance needs.
• Pilot, then scale: Roll out Copilot in phases, beginning with pilot groups to gather feedback and refine your approach before expanding companywide.
• Communicate early and often: Proactive communication and leadership sponsorship are essential for managing expectations and driving successful adoption.
• Empower champions: Identify and enable employee champions to share best practices, tips, and real-world scenarios that help others get value from Copilot.
• Invest in training: Provide tailored learning resources and support to help users build confidence and skills with Copilot in their daily workflows.
• Measure and optimize: Track usage, collect feedback, and continuously refine your deployment to maximize impact and uncover new opportunities.
• Plan for support: Set up self-service and human support channels early so employees can get help quickly and keep momentum going.
• Extend with agents: As your organization matures, explore agentic AI to automate workflows and unlock even greater productivity gains.

Key actions

How we did it at Microsoft

• Read our IT playbook for becoming a Frontier Firm in the era of AI.
• Review our five-step AI maturity guide for IT leaders.
• Learn how our IT organization is powering our companywide digital transformation.
• View the full, detailed version of this guide.

Further guidance for you

• Read the Microsoft Work Trend Index Annual Report.
• Find the best overall Copilot deployment and adoption guidance at adoption.microsoft.com.

Try it out

• Learn how to get ready for Microsoft 365 Copilot at your company.

The post Microsoft 365 Copilot for executives: Sharing our deployment and adoption journey at Microsoft appeared first on Inside Track Blog.

To help us and all enterprises respond to this new opportunity, the company just announced Microsoft Agent 365 at Microsoft Ignite. This product serves as the control plane for AI agents—a new evolution of the existing systems that organizations like ours use to manage people and apps.

“We’re empowering our employees and teams to build agents with guardrails. We have governance structures in place to ensure our internal agents are useful, safe, and properly scoped.”

David Johnson, principal program manager architect, Microsoft Digital

Our team—Microsoft Digital, the company’s IT organization—is now using Agent 365 to track agents that employees and teams from across the company are building and deploying. We’re also using it to access the dashboard that allow us to manage and govern agents companywide. We plan to utilize the new platform to comprehensively manage our agent workload.

Agent 365 will enable Microsoft Digital to help our employees, teams, and organizations to build and deploy agents safely and effectively, according to David Johnson, principal program manager architect for governance for the organization.

“We’re empowering our employees and teams to build agents with guardrails,” says Johnson, who notes that we have more than 100,000 agents on the Microsoft tenant today. “We have governance structures in place to ensure our internal agents are useful, safe, and properly scoped.”

Agent 365 is the control plane for AI agents and will play a key role in accelerating our journey toward becoming an AI-powered Frontier Firm. Whether your agents are created with Microsoft platforms, open-source frameworks, or third-party tools, Agent 365 helps you deploy, organize, and govern them securely.

“Agent 365 delivers unified observability across your entire agent fleet through telemetry, dashboards, and alerts,” says Charles Lamanna, president of Business Apps & Agents for Microsoft. “IT leaders can track every agent being used, built, or brought into the organization, eliminating blind spots and reducing risk.”

Here in Microsoft Digital, we’re planning to use Agent 365 for multiple purposes, including:

• Filtering our agent inventory on specific criteria, such as the type of agent or how it was built
• Enhancing governance-specific actions we can take with agents in areas like ownership and quarantining
• Gaining visibility into trends like agent usage
• Ingesting agent blueprints and defining policy templates

If you are unfamiliar with an agent blueprint, it’s a portable specification for an AI agent’s identity, capabilities, constraints, data access, and lifecycle.

Agent 365 is part of our Frontier Firm organizational blueprint, which we’re using to blend machine intelligence with human judgment to create agents that are AI-operated but human-led.

Boosting governance with Agent 365

Agent 365 maximizes the value of agents while minimizing tenant risk. These are capabilities that play well with the data governance foundation that we’ve already laid here in Microsoft Digital, in which we use data sensitivity labels and data loss prevention controls to govern the data that agents use in our environment.

We incorporated elements of our tenant’s minimum bar for governance into how we secure agents. Those include Microsoft Purview Information Protection, a functional inventory, activity logging, lifecycle management, and the ability to properly isolate agents against crossing data boundaries.

Our intention is always to act as proactively as possible while putting reactive structures in place to catch any issues that arise. After all, this is a new technology, and there are bound to be some surprises. By combining all of these elements, we’ve landed on six core principles for governing agents:

1. We built a data hygiene foundation: This enables you to trust your data estates with which employees build and use agents.
2. We empower employees to create and share simple, low-risk agents: We provide a safe space and personal flexibility that allows individual employees to experiment, without implicating company data or content that users don’t own.
3. We capture and vet sensitive data flows at the enterprise level: More complex or far-reaching agents owned by teams or lines of business need enterprise documentation to account for external audits or security and privacy validation.
4. We protect data designated confidential or higher: We contain data flows to tenant mandates and only trust suitable storage destinations for content. This depends on the ability to gate which connectors can work with which particular source data and sensitivity labels.
5. We enable internal teams and organizations with a smooth path to develop agents: This provides them with all of the services and sources they need along a path to release to the company.
6. We honor the enterprise lifecycle: Both user-based and attestation-based lifecycles come into play. We treat agents that individual users own like any other user app, and delete them when the employee leaves the organization. Agents owned by teams have a lifecycle defined by the tenant and tied to attestation, the software development lifecycle, and accountability confirmations.

“We want and need feedback from our own IT team. It will help ensure all our customers are able to move quickly to deploy the platform with speed and safety.”

Charles Lamanna, president, Business Apps & Agents

Customer Zero for Agent 365

In our role as Customer Zero for Microsoft, our team in Microsoft Digital shares our insights on Agent 365 and our suite of agentic AI products with Lamanna and the product team. This makes the products more effective for our customers.

“We want and need feedback from our own IT team,” Lamanna says. “It will help ensure all our customers are able to move quickly to deploy the platform with speed and safety.”

While it’s still early days for Agent 365, the potential for transformative impact is significant.

“I meet with many of our top enterprise customers, and some of their primary questions are around how Microsoft manages agents to prevent sprawl, allows agent enablement against company data, and governs those agents,” Johnson says. “Agent 365 gives us a powerful new tool to manage our agentic estate, ensuring that our agents are delivering the transformative impact we expect while also enabling us to manage and secure our environment more effectively. Enabling self-service agent creation at scale necessitates enterprise observability and governance.” 

We’re excited to share more about our Customer Zero journey with Agent 365 on Inside Track soon.

Key takeaways

Here are five ways you can use Agent 365 to unlock agent observability and management at your company:

• Registry: Get the complete view of all agents in your organization, including agents with agent ID, agents you register yourself, and shadow agents.
• Access control: Bring agents under management and limit their access to only the resources they need. Prevent agents from being compromised with risk-based conditional access policies.
• Visualization: Explore connections between agents, people, and data, and monitor agent behavior and performance in real time to assess their impact on your organization.
• Interoperability: Equip any agent with apps and data to simplify human-agent workflows. Connect them to Work IQ to provide context for the work to onboard them into business processes.
• Security: Protect agents from threats and vulnerabilities, and detect, investigate, and remediate attacks that target agents. Protect data that agents create and use from oversharing, leaks, and risky agent behavior.  

Try it out

Get started with Microsoft Agent 365 at your company.

Related links

• Read the official blog post announcing Microsoft Agent 365.
• Learn how we’re powering agentic AI adoption at Microsoft through our ‘Customer Zero’ story.
• Explore how we’re becoming an AI-first frontier firm in the agentic future.
• See AI-powered agents in action and discover how we’re embracing this new ‘agentic’ moment at Microsoft.
• Check out how we’re riding the wave of agents washing over Microsoft with strong governance.
• Discover how we unlocked enterprise AI extensibility at Microsoft with Microsoft Copilot Studio.
• Find out how we powered AI value with Microsoft 365 Copilot extensibility at Microsoft.
• See how our employees are extending enterprise AI with custom retrieval agents.
• Learn about our strategy and vision for deploying the Employee Self-Service Agent internally at Microsoft.
• Dive into how we’re reimagining campus support at Microsoft with the Employee Self-Service Agent.

The post Deploying Microsoft Agent 365: How we’re extending our infrastructure to manage agents at Microsoft appeared first on Inside Track Blog.

At Microsoft Digital, the company’s IT organization, we’re embracing this as Customer Zero for the company.

What does that mean?

It means that we’re testing and shaping new Windows 11 features before they ship to customers. And as such, we’re helping the company reimagine what the OS can do for enterprise users in an AI-first world. We’re also helping the company transform the tools and processes we and our customers use to manage the Windows devices that our employees use to do their work.

“Windows 11 is our foundation for the future of work. We’re helping to build an OS that’s not just reactive—it’s predictive. It understands context, adapts to users, and helps IT teams stay ahead of the curve.”

Sean MacDonald, partner director of product management, Microsoft Digital

When we rolled out Windows 11 across Microsoft in 2021, we wanted to modernize the Windows experience for our global workforce. That meant moving beyond the legacy of Windows 10 and building a platform that’s smarter, more secure, and easier to manage. It also meant working closely with engineering teams to ensure that what we deploy internally reflects what customers need externally.

“Windows 11 is our foundation for the future of work,” says Sean MacDonald, partner director of product management at Microsoft Digital. “We’re helping to build an OS that’s not just reactive—it’s predictive. It understands context, adapts to users, and helps IT teams stay ahead of the curve.”

This transformation isn’t happening in isolation. It’s part of a broader organizational commitment to AI across Microsoft. From the integration of Copilot into dozens of Microsoft products to intelligent device management, we’re aligning every layer of the stack to deliver smarter experiences.

And we’re doing it because the time is right. The end of Windows 10 support is here, and Windows 11 is the essential solution for organizations seeking the enhanced productivity, security, and personalized experiences that AI makes possible.

Embracing a secure and efficient update environment

Keeping Windows 11 secure and up-to-date has evolved into a streamlined, intelligent process.

With Windows Autopatch, we’ve automated the deployment of updates across our enterprise.

But automation doesn’t mean losing control. The management tools available across Microsoft Intune and Windows allow us to exercise complete control over updates. We can leave Autopatch to make patching decisions, or we can dictate how any part of the process works—evaluate and select which updates to perform, define the rollout structure and schedule, and monitor the updates.

“Autopatch update readiness takes us to a new level with Windows 11 updates. It allows us to be proactive, rather than reactive in ensuring our Windows devices are in a ready state to seamlessly update, which minimizes disruptions and distractions to our employees.”

Dave Rodriguez, principal product manager, Windows team, Microsoft Digital

Autopatch lets us tailor rollouts to match our business structure. We’ve created custom Autopatch groups of up to 50 rings so we can deploy updates to the right people at the right time.

This flexibility is critical. It means we can schedule around sensitive periods like year-end close, define grace periods, and even choose which updates to deploy—feature, driver, or quality.

But the real magic happens behind the scenes.

With Windows 11 and Autopatch, we’re not just reacting to issues—we’re anticipating them. That’s where the Autopatch update readiness (AUR) comes in. It adds a new layer of resilience to our update management strategy.

Update readiness continuously monitors device health and update compliance across the enterprise.

By analyzing real-time telemetry, update readiness flags irregularities early and recommends targeted fixes.

“Autopatch update readiness takes us to a new level with Windows 11 updates,” says Dave Rodriguez, a principal product manager on the Windows team in Microsoft Digital. “It allows us to be proactive, rather than reactive in ensuring our Windows devices are in a ready state to seamlessly update, which minimizes disruptions and distractions to our employees.”

“Hotpatching has been a game-changer for keeping our devices secure without disrupting work. Security updates take effect immediately—no reboot required. That’s a big deal.”

Harshitha Digumarthi, senior product manager, Windows team, Microsoft Digital

One of the biggest wins?

Hotpatch, which allows us to apply most of our monthly security updates without our employees needing to restart their devices, which has been huge for our productivity.

“Hotpatching has been a game-changer for keeping our devices secure without disrupting work,” says Harshitha Digumarthi, a senior product manager on the Windows team in Microsoft Digital. “Security updates take effect immediately—no reboot required. That’s a big deal.”

Hotpatch works by modifying in-memory code to silently apply updates in the background. It’s especially valuable for operations that require high availability.

“We’re seeing a shift from device-centric recovery to user-centric personalization. It’s not just about getting the machine back—it’s about getting the person back to work.”

Markus Gonis, senior service engineer, Microsoft Digital

Together, hotpatch, update readiness, and Autopatch are helping us transform how we manage updates. We’re not just deploying tools—we’re reshaping business critical processes.

Protecting data using Windows Backup and Restore for Organizations

With Windows 11, we’ve redefined what backup and restore means for enterprise users with Windows Backup and Restore for Organizations. It’s not just about getting a device back online—it’s about restoring the user’s experience.

When a user signs into a new device with their Entra ID, they can select a backup to automatically restore their Microsoft Store app configurations, settings, and preferences. It’s seamless. It’s secure. And it’s fast.

“We’re seeing a shift from device-centric recovery to user-centric personalization,” says Markus Gonis, a senior service engineer on the Windows team in Microsoft Digital. “It’s not just about getting the machine back—it’s about getting the person back to work.”

This matters. Especially in large organizations where device turnover is constant and downtime is costly.

With Entra ID, we can automatically enroll devices into Microsoft Intune for management. That means IT policies, security configurations, and compliance settings are applied instantly. No manual setup. No waiting.

And because the restore process is tied to the user’s identity, it works across devices. Whether it’s a laptop refresh, a lost device, or a hardware upgrade, users get their familiar environment back—apps, layout, even their desktop background.

“Windows 11 is designed for fast deployment and compatibility,” Gonis says. “We’ve seen up to 25 percent faster deployment times compared to Windows 10. That’s a huge win for IT teams.”

This isn’t just about convenience. It’s about resilience.

By combining Entra ID with modern device management, we’ve built a recovery system that’s secure by default. Data is encrypted. Access is conditional. And IT retains full control over who can restore what, when, and where.

Capturing the power of AI-enabled apps and experiences

Windows 11 is bringing intelligent experiences to the forefront, and we’re seeing it firsthand at Microsoft Digital. From productivity to security, AI is transforming how our people work.

Windows Recall is an opt-in AI-powered feature built directly into Copilot+ PCs with Windows 11. It’s designed to solve a problem every person knows too well: Finding something you’ve already seen.

Recall allows you to search across time to find the content you need. Just describe how you remember it, and Recall retrieves the moment you saw it. Once opted-in snapshots are taken periodically while content on the screen is different from the previous snapshot. The snapshots of your screen are organized into a timeline. Snapshots are locally stored and locally analyzed on your PC. Recall’s analysis allows you to search for content, including both images and text, using natural language.

Here are its core capabilities:

• Semantic AI-powered search. No need to recall exact filenames. Just describe what you remember—like “blue sustainability slide from last meeting”—and Recall uses on-device AI to surface images or text that match the description.
• Full user control and privacy. IT admins have a full set of controls to manage security and privacy when enabling the Recall feature for the enterprise. Once enabled by enterprise admins, you as the end user then have the choice to opt in to enable snapshots on your machines.
• Explore content with a visual timeline. Recall periodically captures screenshots of your active window and displays them in an interactive, chronological timeline. When you need to revisit something, you can simply scroll through your past activity or jump directly to the specific moment you remember seeing it.
•  Granular snapshot management. You choose which apps and websites to include or exclude. You can pause snapshot capture, delete past captures, and set retention limits (e.g., 30, 60, 90, or 180 days) to manage storage and privacy. And IT admins can control how these capabilities work for the entire organization.
• All snapshots, indexing, and AI processing occur on-device. Recall runs completely locally—no data leaves your PC.It never shares your data with Microsoft or third parties, nor across different user accounts on the same device.

Recall doesn’t just remember—it protects. IT admins can control snapshot storage, retention policies, and even filter which apps and websites are recorded.

That’s where enterprise-scale controls come in.

“We helped define these controls. We tested them to validate they worked as expected.”

John Philpott, principal product manager at Microsoft Digital

Microsoft Digital partnered with the Purview and Intune product teams to help build a rich set of controls that give IT full visibility and governance over Recall’s data store. That includes sensitivity labels, data loss prevention (DLP) policies, and tenant trust reviews—all designed to keep enterprise data safe.

Purview and Intune provide the level of control that IT admins need to ensure that Recall respects the security and privacy concerns of the enterprise and the end user.

If a document is labeled “Highly Confidential,” Recall won’t index it. If a meeting is tagged “Recipients Only,” it won’t be captured. Purview admins can decide exactly which sensitivity levels are allowed in Recall and which are excluded.

Recall’s content redaction feature automatically detects and removes highly confidential information from screen snapshots based on Purview sensitivity labels. Users can work with both sensitive and non-sensitive documents on the same screen without risk of accidental exposure.

“We helped define these controls,” says John Philpott, a principal product manager within Microsoft Digital. “We tested them to validate they worked as expected.”

Implementing Windows 11 for the enterprise

Windows 10 support officially ended on October 14, 2025. Still, many companies have not yet made the needed move, something that Microsoft would like them to do as soon as possible.

At Microsoft Digital, we’ve already made the leap. We’ve deployed Windows 11 across our internal fleet, and we’ve learned what works and what doesn’t.

The most important thing? Have a plan and a phased approach.

“We didn’t try to do everything at once,” Digumarthi says. “We went slow, monitored help desk calls, and paused when needed. It wasn’t about speed—it was about getting it right.”

That phased approach helped us avoid surprises. We used security groups to segment users, deployed in waves, and ran parallel communication campaigns to keep everyone informed. “We built tech web pages, sent individual emails, and used Viva Engage for direct outreach,” Gonis says. “We wanted users to know what was coming and why.”

Organizations have options. They can upgrade to Windows Pro to Windows Enterprise. They can subscribe to Windows 365, which provides access to Windows 11 in the cloud. And they can extend the life of Windows 10 devices with Extended Security Updates (ESU).

Windows 365 lets you keep older hardware while giving users a modern experience. You get ESUs at no extra cost, and you don’t have to manage license keys or deploy images.

With tools like Autopatch and Intune, deployment is faster and easier. Compatibility is strong. And support is built in.

Looking ahead

We’re just getting started.

At Microsoft Ignite, we’re unveiling new capabilities that push the boundaries of what’s possible with AI and automation. Expect deeper integration between Windows and Microsoft Defender, new agentic workflows, and expanded support for AI-driven security operations.

We’re expanding the update readiness initiative, introducing carbon-aware updates in Autopatch, and expanding privacy capabilities in Recall.

Baseline Security Mode is growing, too, with more features, better reporting, and stronger baselines coming soon.

And we’ll keep telling the story. Start with the tools. Lean on the community. And let us help you make the leap to a more intelligent and secure enterprise powered by AI and Windows 11.

Key takeaways

Here are several practical steps you can take right now to maximize your transition to Windows 11 and harness the full potential of its AI-powered capabilities:

• Understand Windows 11’s AI-driven transformation. Learn how Windows 11 leverages artificial intelligence to enhance productivity, security, and user experiences across your organization.
• Discover new enterprise features and deployment strategies. Explore the latest tools and best practices for rolling out Windows 11 efficiently, including advanced management and security capabilities tailored for businesses.
• Learn from Microsoft Digital’s role as Customer Zero. Benefit from Microsoft Digital’s firsthand insights and lessons learned as the initial adopter of Windows 11 within a large enterprise environment.
• Explore migration options. Review your choices for upgrading to Windows 11, such as moving to Windows 11 Pro or Enterprise, subscribing to Windows 365, or leveraging Extended Security Updates for legacy devices.
• Prepare for what’s next. Stay ahead by planning for upcoming features, security enhancements, and innovations that will continue to shape the future of Windows in the enterprise.

Try it out

• Learn more about moving to Windows 11 and download our onboarding kit.
• Start using Windows Autopatch.

Related links

• Check our Microsoft Ignite Windows news announcements.
• Learn more about AI improvements to Windows that we’re announcing at Microsoft Ignite.
• Learn how we’re accelerating workplace productivity at Microsoft with Windows Recall.
• Find out more on how we’re transforming security and compliance at Microsoft with Windows Hotpatch.
• Check out how we’re hardening our defense at Microsoft with Baseline Security Mode.

The post Supercharging our enterprise with Windows 11 and AI PCs appeared first on Inside Track Blog.

Recall on Copilot+ PCs can help. It uses whatever details you remember about the missing item to find it for you.

Our team in Microsoft Digital, the company’s IT organization, has deployed Recall, giving our employees access to its AI-powered memory in a secure and managed environment. Recall now integrates with Microsoft Purview, which layers enterprise-grade security and compliance controls on top of Recall’s local AI capabilities.

How Windows Recall works

Windows Recall is an AI-powered feature built directly into Copilot+ PCs with Windows 11. It’s designed to solve a problem every person knows too well: Finding something you’ve already seen.

Here are its core capabilities:

• Explore content with a visual timeline. Recall captures periodic screenshots of your active window and visualizes them in an explorable, chronological timeline. When you need to revisit something, you can scroll through your activity or jump straight to the moment you remember seeing it.
• Semantic AI-powered search. No need to recall exact filenames. Just describe what you remember—like “blue sustainability slide from last meeting”—and Recall uses on-device AI to surface images or text that match the description.
• Full user control and privacy. IT admins have a full set of controls to manage security and privacy when enabling the Recall feature for the enterprise. Once enabled by enterprise admins, you as the end user then have the choice to opt in to enable snapshots on your machines. Only your device stores them, and they’re encrypted locally via BitLocker or Device Encryption. Access requires Windows Hello biometrics (your face or fingerprint), which ensures only you can view them.
•  Granular snapshot management. You choose which apps and websites to include or exclude. You can pause snapshot capture, delete past captures, and set retention limits (e.g., 30, 60, 90, or 180 days) to manage storage and privacy. And IT admins can control how these capabilities work for the entire organization.
• All snapshots, indexing, and AI processing occur on-device. Recall runs completely locally—no data leaves your PC.It never shares your data with Microsoft or third parties, nor across different user accounts on the same device.
• Jumping back in. Windows Recall doesn’t just help you find something you saw before, it helps you pick up where you left off, getting right back to the page, slide, or chat in Word, Excel, PowerPoint, and Teams, as well as in an app, document, or webpage.

It’s like having a photographic memory for your digital life. Recall is a productivity booster. But it’s also a security-first, enterprise-ready feature.

“We’ve been working for over a year with Microsoft Digital to understand how Windows Recall will function best in the enterprise environment. They helped us get it ready for our customers.”

Adam Wayment, principal product manager, Windows product team

To ensure security, privacy, and governance, the Windows product team turned to our team in Microsoft Digital, the company’s IT organization, to test Windows Recall. This happened after early users of the feature suggested that better controls needed to be put in place. Our team helped the product group design and deploy better enterprise controls.

This collaboration helped shape Recall into a feature that works for everyone—from individual users to global enterprises.

“We’ve been working for over a year with Microsoft Digital to understand how Windows Recall will function best in the enterprise environment,” says Adam Wayment, a principal program manager lead for Windows Recall. “They helped us get it ready for our customers.”

Establishing security and privacy for the enterprise

Recall doesn’t just remember what you’ve seen. It remembers what it should—and forgets what it shouldn’t.

That’s where enterprise-scale controls come in.

Comprehensive controls are at the center of deploying Recall to the enterprise.

Microsoft Digital partnered with the Purview and Intune product teams to help build a rich set of controls that give IT full visibility and governance over Recall’s data store. That includes sensitivity labels, data loss prevention (DLP) policies, and tenant trust reviews—all designed to keep enterprise data safe.

Purview and Intune provide the level of control that IT admins need to ensure that Recall respects the security and privacy concerns of the enterprise and the end user.

“We helped define these controls. We tested them to validate they worked as expected.”

John Philpott, principal product manager at Microsoft Digital

If a document is labeled “Highly Confidential,” Recall won’t index it. If a meeting is tagged “Recipients Only,” it won’t be captured. Purview admins can decide exactly which sensitivity levels are allowed in Recall and which are excluded.

That means no screenshots of HR portals. No copies of credentials. No risk of sensitive data lingering on a user’s device.

Recall’s content redaction feature automatically detects and removes highly confidential information from screen snapshots based on Purview sensitivity labels. Users can work with both sensitive and non-sensitive documents on the same screen without risk of accidental exposure. Only permitted content is captured during multitasking or collaborative activities. That Excel document with employee salary information? It never becomes part of the snapshot.

IT admins also have policy controls to manage access to Recall. They can set retention limits. They can restrict access by role, ensuring Recall is only available to the right people. And they can block specific apps and websites from being captured.

“We helped define these controls,” says John Philpott, a principal product manager within Microsoft Digital. “We tested them to validate they worked as expected.”

“Security is at the center—data is encrypted on the device. Recall uses the latest technology for security, from all the controls on the backend right up to user authentication, including Windows Hello with face or fingerprint recognition required to access the data.”

Adam Wayment, principal product manager, Windows product team

This wasn’t just about building features. It was about building trust.

We worked to identify the key scenarios and apps—including Word, Excel, PowerPoint, Outlook, Teams, and Edge—to prioritize what needed protection. We made sure Recall could handle the real-world complexity of enterprise data.

It was a massive undertaking, requiring collaboration between Microsoft Digital, the Recall product team, and the products teams from all the apps with which Recall interacts. It came down to creating useful functionality while protecting our data.

“Security is at the center—data is encrypted on the device,” Wayment says. “Recall uses the latest technology for security, from all the controls on the backend right up to user authentication, including Windows Hello with face or fingerprint recognition required to access the data.”

These controls were built in collaboration with the product team, with our Microsoft Digital team acting as Customer Zero. We helped define tenant trust requirements and test every scenario—credentials, certificates, internal portals, and more. And now Recall is stronger because of it.

Moving forward

Our team in Microsoft Digital learned a lot helping the Windows product team build and test Recall.

Some lessons were technical. Some were strategic. All of them made the product better.

One of the first challenges we tackled was credential protection. We wanted to make sure passwords, certificates, and other sensitive data wouldn’t be captured. The product team agreed, and we helped them build the exclusion logic that ensures Recall ignores credential-related content.

Another lesson came from deployment.

Recall is disabled by default in enterprise builds. That meant we had to work through IT policy hurdles to get it up and running. We hit race conditions. We found bugs. But we fixed them. And we made the deployment smoother for everyone.

We also learned the value of centering enterprise needs early in the deployment.

When Recall first launched, we focused on consumers. But customer feedback reinforced how powerful the tool could be for information workers in enterprises like ours. We built tenant trust requirements. We ran evaluations. We created a checklist of what needed to be done. And we did it.

That process changed the conversation, and we’re not done. We’re still listening, still improving, still building.

Key takeaways

Here are four actions you can take right away as you consider deploying Windows Recall in your organization:

• Test at scale. Roll out Windows Recall to a wide group to uncover complex issues—especially those that don’t show up in smaller test environments.
• Start with enterprise needs and roles. Engage enterprise stakeholders early review which roles should have access and shape feature requirements such as tenant trust and data-handling policies.
• Collaborate for improvement. Test controls early to ensure that they are configured to provide the level of security and privacy required by your organization.
• Build confidence for adoption. Use thorough evaluations and checklists to ensure readiness, leading to greater trust among users, partners, and teams.

Try it out

Retrace your steps with Windows Recall.

Related links

• Learn more about Windows Recall.
• ‘Click to Do’ in Recall: find out how to do more with what’s on your screen.
• Ensure privacy and control over your Windows Recall experience.
• Learn how the NPU is paving the way toward a more intelligent Windows.
• Learn how we’re supercharging our enterprise with Windows 11 and AI.
• Check our Microsoft Ignite Windows news announcements.
• Learn more about AI improvements to Windows that we’re announcing at Microsoft Ignite.  
• Find out more about our Microsoft Purview-related news from Microsoft Ignite. 

The post Accelerating workplace productivity at Microsoft with Windows Recall appeared first on Inside Track Blog.