• 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.

We’d like to hear from you!

Want more information? Email us and include a link to this story and we’ll get back to you.

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

Working in Microsoft Digital, the company’s internal IT organization, means being part of a group that operates at massive scale, deploying and managing the technology solutions that enable the company to collaborate, achieve, and fully embrace its shift to a Frontier Firm.

“Being successful in today’s fast-paced environment requires more than technical expertise. Success comes from embracing change, adapting quickly, and continuously learning alongside others. The most impactful teams combine technical capability with curiosity, collaboration, and a mindset of continuous evolution.”

Miguel Uribe, principal PM manager, Microsoft Digital

Our work touches on nearly every aspect of the business, from the network our employees rely on to safely connect to corporate resources, to the productivity apps they rely on every day, to the devices that power our global enterprise. We’re also key to the internal deployment and adoption of agentic AI tools for a global workforce of over 200,000 people.

Microsoft Digital employees have the daily opportunity to tackle complex, real‑world challenges while shaping how Microsoft develops new technologies, serving as Customer Zero for the company’s use of its own products and services.

“Being successful in today’s fast-paced environment requires more than technical expertise,” says Miguel Uribe, a principal PM manager in Microsoft Digital. “Success comes from embracing change, adapting quickly, and continuously learning alongside others. The most impactful teams combine technical capability with curiosity, collaboration, and a mindset of continuous evolution.”

The path to Microsoft Digital

Managing the full breadth of IT responsibilities at an organization the size of Microsoft requires a workforce with a diverse range of perspectives and lived experiences. Accordingly, the people who work here possess a wide variety of backgrounds and skill sets, and hail from around the world.

Networking and relationship-building are often helpful in finding your way into the organization. Mykhailo Sydorchuk, a principal product manager in Microsoft Digital, started his career in Ukraine at a SharePoint solution startup with some prominent global customers. After a successful implementation with one of them, he built a strong relationship with a manager there.

When that person’s company later opened up a SharePoint role, Sydorchuk applied, was hired, and relocated to Los Angeles. He wore many hats in the job, serving as a SharePoint administrator, Microsoft 365 tenant administrator, developer, and project manager for internal IT rollouts and large-scale change management efforts.

Eventually, he was ready for a change.

“My colleague eventually joined Microsoft,” Sydorchuk says. “She felt I would be a good fit and suggested I apply. I went through the interview process and landed the role here about six years ago. So, I got the job very much through networking.”

Some employees at Microsoft Digital have an extensive work history, while others are just getting started in their careers.

“The internship structure is very supportive. Interns are given broad, open‑ended problems rather than tightly scoped tasks, which allows for deeper exploration.”

Jeni Huang, product designer, Microsoft Digital

Internships offer a great opportunity for many candidates who are new to the job market, giving them a way to get a foothold at the company. Microsoft hires thousands of interns each year globally, with year-to-year fluctuations based on hiring conditions and program scope. Within that broader program, design interns are part of a smaller, close-knit cohort, making mentorship and studio connections especially meaningful.

“The internship structure is very supportive,” says Jeni Huang, a product designer in Microsoft Digital who started with the company as an intern in 2022. “Interns are given broad, open‑ended problems rather than tightly scoped tasks, which allows for deeper exploration.”

In Huang’s early work as an intern at the company, she was encouraged to explore more forward-thinking design concepts rather than incremental improvements. That freedom helped her build strong relationships with her manager and others working in the design studio.

“Even though I’m now on a different team, many of the same people remain,” Huang says. “Those connections played a big role in my return as a full‑time Microsoft employee.”

Interesting, impactful work

The people who work at Microsoft Digital routinely tackle ambitious, forward‑thinking projects, with an eye toward reimagining how IT operates at a global scale. Our teams focus on building intelligent, AI‑powered employee experiences, using cloud-native platforms and data-driven insights to simplify work, boost productivity, reduce friction, and help everyone at the company do their best work.

“Microsoft, even after a long and storied history, remains one of the best places for employees to thrive professionally and personally. Experimenting and innovating are at our core—managers are encouraged to provide the time and space for innovation, and to celebrate both successes and learnings.”

Andrew Osten, general manager, business operations and programs, Microsoft Digital

Many of our projects involve large-scale automation, modernizing legacy systems, and embedding responsible AI into everyday workflows, including personalized self‑service technologies, adaptive productivity tools, and predictive insights for decision making. This environment creates a feeling of autonomy for employees and allows them to make significant impact.

“Microsoft, even after a long and storied history, remains one of the best places for employees to thrive professionally and personally,” says Andrew Osten, general manager for business operations and programs in Microsoft Digital. “Experimenting and innovating are at our core—managers are encouraged to provide the time and space for innovation, and to celebrate both successes and learnings.”

Microsoft Digital employees work on front-line technologies that matter. Their efforts serve as living case studies for Microsoft products, testing them in real-world conditions before they reach our customers. The result is a portfolio of work that combines innovation, pragmatism, and long-term thinking.

“We run hackathons sessions like ‘Fix, Hack, Learn,’ where we train ourselves on new technologies and then actively experiment,” Osten says. “That’s one of the most exciting parts of working here: We’re always pushed to explore the latest and greatest technologies and find real value in them.”

The pace can be fast and intense, but it offers the opportunity to work at the cutting edge and be part of transformative software releases. Innovative products result from being given the time and trust to invest and iterate.

“Open-mindedness and flexibility are critical here,” Sydorchuk says. “Technology evolves too quickly to get attached to specific ideas or scopes. Constant change is the norm, and learning to live with uncertainty is essential.”

Customer Zero: Our defining mission

A central component to working in Microsoft Digital is our role as Customer Zero. This concept describes how we use our own products and services internally before releasing them to customers, subjecting them to security, compliance, and productivity demands at an enterprise-level organization.

“Because we deploy these products internally at scale, we learn a tremendous amount, especially since many of these capabilities are early-stage or newly released.”

Andrew Osten, general manager, business operations and programs, Microsoft Digital

This approach surfaces functionality gaps, risks, and usability issues early, turning internal teams into live stress tests for new technologies before they are released to customers. Customer Zero helps ensure our products are resilient, fit for purpose, trustworthy, and grounded in real-world needs, not idealized scenarios. Just as importantly, these practices help create repeatable governance, adoption, and change strategies that customers can reuse, translating internal learning directly into external value.

“Because we deploy these products internally at scale, we learn a tremendous amount, especially since many of these capabilities are early-stage or newly released,” Osten says. “Our role is to generate energy and interest, help teams adopt the tools in ways that deliver real value, and then capture those learnings.”

Customer Zero means that Microsoft Digital functions differently from a typical IT organization, even though we’re still on point for the fundamentals, like keeping the network and its related infrastructure running safely and securely, managing the tenant, providing IT support, driving deployment and adoption, and ensuring our employees have the right tools, devices, and AI-powered services to succeed in a complex global enterprise.

What makes us unique is that we get access to ground-breaking new Microsoft products, features, and capabilities first. We provide early feedback, are the first to try out new experiences, and validate them at enterprise scale.

“We’re often operating at the edge,” Osten says. “For example, I’m currently using early-stage hardware and agentic technologies that haven’t been released yet for general availability, to both provide product feedback and drive value realization as soon as possible. Years ago, through our internal dogfooding program called Elite, I was using a next‑generation Xbox before it launched publicly. Those experiences are part of how we learn about and improve our products.”

Growing AI-based skills

A good example of something truly transformative to emerge from Microsoft Digital recently was our enterprise‑wide deployment and operationalization of Microsoft 365 Copilot—acting as Customer Zero for generative AI technology at scale.

Rather than treating Copilot as a productivity add‑on, we led a full reinvention of how knowledge work happens at the enterprise level. Building everything from governance and data-hygiene standards to role‑based adoption models and change management playbooks, we went all out to change employee habits and safely embed AI into daily workflows across the company.

“AI is behavioral,” Osten says. “To get real value, we work closely with business units to understand the problems they’re trying to solve, map those processes, identify where people can focus on higher-value work, and then build and drive adoption of agents to support that shift.”

In essence, Microsoft Digital is engaged in building an entire business model with AI serving as a governed, trusted, role-aware layer of intelligence. The company refers to this as the Frontier Firm concept, combining human judgment with AI agents—tools that can reason, plan, and execute tasks across systems.

“Building agents just because we can isn’t the goal. The goal is value. Microsoft Digital plays a key role in identifying the right problems, ensuring the right tools are available, and scaling solutions responsibly, so we’re solving problems while not creating new ones.”

Aisha Hasan, principal product manager, Microsoft Digital

The work Microsoft Digital does to conceive, build, and incorporate agents falls under a company-wide initiative known as Microsoft Agent 365. It focuses on three broad questions:

• What problems are we trying to solve?
• How can we build AI agents and workflows to solve them?
• How do we manage and scale this work without creating sprawl or duplicative solutions?

“Building agents just because we can isn’t the goal,” says Aisha Hasan, a principal product manager in Microsoft Digital. “The goal is value. Microsoft Digital plays a key role in identifying the right problems, ensuring the right tools are available, and scaling solutions responsibly, so we’re solving problems while not creating new ones.”

Prospering in Microsoft Digital

In addition to the central role they play as Customer Zero and the opportunity to engage closely with agentic AI, Microsoft Digital employees also benefit from a wide range of opportunities that go beyond technical skills. Rather than limiting our roles within narrow job definitions, we focus on a more holistic career experience that supports pursuing growth opportunities across Microsoft.

“We invest in growth, exposure, innovation, and collaboration in a way that makes the work both challenging and fulfilling,” Osten says.

Employees at Microsoft Digital use traits like curiosity, empathy, and adaptability to thrive within a fast-moving technical landscape. Being curious leads to learning, learning enables adaptation, and empathy pulls it all together, helping people grow as they collectively manage challenges.

“Technology is evolving so fast that keeping up with everything is a challenge in itself,” Hasan says. “Empathy, for yourself and others, matters when everyone is navigating constant change.”

It’s common for employees to leverage a range of responsibilities both within and between different jobs. Open-mindedness and flexibility are critical. Technology evolves too quickly to get attached to specific ideas or job scopes.

“I began in engineering and operations, moved into network engineering, and then gradually ‘peeled back the onion’ by stepping into technical program management,” Hasan says. “That allowed me to see the end-to-end picture: business value, technology, end users, adoption, and long-term maintenance.”

To be successful at Microsoft Digital, technical skills are important, but what really matters is the ability to innovate and work through uncertainty.

“I look for people who thrive in ambiguity, who enjoy taking on new challenges rather than waiting for perfect clarity,” Osten says. “Collaboration is equally important. In an environment this dynamic, you may be accountable for an outcome, but your success depends on the work of many other teams.”

How Microsoft values drive our work

No description of what it’s like to work at Microsoft Digital is complete without a discussion of the principles that fuel us, both at the department level and for the company as a whole.

“It often feels like drinking from a firehose, in terms of the volume of information one needs to process. It’s high-intensity, but being able to work at the cutting edge and be a part of major technological transformation that empowers everyone on the planet to achieve more makes it totally worth it.”

Mykhailo Sydorchuk, principal product manager, Microsoft Digital

Here are four core Microsoft Digital value pillars, as Osten describes them:

1. People development and skilling. This includes technical skills—including around emerging technologies like agentic AI—as well as people skills. We focus on stakeholder management, storytelling, and career development skills that support long‑term employee growth.
2. Leadership and manager development. We continually build leadership capability through a growth mindset, reinforcing principles like creating clarity, generating positive energy, and driving success. We invest heavily in helping both current and future leaders build “model‑coach‑care” skills.

3. Connection and collaboration. We intentionally create opportunities for teams to understand one another’s dependencies, whether through global meetings or structured collaboration initiatives. It’s easy to become siloed in a large enterprise, and these connections are critical, especially as AI continues to blur traditional boundaries.
4. Inclusion. This means being inclusive across communities, geographies, languages, cultures, and work environments. We focus on how we meet, how remote participation works, and how to ensure everyone can contribute effectively, regardless of location or role.

Following our pillars, and being benchmark examples of Microsoft’s value model, contributes to the success of Microsoft Digital and enables our employees to thrive  working at one of the world’s most prominent tech companies.

“Microsoft is a fast-paced environment, primarily due to scale and constant innovation,” Sydorchuk says. “It often feels like drinking from a firehose, in terms of the volume of information one needs to process. It’s high-intensity, but being able to work at the cutting edge and be a part of major technological transformation that empowers everyone on the planet to achieve more makes it totally worth it.”

Key takeaways

Here are five keys to employee success at Microsoft Digital, which can be applied to any IT organization:

• To get a foot in the door, be resourceful. Microsoft Digital employees find their way into the company through a variety of channels, including personal networking, internships, vendor relationships, and Microsoft external and internal career sites.
• Embracing Customer Zero is crucial. The concept of using Microsoft employees as early adopters of new products and services is a strategic cornerstone and an essential aspect of how the company operates.
• Understand what it means to be a Frontier Firm. Orienting your approach to work in a way that corresponds with the benefits of agentic AI can help you align with Microsoft Digital’s journey, as we become a lighthouse example of a Frontier Firm for other IT organizations.
• Develop your curiosity, empathy, and versatility. Technical skills are valuable, but continuous learning and softer skills are foundational to professional and personal growth and success.
• Know your organization’s core values. Collaboration, connection, and inclusion are vital tenets for succeeding at Microsoft Digital, as reflected in the organization’s values.

Try it out

Empower your future with an IT career at Microsoft.

Related links

• Learn more about our company’s mission, values, and products.
• Check out the main Microsoft Careers page.
• Read about Olutunde Makinde’s journey to Microsoft.
• Learn about Anahit Hovhannisyan’s impact on IT at Microsoft.
• See how Microsoft Digital is transforming IT at the company.
• Discover how Microsoft Digital leverages Customer Zero to drive AI innovation.
• Understand more about how agentic AI is core to becoming a Frontier Firm with this deployment readiness guide.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post IT on the cutting edge: Working in Microsoft Digital in the era of AI appeared first on Inside Track Blog.

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For more than two decades, SharePoint has been a foundational part of how work happens at Microsoft. This pivotal application supports everything we do, including companywide communications, day‑to‑day collaboration, and empowering our employees to create, share, and manage information.

In 2026, we’re celebrating 25 years of SharePoint at Microsoft. Microsoft Digital, the company’s IT organization, is commemorating this anniversary by reflecting on the journey we’ve taken with the product over the last quarter-century.

In this article, we’ll share our journey as SharePoint’s Customer Zero and step through the lessons we’ve learned building and maintaining an IT stack in the age of agentic AI.

Why SharePoint?

In the early 2000s, we faced a technical challenge familiar to just about any organization: We had important documents and data scattered across siloed file shares, institutional knowledge hidden away in email attachments, and access challenges preventing different teams from collaborating across geographical borders and departmental boundaries.

SharePoint offered the solution to these challenges.

Its flexible, web-based platform gave us the ability to collaborate using shared sites, centralized document libraries, and widely accessible workspaces. The application also fundamentally reshaped our corporate communications and publishing capabilities, providing features that would power key internal portals like Microsoft Web (our longtime internal company homepage, often called MSW), HRWeb, and MS Library.

“At the time, because there were so few customers running SharePoint at scale, the product was in many ways directly built to meet our IT needs.”

Sam Crewdson, principal program manager, Microsoft Digital

The evolution of how we used SharePoint in Microsoft Digital can best be described in three phases:

1. Our on-premises expansion and optimization
2. Our migration to the cloud, self-service growth, and modernization
3. Our incorporation of agentic AI

On-premises expansion and growing pains

When we first adopted on-premises SharePoint at scale, it became indispensable almost immediately. Internal teams used SharePoint to replace their existing file shares, publish information internally, and create many custom workflows and applications tailored to their needs.

Our team at Microsoft Digital was responsible for deploying SharePoint on an enterprise scale. Because we were one of the first enterprise customers to fully use SharePoint’s capabilities, we worked closely with the SharePoint product team from the beginning of its existence as a company. This meant we played a sizable role in influencing what SharePoint ultimately became.

“At the time, because there were so few customers running SharePoint at scale, the product was in many ways directly built to meet our IT needs,” says Sam Crewdson, a principal program manager in Microsoft Digital. “A result of our being their first and best customer at the time was that the SharePoint team often built capabilities for us that no one else was asking for yet, such as specific portals features and supportability needs.”

Our initial adoption of SharePoint exposed some structural limitations and gaps. To meet the goals of our internal customers, we often relied on custom code, which made upgrades more difficult. And data governance and lifecycle management could be challenging, with our internal teams creating thousands of sites with little or no ownership tracking.

Using SharePoint in this way meant rapidly accumulating abandoned sites and outdated content. Trying to conduct even routine maintenance became difficult because there was no reliable way to contact site owners.

“Because of the initial difficulties, SharePoint was frustrating at first, especially for admins. But then I realized how important it was for our users—the product saved them so much time, and they were so happy that it was available. It was a complete 180-degree shift in my mindset towards SharePoint.”

Thomas Snyder, principal service engineer, Microsoft Digital

These challenges meant tensions often ran high for the IT team during the initial adoption phase. Tempers sometimes flared as we navigated this period in SharePoint’s evolution at Microsoft.

However, the time and effort we put into overcoming these growing pains—time and effort our customers didn’t have to invest themselves—made the frustrations well worth it.

“Because of the initial difficulties, SharePoint was frustrating at first, especially for admins,” says Thomas Snyder, a principal service engineer in Microsoft Digital. “But then I realized how important it was for our users—the product saved them so much time, and they were so happy that it was available. It was a complete 180-degree shift in my mindset towards SharePoint.”

Scalable self-service, effective governance, and the cloud

SharePoint’s role at Microsoft quickly expanded from a collaboration platform into a more powerful application where our teams could build workflows, forms, dashboards, and other solutions.

Thanks to a decision to enable SharePoint’s self-service site creation capabilities, our internal customers were able to use it to build the sites they needed without having to wait for us in IT. By removing the friction of having to work with IT, they innovated faster and built new capabilities on their own using SharePoint’s out-of-the-box technology.

However, this self-service power we gave to our users also drove some sprawl that we were not initially ready to manage. By the late 2000s, the information explosion that SharePoint sparked at the company was increasing our operational and governance burden. The rapid growth in sites delayed upgrades and introduced security and compliance issues stemming from a lack of clear ownership when site owners changed jobs or left the company.

As a result of this growth, we made the decision to invest heavily in building up our governance and lifecycle management for SharePoint. We prioritized defining clear ownership for all SharePoint sites, establishing best practices around data cleanup, and building the guardrails necessary to make widespread adoption and use more manageable.

Moving SharePoint to the cloud

Our cloud migration started in late 2010 and quickly became the driving force for us in IT. Rather than see the migration as a simple lift-and-shift activity, we took the opportunity to strategically reconfigure the architecture and customization level of our SharePoint instance.

This was a huge undertaking.

We had to think globally across all our sites in different regions and countries. The tooling suite for migration was immature at the time, meaning some of our portals and sites would require refactoring. We also had to contend with the constraints of varied and sometimes conflicting regional data residency requirements.

“It’s effectively filtering, so you don’t migrate everything. You’re cleaning your house before you move. You don’t move everything in your garage—you clean it out first. The easiest move is the one you don’t have to do.”

David Johnson, principal product manager architect, Microsoft Digital

Our approach to moving SharePoint to the cloud took several phases

First, early adopters who expressed active interest in migrating were provisioned the first sites in the cloud. By harnessing their enthusiasm for cloud services, we allowed them to self-migrate their own site content

Second, we did extensive analysis of all sites to establish actively used sites. Sites where we had no recent usage were backed up, stored offline, and deleted. If nobody screamed, we didn’t move them to the cloud.

Third, we moved the zero- and low-customization sites. These were sites using out-of-box features that had the highest likelihood of a successful migration

Finally, all we had left were the highly customized sites, which often used customization approaches which were not supported in the cloud. These we chose to manually rebuild and often to refactor as part of our migration approach.

While we were making these first-in-the-world migrations, we spent a lot of time with our SharePoint product team partners to learn how best to move sites and to document the approaches for the millions of sites that would follow. Sites which had high levels of customization or features that the cloud couldn’t support were instead rebuilt in the cloud environment from the ground up.

We treated our SharePoint cloud migration as an opportunity to take stock of what we had and decide what we didn’t want to bring with us into the new age of SharePoint at Microsoft. We cleaned our data and retired unused sites based on which content and functions employees told us they regularly used and relied on.

“It’s effectively filtering, so you don’t migrate everything. You’re cleaning your house before you move,” says David Johnson, a principal product manager architect in Microsoft Digital. “You don’t move everything in your garage—you clean it out first. The easiest move is the one you don’t have to do.”

Cloud migration also presented fresh governance challenges for our team. Governance practices had to be established for this new environment that would allow for effective self-service across multiple sites.

Building governance around lifecycle management, attestation, ownership policies, and guarding against oversharing required a significant amount of effort from the team, but it was necessary to ensure a smooth transition from an on-premises tool to the cloud.

Site modernization: Reducing the need for customization

Around 2016, SharePoint rolled out what came to be known as SharePoint Modern. This new version was a game changer for our major portals, as it reduced the need for heavy, developer-driven customization and replaced it with powerful out-of-the-box page creation capabilities, responsive design, and improved accessibility. The product also eventually added seamless built-in integration with solutions like Microsoft Teams and OneDrive.

Less custom code meant we could upgrade faster and dramatically lower our development, support, and maintenance costs. But the best part was the improved user experience and better navigability of the new version. Before this, our IT team fielded numerous questions about SharePoint on a weekly basis. The more intuitive, user-friendly experience of modern SharePoint reduced the volume of inquiries and service requests drastically. Our internal users were happier, and so were we.

SharePoint in the age of agentic AI

We see SharePoint as a key “knowledge platform” for AI. It’s a critical enterprise-scale repository for our documents and data and other information that we use to power our global enterprise.

“Security through obscurity is dead. It’s the double-edged sword of semantic search.”

Thomas Snyder, principal service engineer, Microsoft Digital

As such, it’s one of our key “knowledge platforms,” locations where we store the information that is the lifeblood of our enterprise. And as our enterprise-scale repository for documents, data, and other information used to run our global multinational, it has become the launching point for many of our AI-powered experiences.

AI is only as effective as the quality of the data it can access, which is why we’ve prioritized governance best practices as we make this transition. With these new tools, we’ve had to overcome new challenges.  For example, in the early days of AI, the discovery of previously well-buried personal data is becoming a common occurrence.

“Security through obscurity is dead,” Snyder says. “It’s the double-edged sword of semantic search.”

Prioritizing good governance helps ensure agentic AI only has access to the data it’s permitted to use, avoiding accidental oversharing and related hallucinations.

As an AI-driven Frontier Firm, we’re empowering our non-technical users and engineering and development teams alike to begin building custom AI agents to drive innovation at Microsoft. Our teams can now use agents in SharePoint for tasks like creating applications, knowledge depositories, and sites, saving huge amounts of time and effort.

Many of these agents will eventually be available in Azure DevOps and GitHub, so we’re focused on helping SharePoint site owners put the appropriate data ownership and permissions in place to effectively manage and govern the data for use by agentic AI.

After 25 years, SharePoint remains a core part of IT operations across Microsoft. We look forward to growing alongside it as it continues to evolve and improve.

Key takeaways

These insights can help you mature and transform how you use SharePoint at your company:

• Self-service and good governance go together. Without solid guardrails for your SharePoint instance, your organization could contend with information sprawl and internal friction between departments.
• Cloud migration is a golden opportunity. Before you migrate from on-premises IT to the cloud, take the time to clean your data to avoid carrying technical debt and outdated information into the future.
• Out-of-the-box capabilities are your friend. Customization is useful, but too much of it can be unwieldy and expensive to maintain.
• Make data hygiene a priority. Poorly governed data can undermine users’ trust in AI, expose sensitive information, and delay widespread adoption.

Try it out

Explore how Microsoft SharePoint can help your team collaborate more effectively and be ready for the agentic AI future.

Related links

• Read how we keep our content fresh, findable, and governed with AI-powered SharePoint at Microsoft.
• Learn about how we’re handling Microsoft 365 Copilot governance issues internally in this guide.
• Discover ways to use SharePoint agents to surface knowledge and improve how employees find answers.
• Explore how we’re supercharging SharePoint sites with Microsoft 365 Copilot.

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At Microsoft, we’ve put that potential into action by building the Employee Self-Service Agent, a centralized “front door” for employee support inquiries on all things Microsoft. Whether the question is related to an IT, human resources (HR), or campus services-related challenge, this agentic solution delivers geographically relevant, role-specific content on demand.

Our agent was rolled out in stages to our global workforce, as we continually added topic categories, features, and geographic availability. It eventually reached our entire workforce—more than 300,000 employees and vendors in 103 countries and regions—before being publicly released last November.

Our team in Microsoft Digital—the company’s IT organization—played a pivotal role in our global rollout, working closely with the product team and providing valuable feedback throughout development. It’s all part of our Customer Zero philosophy here at the company.

The agent proved its value early, piloting in large, primarily English-speaking regions—including Canada, India, the UK, and the US—and reaching more than half of our global workforce. But we wanted to raise the bar, so we turned to the rest of Europe.

The next chapter in the rollout was the Europe North region, which brought in 21 countries that are home to a wide variety of languages, cultures, country-specific HR policies, and nuanced IT support requirements.

“For the Employee Self‑Service Agent to work in Europe North, we had to listen locally to understand each country’s realities and respect those differences, rather than forcing a single global approach.”

Allan Hvass, director, Employee Experience in Europe North, Microsoft Digital

However, early deployments in smaller markets in the region revealed that when local content for a specific geography was missing, the agent sometimes defaulted to policies related to the US or other unrelated countries. Sensitive HR scenarios and strict country-level rules increased the complexity and resulting challenges.

Our team in Microsoft Digital met the challenge by working through front‑end field adoption and back‑end product updates to successfully land the Employee Self-Service Agent in Europe North’s small and midsize countries. This included adapting the product to distinct local realities in each country.

“For the Employee Self‑Service Agent to work in Europe North, we had to listen locally to understand each country’s realities and respect those differences, rather than forcing a single global approach,” says Allan Hvass, director for Employee Experience in the Europe North region of Microsoft Digital.

Mobilizing field representatives

To help with the tricky aspects of driving local adoption of  the Employee Self-Service Agent, our team in Microsoft Digital formed an adoption advisory team. The team included leadership representatives from all major countries and business divisions.

The group established on‑the‑ground field representatives to create better communications channels with the Europe North countries. This helped us learn what was and wasn’t working locally while we extended support for neighboring countries and kept excitement around the agent alive.

“I encouraged my colleagues to use the agent, and then to tell customers about their experience,” Rusen says. “A story grounded in real use is much more powerful and authentic than any slide deck.”

Daniel Rusen, sales enablement and operations leader, Europe North

Because the team had already been communicating about the agent internally, including hosting all-hands meetings to spark early usage, we were able to collect thousands of instances of employee feedback. Key themes surfaced, including policy accuracy by country, quality of language, and IT support variance by market.

Daniel Rusen, a sales enablement and operations leader for Europe North, served as one of the field representatives. He helped the advisory team close the loop between the field and the core project by highlighting the language and local relevancy issues that were reported. He also became an evangelist for the agent, encouraging other sales executives to use the tool and experience it first-hand.

“I encouraged my colleagues to use the agent, and then to tell customers about their experience,” Rusen says. “A story grounded in real use is much more powerful and authentic than any slide deck.”

Driving adoption with contextual experiences

To support the rollout of the Employee Self-Service Agent across Europe North, we designed an adoption approach aligned with regional priorities and local ways of working.

We focused on making the value of the agent immediately tangible. Through Microsoft Viva Engage communications, we connected the agent directly to Europe North business goals and highlighted the most relevant, high-impact scenarios—helping employees quickly recognize when the agent was the right “front door” for their support needs.

“Adoption is not about pushing a tool, it’s about helping people recognize, in their own context, when it truly makes their day easier. By focusing on relevant scenarios, simple communication, and hands-on experiences, we made the Employee Self-Service Agent useful from the start.”

Edith Dubuisson, senior business program manager, Employee Experience in Europe North, Microsoft Digital

To avoid overwhelming users, we prioritized simple, focused communication formats. For example, an Advent calendar campaign combined the agent with Copilot capabilities, enabling employees to discover one practical, actionable use case at a time.

In parallel, we hosted targeted readiness sessions to demonstrate key end-to-end scenarios and share practical tips and best practices. This ensured employees not only understood the value of the agent, but also felt confident using it from day one—creating a strong and positive first experience.

“Adoption is not about pushing a tool, it’s about helping people recognize, in their own context, when it truly makes their day easier,” says Edith Dubuisson, a senior business program manager in Microsoft Digital. “By focusing on relevant scenarios, simple communication, and hands-on experiences, we made the Employee Self-Service Agent useful from the start.”

Fine-tuning the agent

Built in Copilot Studio, the Employee Self-Service Agent works on global, regional, and area levels to make sure that users receive the content that corresponds to their geographical location and preferred language.

The Microsoft Global Support Services group manages the agent capability and improvements, driven by a strong partnership with internal engineering teams. The team triaged feedback and partnered with the product group to tag accurate policies and knowledge by country, and to tune agent behavior and guardrails for localized content. They prioritized quick fixes and high-impact content gaps.

Updating the Employee Self-Service Agent to fix content mismatches in Europe North wasn’t about tweaking the AI in isolation. Instead, we needed to overhaul the content that the agent relies on.

“Instead of treating mismatches as failures alone, we used them as signals to improve the underlying content—revising articles, correcting categorization, and closing gaps in coverage. Over time, this combination of tightly scoped data sources, country-level tagging, and ongoing content curation turned the agent into a far more reliable assistant.”

David Finney, director, IT Service Management, Microsoft Digital

The team “grounded” the agent in a set of trusted, IT-approved sources: About 250,000 vetted knowledge base articles and 15-20 different internal SharePoint sites containing policies, guidelines, how-to articles, and related information.

Then they tackled regional nuances, one of the biggest drivers of content mismatches (when a user gets a reply based on content that doesn’t match their country or region). The team tagged content by geography (such as UK-only or Romania-only), so the agent would be fed the correct information for that geographic area.

The process of fixing mismatches also yielded insights.

David Finney, a director of IT Service Management in Microsoft Digital, frames the process as a clear lesson: AI is only as good as the content behind it, so the real work is often on the back end.

“Instead of treating mismatches as failures alone, we used them as signals to improve the underlying content—revising articles, correcting categorization, and closing gaps in coverage,” Finney says. “Over time, this combination of tightly scoped data sources, country‑level tagging, and ongoing content curation turned the agent into a far more reliable assistant.”

Impact and results

The Global Support team added a continuous feedback loop to keep the agent’s content aligned with reality. Users can flag low-quality and inaccurate answers directly through the agent interface. That data flows to a dedicated knowledge management team, creating an efficient pipeline for feedback to inform back‑end fixes and product improvements.

“We’re measuring success by a reduction in tickets, but that’s based on the user having a better experience using the Employee Self-Service Agent versus calling our global help desk and talking to a person. We can only be truly successful if we are creating a better experience for our users.”

Anders Jepsen, director, Field IT Management, Microsoft Digital

Today, the Employee Self-Service Agent’s metrics are moving in the right direction.

The team is optimistic as the Global Support Services data shows agent activity steadily increasing after it officially went live last October, as shown in the following image. At the same time, usage of Legacy Bot (an existing digital support chatbot) decreased, along with support interactions via phone, email, and web.

This data suggests the agent is meeting its ultimate goal: To provide users with an improved support experience, including better first‑touch answers that build employee confidence and yield faster issue resolution. This reduces escalation to human-run support channels and decreases the volume of tickets our employees have to create.

“We’re measuring success by a reduction in tickets, but that’s based on the user having a better experience using the Employee Self-Service Agent versus calling our global help desk and talking to a person,” says Anders Jepsen, a director of Field IT Management in Microsoft Digital. “We can only be truly successful if we are creating a better experience for our users.”

What’s next for self-service support

Our experience deploying the Employee Self-Service Agent in Europe North has allowed us to create a playbook for other small and midsize countries in similar situations, including dealing with multiple languages and specific regional policies.

“Our long-term ambition is to reduce our human-led support tickets by 40 percent. In some areas, like Europe North, we are already taking a significant step toward that.”

Trent Berghofer, general manager, Microsoft Digital Modern Support

The agent now serves as both a self-service tool and the first contact point for employee questions. It doesn’t completely remove humans from support, because if that first point of contact doesn’t resolve the IT issue, a team of humans is available to help.

In the end, the fewer support tickets that are opened, the more time employees can have back for higher-value tasks.

“Our long-term ambition is to reduce our human-led support tickets by 40 percent,” says Trent Berghofer, a general manager in Microsoft Digital Modern Support. “In some areas, like Europe North, we are already taking a significant step toward that.”

The Employee Self-Service Agent is a great example of using the power of AI to increase employee productivity and efficiency, as they access highly curated support through the tool on demand. It fits in with our company’s overall strategic efforts to evolve into an AI-driven Frontier Firm.

“The agent brings IT, HR, and facilities together in one place,” Dubuisson says. “It’s not just a Q&A bot. It gives you information, guides you, and even holds your hand through troubleshooting. The agent tells you what to do and can even do it for you. It standardizes, simplifies, and still lets you chat with someone or get a call back when you need it.”

Key takeaways

Here are steps organizations can take today to implement an AI-powered employee support hub:

• Evaluate your employee support systems. Assess whether employees have a single, trusted “front door” for support issues, or if your organization’s support is still fragmented across different tools.
• Audit local policy coverage in your AI solutions. Identify where tools may be defaulting to global or geographically incorrect content–especially in regions with multiple countries or languages–to validate accuracy and boost trust.
• Pilot localized AI support efforts in a diversified region. Engage regional HR, IT, and field adoption teams early on to make sure that AI experiences reflect real, country-specific employee needs.

Try it out

Learn all about the Employee Self-Service Agent.

Related links

• Check out our in-depth guide to deploying the Employee Self-Service Agent.
• See how we’re accelerating support services at Microsoft with the Employee Self-Service Agent.
• Read about how the agent improves campus and facilities-related support at Microsoft.
• Explore Microsoft Learn content about the Employee Self-Service Agent.
• Watch a Microsoft Ignite Session about the Employee Self-Service Agent.

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The post Transforming IT support across Microsoft with the Employee Self-Service Agent appeared first on Inside Track Blog.

Yonatan Zunger, CVP and deputy CISO for Microsoft, suggests focusing exclusively on hardening a piece of software to security threats may make it difficult to use and introduce a new risk when users get frustrated and try to bypass controls. This is why engineers need to consider not just individual components but how they work together to maintain productivity.

“Think of every system as a socio-technical system containing many parts, and all of them working together in unison have to be secured,” Zunger says.

Learn from our experience 

Read our practical advice about applying security fundamentals to AI.

Try it out

Read more from Zunger about applying security fundamentals to AI.

Related links

• Explore more from Zunger about how to deploy AI safely.
• Discover what you need to know about governing autonomous agents.
• Learn about aligning user, developer role, and organizational intent in agent governance.
• Find out how to use Authorization Fabric to govern AI agents at scale.
• Read about agent abuse patterns.
• Identify ways to secure AI agents with Azure AI Foundry.
• Explore how Data Security Posture Management for AI can prevent runtime risks.

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• Want more information? Email us and include a link to this story and we’ll get back to you.

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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.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

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

At Microsoft, we’re leading the way in exploring how workers can use AI agents to help them save time, automate workflows, and amplify human impact. It’s all part of our journey to becoming an AI-first Frontier Firm.

As part of this AI transformation, the Microsoft Azure AI marketing team is modernizing its work through intelligence on tap. Together with a group of Microsoft Foundry developers, the team has been using Foundry to create agent-based tools that are changing the way the marketers work and accelerating their impact.

Microsoft Foundry is our unified, enterprise‑grade Azure platform for building, deploying, and governing AI models and agents—bringing development, operations, security, and governance together in one place.

Marketing: Human challenges, AI opportunities

Marketers today face a challenging work landscape. They’re responsible for reaching diverse and dynamic audiences, adjusting to rapidly shifting market conditions, and promoting ever-expanding product portfolios with tight branding and messaging control—all under intense time pressure at an escalating scale.

At Microsoft, our marketing organization is no exception. It has experienced a 40% year-over-year increase in product launches. This job function is also highly multi-disciplinary, with many marketing professionals wearing different hats and adapting to new capabilities, often involving an array of disparate tools.

It can be an overwhelming space, which makes it easy to overlook outdated content and terminology, produce incomplete materials, or misalign messaging. All of that pressure doesn’t just lead to poor performance, but also employee burnout. It’s not surprising that plenty of marketers feel overtaxed.

“Frontier marketing is about helping our team navigate the AI transition to thrive in their roles. Contrary to people’s fears about AI, this technology is tremendously helpful for amplifying marketers’ ability to connect products and services to their audiences.”

Don Scott, general manager, Azure AI Marketing

Leaders on our Azure AI marketing team recognized these challenges, so they started exploring ways that AI could make their workers’ jobs easier. Two new AI-driven projects have come out of this effort:

• MarThrive: A marketing platform featuring a suite of complementary agents and grounded data designed to improve blog quality, assist with product launches, and deliver competitive intelligence on demand.
• AI Messaging Assistant: A generative AI application grounded in 100,000-plus proprietary customer voices that embeds this intelligence directly into marketing workflows, influencing business decisions in real time.

These tools benefit from the power of AI agents while keeping human creativity firmly at the center of our marketers’ work. Both represent function-aligned agentic design aimed specifically to meet the needs of our marketing team.

These aren’t generic AI platforms. They’re tools built by marketers, for marketers. And they’re a big part of equipping our marketing team to embrace the world of the Frontier Firm.

“Frontier marketing is about helping our team navigate the AI transition to thrive in their roles,” says Don Scott, general manager for Azure AI Marketing. “Contrary to people’s fears about AI, this technology is tremendously helpful for amplifying marketers’ ability to connect products and services to their audiences.”

But these capabilities don’t happen by accident. Before either tool could come to fruition, we first needed to ensure we had a tightly unified, AI-ready marketing data ecosystem.

“If you feed your agents the right data, they’ll be so much more useful,” says Brett Mills-Meiner, a director of AI intake and platform strategy for Microsoft Foundry. “Agent development isn’t the hard part—it’s getting the data in the right place.”

MarThrive: An agentic toolkit built for marketers

After a months-long effort to build secure, scalable integrations across core systems, the marketing team had an agentic toolkit they could use to accelerate product launches. They dubbed it MarThrive.

The creation process relied on a strong strategic vision and close alignment between marketers and AI agent developers.

“AI allows the people who do the work to be a lot closer to the technology they’re using.”

Brett Mills-Meiner, director of AI intake and platform strategy, Microsoft Foundry

The process for developing MarThrive started with getting a handle on the tasks and human needs that AI can fulfill. In many ways, the platform acted as an internal proving ground for agentic patterns by making use of Microsoft Foundry’s platform capabilities.

It was also a way to establish closer collaboration between employees who have specific business needs and Microsoft Foundry developers who can build more complex agents.

“We knew we wanted to use Microsoft Foundry to empower our own organization,” Mills-Meiner says. “AI allows the people who do the work to be a lot closer to the technology they’re using.”

The Azure AI marketing team began by establishing what it wanted to accomplish, the ideal capabilities for the necessary tools, and what their functional requirements would be. One major step was defining the specifications and workflows the tool needed to support. Another was getting the live data connections set up, which helped them properly contextualize and ground the agents (with FoundryIQ playing a big role in getting the most from the organizational data).

The main goal was to improve the consistency of the many blogs and messaging surfaces the team oversees, while also minimizing the need for review. From there, it was a matter of experimenting with how individual agents could accomplish those goals.

The results were astounding, as the tool enabled a small team to generate a host of agents on a very tight timeline. In just three weeks, the agent-builder team created 12 agents and released them over 12 days: Azure AI marketing’s so-called “12 Days of Shipmas.” The agents covered a wide variety of functions, as shown here:

MarThrive users in action

Sharmila Chockalingam and Jenn Cockrell are both senior product marketing managers on the Microsoft Foundry team. The agents they access through MarThrive have become instrumental to their work and productivity.

“We typically don’t get all the information about a model until a few days before its launch on Foundry; the MarThrive tool has made rapid iteration and review possible.”

Sharmila Chockalingam, product marketing director, Microsoft Foundry Models

One of Chockalingam’s greatest challenges has been working with partner contributors to launch third-party models as they get added to Foundry. Model releases vary in scope, so they require a spectrum of marketing assets like blog posts, social copy, pitch decks, sizzle videos, product demos, and FAQs.

For Chockalingam, MarThrive provides the greatest value through the Social Copy Generator and Edit Suggester. These agents help her get incoming copy from model partners into consistent shape quickly. Meanwhile, the BOM Generator agent helps her team rapidly spool up full complements of assets to support launches properly.

“On one of our major, late-breaking model launches, MarThrive really proved how crucial it could be,” Chockalingam says. “We typically don’t get all the information about a model until a few days before its launch on Foundry; the MarThrive tool has made rapid iteration and review possible.”

One of Cockrell’s areas of responsibility is managing one of our Tech Community blogs. This blog relies heavily on multiple internal and community contributors, so it can be a challenge to review output and ensure quality at scale.

“The main benefit is the single pane of glass that gives marketers access to the agents they need.”

Jenn Cockrell, senior product marketing manager, Microsoft Foundry

The Blog Grader agent provides an initial scrub of a contributor’s work, giving immediate feedback and a grade for aspects like technical depth and visuals. From there, Cockrell can provide contributors with specific, actionable feedback so they can improve their submissions.

At a more strategic level, the Blog Tree Explorer helps her position different blog posts within our overall approach to content. It also gives her team the comprehensive visibility it needs to establish baseline standards around branding, quality, and best practices.

“MarThrive really only rolled out in December of last year, and we’ve already seen immediate value and better output, as well as improvements to the AI tool,” Cockrell says. “The main benefit is the single pane of glass that gives marketers access to the agents they need.”

To keep our blog quality standards fresh and evolving, the team uses an agent that connects to the rest of the MarThrive ecosystem: Calibration Studio.

When a blog post performs particularly well, the team works with this agent to apply its learnings to other tools like the Edit Suggester and Blog Grader. This produces a multi-agent workflow that relies on human judgment to make adjustments that align with our priorities as a business.

Thanks to these tools, the team has seen the conventional product marketing cycle shrink from 18 months to as low as 18 hours. We’ve also boosted our blog post engagement metrics by 10–12 points.

On the popular Microsoft Tech Community site, publishing a blog post used to involve at least a week of reviews and communication back-and-forth between the author and our marketers. With an average of 250 posts a year by our marketing team, that was no small commitment.

Today, writers submit their work, and a product marketing manager can run the draft through the Blog Grader agent. If their post gets a high enough score, the marketer will proceed with publication. That translates to at least four hours of time saved per post for our product marketing managers.

The overall result is a substantial reduction in human effort while quality improves, velocity increases, and our marketers can spend more time on strategy and big-picture guidance.

The AI Messaging Assistant: An audience marketing ally

As the discipline of marketing has modernized, the possibilities for reaching highly tailored and targeted segments have only increased. But to be truly effective, this requires greater granularity and deeper insights, all in the context of accelerating market changes. That analysis takes time—time that marketers don’t usually have.

With that pressure in mind, the Azure AI market research team set out to augment its ability to flow audience insights directly into their work. The result was the AI Messaging Assistant.

At the outset of this project, there were questions about whether to use Microsoft Copilot Studio or Microsoft Foundry to create the AI Messaging Assistant tool. The team eventually decided that Foundry offered the end-to-end capabilities it needed—from building, deploying, and governing the agent to iterating and updating it as time went on.

Research is a very specific discipline, so creating this tool relied on close collaboration between the Microsoft Foundry team, data scientists, and researchers. The core goal was to help the research team scale their skills by extending their work through AI agents.

In defining the solution, the teams mapped the process from research to marketing output, identifying processes that often get left by the wayside in day-to-day workflows because of time pressure and resourcing.

The AI Messaging Assistant was built to bridge those gaps. It accesses our rich store of customer intelligence and builds models on top of it, then applies that data to produce outputs grounded in what real audiences actually think, feel, and prioritize.

Marketers select their audience and parameters and the tool generates or refines content accordingly, including messaging, naming, and feature prioritization. Because every output is rooted in real customer intelligence, the result is marketing content that is more personalized, engaging, and relevant to the audiences that matter most.

“As the speed of marketing increases, the AI Messaging Assistant makes sure we can still represent the voice of the customer. We’re closing the gap between marketer intent and marketing output.”

Robert Graves, senior director, Data Management and Science

A simple user interface was crucial to keeping the process streamlined. Users access the AI Messaging Assistant through an easy-to-manage web portal, then select from 12 different audiences. Examples include gamers and Microsoft 365 users on the consumer side, or IT decision-makers and developers in the commercial space.

Then the user chooses a pre-made output type to guide their messaging. While marketers mostly use the tool for last-mile naming and messaging support, researchers have more flexibility to pore over data through a blank workbook.

The AI Messaging Assistant is not designed to replace humans. Instead, it expands what our human researchers and marketers can do, extending customer intelligence into decisions and moments that would otherwise be out of reach. The process remains human-led. Marketers set the parameters, assess the output, and make the final decisions before deploying.

“A lot of use cases are things we normally wouldn’t have time to research,” says Robert Graves, senior director with Data Management and Science. “As the speed of marketing increases, the AI Messaging Assistant makes sure we can still represent the voice of the customer. We’re closing the gap between marketer intent and marketing output.”

AI Messaging Assistant user in action

Ben Loeb is a product marketing manager on the Microsoft Edge team. His work focuses on ways we’re bringing AI into the browsing experience.

Perceptions of AI, habits around using it, and even the nature of engaging with the internet all mean that the browser marketplace is in a constant state of change. Agile intelligence is key.

“This is a highly competitive space, so we need to adapt quickly,” Loeb says. “We’re always thinking with an audience lens to create messaging that resonates.”

In the course of Loeb’s day-to-day tasks, he tends to use the AI Messaging Assistant to work with pre-built prompts for research projects he’s conducting and populate them with elements specific to a particular initiative. Typically, he’ll specify the product he’s working on, identify the perceptions or attributes he wants to work with, and give the agent the context it needs to craft messaging or naming. He’ll then test the outputs against different audiences, like IT decision makers versus employee users.

“Now we don’t feel like we have to make a trade-off between research and velocity.”

Ben Loeb, product marketing manager, Microsoft Edge

For example, he might suggest that a feature name needs to combine the concept of innovation with objective descriptions of its functionality. The AI Messaging Assistant will deliver options based on the parameters he provides, and he can then take those suggestions through the final, human mile of refining and decision making.

Of course, any product or feature name will still need oversight from our product and branding teams. But the tool provides a starting point grounded in audience insights.

The Microsoft research team is a strategic asset. And like any high-value resource, its impact is greatest when focused on the decisions that most benefit from deep human expertise.

The AI Messaging Assistant expands what’s possible by providing initial intelligence that marketers can act on with confidence, backed by data rather than instinct alone. Teams no longer have to be selective about where customer voice enters the conversation—the tool ensures it’s present across a much broader range of decisions.

The immediate outcome for Loeb and his peers is that they save time and increase output, all while operating with greater confidence.

“Now we don’t feel like we have to make a trade-off between research and velocity,” Loeb says.

The impact has been quite dramatic. Thanks to the AI Messaging Assistant, message testing cycles have accelerated by up to 90%. We estimate the tool has generated at least $10 million in value to date; in one Windows 11 campaign, AI Messaging Assistant marketing enhancements contributed to sales that were 25% above target.

From a confidence standpoint, it’s clear that the Azure AI marketing team trusts and values this tool. So far, the AI Messaging Assistant has informed more than 250 significant business decisions.

Exploring opportunities for AI across the enterprise

The benefits of AI-driven tools like MarThrive and the AI Messaging Assistant aren’t unique to Microsoft. Our experience is just one part of a new approach to work, one where anyone can build the agents they need to make their jobs and lives easier.

This is true whether it’s simple agents that employees create through Copilot Studio Agent Builder or more advanced tools tailored to lines of business, created in partnership with professional developers using Copilot Studio or Microsoft Foundry. It’s clear there are opportunities everywhere for highly personalized, human-centered workflow reinvention.

With the right data foundations, a responsible outlook, a focus on human problems, and a process of experimentation and iteration, you can follow in our footsteps to seek out frontier transformation.

It’s important to note that in the case of both MarThrive and the AI Messaging Assistant, the end product isn’t static. Keeping these tools relevant and effective relies on regular evaluation, feedback loops, and continual calibration to ensure consistent quality.

“What we’ve discovered as we’ve enabled different disciplines to create agents is that there’s tremendous innovation waiting in all of these pockets,” Scott says.

Ultimately, these tools are about reducing cognitive load, not adding process. They’re about helping marketers thrive, not replacing them. And by accomplishing those goals, we’re driving greater impact in marketing: improved quality signals, more consistent application of standards, the ability for small teams to have an outsized impact, and faster experimentation without sacrificing trust.

Key takeaways

If you’re ready to start creating agents that support work in any discipline, consider taking these steps:

• You can use agents for every function. You may not be part of a technical team, but that doesn’t mean agents don’t have a place in your discipline. With simplified tools for agent creation, it’s important for all different parts of your organization to experiment with these initiatives.
• Assess challenges before building solutions. Identify problems where AI solutions could apply, then triage those use cases according to the greatest potential impact.
• These tools need iteration by users to ensure effectiveness. AI tools won’t get things right the first time. You need a good feedback loop to ensure they grow and evolve to fully meet your needs.
• Agentic tools represent a fundamental change in what humans focus on. Human oversight is the key component of Frontier Firm transformation. Think of the human’s role as creating the notion of what a good outcome will be, identifying the data sources needed to get there, and experimenting with AI solutions.
• Managing agents will require resources. Consider explicitly creating a role to manage the strategic planning of agent processes: identifying goals, setting targets, and managing feedback and iteration.

Try it out

Explore Microsoft Foundry on Microsoft Learn.

Related links

• See how we’re becoming an AI-first frontier firm at Microsoft.
• Learn how we’re extending our infrastructure to manage agents at Microsoft by deploying Microsoft Agent 365.
• Find out how we’re powering agentic AI adoption at Microsoft: Our ‘Customer Zero’ story.
• Read our IT playbook for the AI era and explore ways Microsoft is becoming a Frontier Firm.
• Find out how we deployed the Employee Self‑Service Agent and explore our blueprint for enterprise‑scale success.
• See how knowledge workers are forging their own AI tools at Microsoft.
• Learn how we’re shaping AI management at Microsoft with Agent 365 and Copilot controls.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Transforming the marketing function at Microsoft with AI appeared first on Inside Track Blog.

Our teams across Microsoft Digital—the company’s internal IT organization—leaned in. We built tools, workflows, and AI enabled solutions at speed. Momentum followed, along with real enthusiasm and growth.

“We did a lot of good work building community and excitement. But at some point, we needed to evolve and put more structure around what we’d built.”

Qingsu Wu, principal group product manager, Microsoft Digital

But increasing scale required us to evolve our approach.

As adoption accelerated, we began to see duplication, uneven governance, and growing gaps between strategy and delivery. What helped us move fast early on wasn’t enough to sustain impact over time.

“We did a lot of good work building community and excitement,” says Qingsu Wu, a principal group product manager who leads the AI CoE at Microsoft Digital. “But at some point, we needed to evolve and put more structure around what we’d built.”

AI agents and solutions began appearing across Microsoft Digital. Different teams solved similar problems. Standards were interpreted differently. Reporting was inconsistent, and in many cases manual.

The question was no longer, “How do we help teams try AI?” It became, “How do we turn AI into consistent, measurable outcomes at scale?”

Answering that question required a change in how our CoE operated.

Rather than acting primarily as an advisory group, the AI CoE evolved into an execution‑focused function. Its role expanded from guidance to coordination, helping set priorities, define guardrails, and connect AI work directly to business outcomes.

The goal wasn’t to slow AI innovation down, but to help it move in the correct direction with more agility and better scalability.

Evaluating AI for Microsoft

The AI CoE connects AI strategy to execution across Microsoft Digital. It operates as a cross‑functional coordination layer that sets direction and creates shared accountability for how AI work gets done.

“We can see patterns that a single team can’t. We’re translating AI CoE strategy and enterprise priorities into clear execution plans that work in each organization’s context. That helps us align priorities and make sure the biggest bets are actually landing.”

Ria Khetan, senior program manager, Microsoft Digital

The CoE brings our leaders and practitioners together from AI, data, responsible AI, and operations to answer questions collectively. We use that cross‑disciplinary view to operate above individual projects without losing touch with day‑to‑day reality.

The CoE looks across the organization and answers questions individual teams can’t answer on their own.

• What AI initiatives are already in flight?
• Which ones matter most to the business?
• Where are teams duplicating effort?
• Where do we need clearer standards or stronger governance?

“We can see patterns that a single team can’t,” says Ria Khetan, a senior program manager in Microsoft Digital who helps lead program management for the AI CoE. “We’re translating AI CoE strategy and enterprise priorities into clear execution plans that work in each organization’s context. That helps us align priorities and make sure the biggest bets are actually landing.”

We’ve designed the AI CoE to act as the connective tissue between leadership intent and execution on the ground. It helps ensure that AI work across Microsoft Digital moves forward with purpose, consistency, and measurable impact.

Building transformation on core pillars

The AI CoE establishes a common structure that helps our teams work toward the same outcomes, even when they are building different solutions.

“We use the CoE to bring consistency to how AI work gets done. It gives us a way to step back and ask whether we’re solving the right problems and whether we’re set up to scale.”

Don Campbell, principal group technical program manager, Microsoft Digital

The operating model is intentionally simple.

AI initiatives are reviewed against shared pillars that help teams think beyond individual projects. These lenses ensure the work aligns to business priorities, can scale safely, has a clear delivery path, and supports responsible adoption.

“We use the CoE to bring consistency to how AI work gets done,” says Don Campbell, a principal group technical program manager who leads AI strategy here in Microsoft Digital. “It gives us a way to step back and ask whether we’re solving the right problems and whether we’re set up to scale.”

Our CoE uses these four pillars to guide our work:

• Strategy. We work with product and feature teams to determine what we want to achieve with AI. They define business goals and prioritize the most important implementations and investments.
• Architecture. We enable infrastructure, data, services, security, privacy, scalability, accessibility, and interoperability for all our AI use cases.
• Roadmap. We build and manage implementation plans for all our AI projects, including tools, technologies, responsibilities, targets, and performance measurement.
• Culture. We foster collaboration, innovation, education, and responsible AI among our stakeholders.

These pillars are the common language that helps us connect strategy to execution and make decisions across all teams and scenarios at Microsoft Digital.

Strategy

Our CoE strategy team’s role is to step back and create clarity.

Our strategy is driven from the organization’s top level, and executive sponsorship is crucial to executing our implementation well. When our transformation mandate comes from the organization’s leader, it resonates in every corner of the organization, every piece of work, and every task. We also encourage and welcome ideas from every level of the organization, empowering individuals to contribute their AI insights.

We maintain a centralized view of AI initiatives across Microsoft Digital, including agents, workflows, and AI‑enabled solutions. That visibility allows our CoE team to identify duplication, surface opportunities to scale successful ideas, and align investments to enterprise priorities. This creates a shared intake and prioritization model.

One of our CoE strategy team’s most significant responsibilities is prioritizing the idea pipeline for AI solutions. All employees can feed ideas into the pipeline through a form that records important details. The strategy team then evaluates each idea, analyzing two primary metrics:

• Business value. How important is the solution to our business? Potential cost reduction, market opportunity, and user impact all factor into business value. As our business value increases, so does the idea’s position in the pipeline priority queue.
• Implementation effort. We focus on clearly defining the problem statement—what the problem is, why it matters, who the customer is, the baseline metrics, and the plan to attribute value pre‑production. This ensures we prioritize AI for the most critical business problems and can measure impact before and after deployment.

By anchoring AI work in business outcomes from the start, the strategy pillar helps ensure the organization’s energy is spent on the work that matters most.

Architecture

Our architecture pillar defines how we help teams scale AI solutions without creating security gaps, compliance issues, or technical debt they’ll have to unwind later.

“The CoE introduces a framework to enable design reviews in the early development phase. We help make sure teams are choosing the right platforms and thinking about security and compliance from the beginning.”

Qingsu Wu, principal group product manager, Microsoft Digital

Before solutions move into broader use, our architecture team helps think through data readiness, platform alignment, and governance requirements. The goal isn’t to prescribe a single architecture, but to make sure foundational decisions won’t limit scale or create risk down the line. Many times, this means doing things before development, while other times it means making improvements after the initial development is done and the product or scenario is launched and being used. We also track our efforts with measurable metrics like usage.

One common pitfall is that teams may gravitate toward the most flexible platforms with full control, without fully understanding the associated security and compliance implications. To address this, we publish clear guidance to help teams choose the right platform—one that strikes the appropriate balance between flexibility and the security and compliance effort required.

Our architecture pillar helps prevent that by reinforcing a set of common expectations. Teams still build locally and move fast, but they do so within a framework that supports reuse, interoperability, and responsible operation built on enabling teams and employees to experiment with guardrails that keep our production systems safe.

“The CoE introduces a framework to enable design reviews in the early development phase,” Wu says. “We help make sure teams are choosing the right platforms and thinking about security and compliance from the beginning.”

Teams are encouraged to build on recommended platforms and services that support enterprise‑grade security, observability, and lifecycle management. This helps ensure solutions can be monitored, governed, and supported over time.

Security and compliance are never treated as downstream checkpoints. Architectural guidance reinforces the need to design with identity, access controls, auditability, and responsible AI principles from the start.

When solutions prove valuable, we look for opportunities to reuse architectural patterns, components, or services rather than rebuilding them in isolation. This reduces duplication and accelerates future work.

Roadmap

Our CoE roadmap team examines our employee experience in the context of our AI solutions and governs how we achieve the optimal experience in and throughout AI projects. It focuses on how our employees will interact with AI. Getting the roadmap right ensures user experiences are cohesive and align with our broader employee experience goals.

We’ve recognized AI’s potential to impact how our employees get their work done.

Their experiences and satisfaction levels with AI services and tools are critical. Our roadmap pillar is designed to encourage experiences across all these services and tools that are complementary and cohesive.

We’re focusing on the open nature of AI interaction.

“We’re surfacing AI capabilities and information when the user needs them, according to their context,” Campbell says. “It makes the user experience and user interface for an AI service less important than how the service allows other applications or user interfaces to interact with it and harness its power.”

A key part of this approach is disciplined experimentation.

Rather than treating every idea as a long‑term commitment, the roadmap pillar helps teams validate value early. Our teams know when they’re in an experimental phase and when they’re expected to operationalize. This gives our leaders a more consistent view of progress and risk. The net result is that dependencies between teams surface earlier, when they’re easier to resolve.

Culture

Our culture pillar ensures that AI adoption across Microsoft Digital is intentional, responsible, and sustainable.

Culture underpins everything we do in the AI space. Ensuring our employees can increase their AI skillsets and access guidance for using AI responsibly are critical to AI at Microsoft.

“We’re driving a shift from ad‑hoc AI usage to intentional, outcome‑driven adoption,” Khetan says. “That requires clarity, education, and shared expectations.”

In practice, that means the culture pillar defines how our teams are expected to adopt AI and integrate it into their work, not just what tools they can use.

Our culture team works with AI champions across the organization to translate enterprise AI priorities into local execution. Those champions act as two‑way conduits, bringing real‑world feedback and blockers back to the CoE and carrying guidance, standards, and learnings back to their teams.

Without this structure, AI adoption tends to fragment as teams experiment in isolation.

Our culture team has published training, recommended practices, and our shared learnings on next-generation AI capabilities. We work with individual business groups at Microsoft to determine the needs of all the disciplines across the organization. That work extends to groups as diverse as engineering, facilities and real estate, human resources, legal, sales, and marketing, among others. 

Responsible AI is embedded throughout that work.

The CoE reinforces responsible AI practices as part of everyday decision‑making—during design, experimentation, and scale. Teams are expected to understand not just what they’re building, but the implications of how they build it.

In the AI CoE, culture isn’t abstract. It shows up in how teams propose ideas, how they design solutions and how they measure success.

Fostering agent innovation

The true value of the AI CoE is evident when strategy, architecture, roadmap, and culture come together around real work.

A clear example of that is how we addressed the rapid growth of AI agents across the organization.

“That’s the core problem we’re trying to solve. In the past, admins had to go to multiple portals just to understand how many agents exist, and they all give different answers.”

Garima Tiwari, principal product manager, Microsoft Digital

Our teams were building agents in different platforms, for different scenarios, and at very different levels of maturity. That flexibility accelerated innovation, but it also made it difficult to answer basic questions.

• How many agents exist today?
• Which ones are in production?
• Which ones touch sensitive data?

The strategy lens helped clarify what mattered most. Our goal wasn’t to inventory every experiment. It was to gain visibility into agents that were active, scaling, or depended on by others, and to ensure those agents aligned to business priorities and Responsible AI expectations.

Architecture quickly followed.

As the CoE looked at how agents were built, we quickly discovered that information about agents was fragmented across tools. Different platforms showed different numbers. Ownership wasn’t always clear. And governance signals were hard to reconcile.

“That’s the core problem we’re trying to solve,” says Garima Tiwari, a principal product manager in Microsoft Digital leading our internal strategy and adoption of Agent 365. “In the past, admins had to go to multiple portals just to understand how many agents exist, and they all give different answers.”

This is where Agent 365—which we use to govern agents here at Microsoft—became a critical enabler.

Agent 365 brings together signals from multiple agent‑building platforms into a single, consolidated view. That visibility allows the CoE and administrators to understand agent inventory, ownership, lifecycle state, and governance posture in one place.

“Agent 365 is really about accurate inventory and observability,” Garima says. “It provides one number we can trust and a way to see how agents are behaving, who they’re interacting with, and whether they’re compliant.”

That architectural clarity changed how decisions were made.

Instead of guessing what was safe to scale, the CoE could see which agents were production‑ready, which needed remediation, and which should remain in experimentation. Security, privacy, and compliance considerations moved to earlier in the lifecycle.

“We can’t scale what we don’t understand,” Wu says. “Agent 365 helps us see what’s actually running so we’re not scaling something blindly.”

The roadmap lens then brought structure to execution.

“What changed was the mindset. Teams started thinking about manageability, security, and scale much earlier, not after an agent was already deployed.”

Don Campbell, principal group technical program manager, Microsoft Digital

Rather than standardizing everything at once, the CoE helped teams sequence work. Some agents stayed in pilot. Others moved toward broader rollout, informed by architectural and governance signals surfaced through Agent 365.

Culture and enablement ran alongside that work.

Teams began factoring operational readiness into design decisions instead of treating governance as a final checkpoint. Agent 365 isn’t positioned as a control tool at the end of the process, but as part of building agents the right way from the start.

“What changed was the mindset,” Campbell says. “Teams started thinking about manageability, security, and scale much earlier, not after an agent was already deployed.”

The outcome wasn’t a single standardized solution.

It was a repeatable approach within a shared CoE framework, supported by platforms like Agent 365, that made scaling AI more visible, more manageable, and more intentional.

That’s what the AI CoE enables at Microsoft Digital.

Key takeaways

If you’re just starting to consider AI usage at your organization, or if you’re already creating a standardized approach to AI, consider the following:

• Start with outcomes, not tools. AI work scales faster when teams align on the business problem first and select technology second.
• Design for scale from day one. Early architectural decisions around data, security, and platforms determine whether solutions can grow—or need to be rebuilt.
• Make experimentation disciplined. Clear paths from prototype to production help teams move fast without committing to ideas that haven’t proven value.
• Treat governance as an enabler, not a gate. Visibility and manageability, supported by platforms like Agent 365, make it easier to scale AI responsibly.
• Create shared accountability. Standard metrics and automated reporting turn AI activity into measurable progress.

Try it out

Learn more about how Microsoft Agent 365 enables agent governance and manageability.

Related links

• Discover, create, and onboard an agent in Agent 365.
• Use and collaborate with agents in Agent 365.
• Learn about responsible AI at Microsoft.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Powering the technical veracity of AI at Microsoft with a Center of Excellence appeared first on Inside Track Blog.

• The case for AI in employee assistance
• Chapter 1: Governance means getting your data right
• Chapter 2: Implementation with intention
• Chapter 3: Driving adoption by breaking old habits
• Begin your journey with the Employee Self-Service Agent

The case for AI in employee assistance

The advent of generative AI tools and agents has been a game changer for the modern workplace at Microsoft. And one of the foremost examples of how we’re reaping the benefits of this agentic revolution is our deployment of our new Employee Self-Service Agent across the company.

Thanks to the power of AI, agents, and Microsoft 365 Copilot, our employees—and workers everywhere—are discovering new ways to be more productive at their jobs every day. Recent research shows that knowledge workers are increasingly seeing big gains from using AI tools for work tasks. According to our Microsoft Work Trend Index:

As an AI-first Frontier Firm, Microsoft is at the leading edge of a transformation that’s bringing this technology into all aspects of our workplace operations. With tools like Microsoft 365 Copilot providing “intelligence on tap,” we’re forging a human-led, AI-operated work culture that enables our employees to accomplish more than ever before.

Bringing AI to employee assistance

As part of this move to embed AI across our enterprise, it was a natural step for us to apply this burgeoning technology to a common pain point for us and many workplaces today—employee assistance.

Workers in organizations large and small face many common issues in their day-to-day jobs. Whether it’s a problem with their device, a question about their benefits, or a facilities request, our typical employee was often forced to navigate a bewildering array of tools, apps, and systems in order to get help with each specific task.

This confusion is reflected in research showing that most workers are dissatisfied with existing employee-service solutions.

Our studies show that most employees have trouble finding the appropriate tools and resources they need to address their workplace-related questions.

Realizing that this was an ideal opportunity for AI, we set out to develop a state-of-the-art agentic solution. At Microsoft Digital, the company’s IT organization, we partnered with our product groups to develop and deploy the Employee Self-Service Agent, a “single pane of glass” that employees can turn to any time they need help. The product is now broadly available in general release.

“With this employee self-service solution, we’re shaping a new era in worker support. With AI, every interaction is intuitive, every resource is within reach, and help feels seamless—creating an experience that empowers our people and accelerates business outcomes.”

Nathalie D’Hers, corporate vice president, Microsoft Employee Experience

Because Copilot is our “UI for AI,” the Employee Self-Service Agent is delivered as an agent in Microsoft 365 Copilot. If your employees have access to Copilot, you can deploy the agent at your company at no extra cost. If your employees don’t have a Copilot license, they can access it via Copilot Chat if it’s enabled by your IT administrator.

For the initial development and launch of our Employee Self-Service Agent, we decided to provide agentic help in three categories: Human resources, IT support, and campus services (real estate and facilities). Every organization will have to make its own determination for which functions to include in their implementation. Note that the agent is inherently flexible and expandable; we plan to add additional capabilities, such as finance and legal, in the future.

We learned many lessons in the almost year-long process of developing and implementing the Employee Self-Service Agent across our organization worldwide. The goal of this guide is to pass on what we learned—including how we used it to provide value to our employees and vendors—to help you prepare for, implement, and drive adoption of your own version of the agent.  

“With this employee self-service solution, we’re shaping a new era in worker support,” says Nathalie D’Hers, corporate vice president of Microsoft Employee Experience. “With AI, every interaction is intuitive, every resource is within reach, and help feels seamless—creating an experience that empowers our people and accelerates business outcomes.”

Before you start: Developing your plan

As you embark on your Employee Self-Service Agent journey, make sure to establish a clear and structured plan. This was a critical step for us in our deployment, and we can say with confidence that it will help you avoid surprises and increase your chances of a successful outcome.

Based on our experience here at Microsoft, the below is a high-level outline of the steps you should consider as you prepare for deploying your agent.

1. Define prerequisites
Start by making sure that all foundational elements for the agent are in place.

• Assign licenses to your employees who will interact with the agent. They will need Microsoft 365 Copilot or Copilot Chat.
• Verify readiness by configuring your Power Platform environments, applying Data Loss Prevention (DLP) policies, and setting up isolation (limited and controlled deployment with guardrails in place) where needed.
• Ensure connectivity with critical systems by confirming that you have appropriate APIs and connectors available and functioning for the essential workplace systems that your organization uses (e.g., Workday, SAP SuccessFactors, and ServiceNow).

2. Identify your core team and responsibilities
Successful implementation of the Employee Self-Service Agent requires collaboration across multiple roles and departments in your organization.

• Business owners from the areas your agent will cover—such as human resources and IT support—can help you define requirements, priorities, success criteria, and telemetry needs.
• Platform administrators, particularly for Power Platform and tenant/identity teams, can manage your technical configuration.
• Content owners and editors are needed to identify the knowledge sources to surface in the agent, curate new knowledge sources, and maintain the data underpinning these sources on an ongoing basis.
• Subject matter experts can provide important “golden” prompt and user scenarios that the agent should prioritize and answer accurately.
• Compliance, privacy, and security leaders and their teams are needed to address risk considerations.
• Support professionals can help build a structure for live agent escalation and ticketing operations (in situations where the agent is unable to provide a solution).
• Focus groups of end users assist with validating requirements and scenarios, as well as help with testing the agent.

3. Establish a clear timeline
We found that creating a schedule for the creation, implementation, and adoption of the agent is crucial. This phased approach will help you maintain momentum and accountability over the duration of the project.

For example, here’s a rough implementation timeline that you might use to gauge your progress:

4. Articulate your vision

Communicate your rollout plan to your team, including timelines and phases, and adjust it based on feedback. Establish clear goals and meaningful success metrics to guide you and make sure your efforts are in alignment with your company objectives. (Note: You may want to consider key upcoming projects or events in your organization and link the agent roadmap to them. This will help you meet your project’s success criteria faster and encourage quicker agent adoption.)

5. Define your governance

This phase will allow you to define policies and standards and conduct a thorough content audit to ensure accuracy, relevance, security, and sustainability.

6. Implement your agent

This phase involves configuration and integration, followed by testing.

7. Roll out the agent while driving adoption and measurement

We advise deploying the Employee Self-Service Agent using a phased, or ringed, approach. We started with a small group of employees, then gradually rolled it out to larger and larger groups  before finally releasing it to our entire organization.

We encouraged adoption with internal targeted communications and promotional efforts. Careful measurement enabled us to track impact and optimize agent performance. This type of concerted change management allowed us to share the latest product developments with our employees and to keep them excited and engaged with the tool.

By investing sufficient time and effort in the planning phase of your deployment, you’ll create a strong foundation for a secure, scalable, and successful self-service agent experience.

Chapter 1: Governance means getting your data right

When a Microsoft employee enters a query into an AI chat tool like Microsoft 365 Copilot, they know that they may not receive an individualized response that is directly specific to their situation. They are aware that they might need to verify the answer they receive with further research and additional sources.

But when it comes to our company-endorsed self-service agent, the stakes are different. Our employees expect to receive accurate and personally relevant responses when they ask for help. This is particularly true for queries related to important personal details, like HR-related questions about leave policies or benefits.

“People expect personally tailored and highly accurate answers, especially for HR moments that really matter. We designed the Employee Self‑Service Agent with that expectation in mind, pairing trusted data and deep personalization with strong governance controls so that privacy, security, and trust are built into every interaction.”

Prerna Ajmera, general manager, HR digital strategy and innovation

Although the Employee Self-Service Agent comes pretrained with basic HR and IT support data, we found that the quality of the responses that our employees receive is directly connected to the accuracy, currency, and depth of the information we provide to the tool. You’ll want to spend the necessary time and effort to make sure that your data governance process is well thought-out and thorough, so that your employees experience the best possible results.

“Employee self‑service has a higher bar than generic AI tools,” says Prerna Ajmera, general manager of HR strategy and innovation. “People expect personally tailored and highly accurate answers, especially for HR moments that really matter. We designed the Employee Self‑Service Agent with that expectation in mind, pairing trusted data and deep personalization with strong governance controls so that privacy, security, and trust are built into every interaction.”

Major considerations for governance

We learned that before you configure your agent, you need to establish guardrails that protect your data’s integrity and that build your employees’ trust. These considerations will form the backbone of your governance framework:

• Managing requirements: Define what the agent must deliver and align your stakeholders on clear, prioritized goals and objectives.
• Determining and managing resources: Ensure you have the right people, systems, and funding in place to support your full product lifecycle.
• Data security: Protect your sensitive employee information with strong controls, compliant storage, and least‑privilege access.
• User access: Establish who can use, administer, and update your agent, with appropriate permissions and guardrails.
• Change tracking: Monitor your updates to content, configurations, and workflows so your agent always reflects your current policies.
• Reviewing: Regularly evaluate your content’s accuracy, the agent’s performance, and your organizational fitness to help you keep your employees’ experience with the agent trustworthy.
• Auditing: Maintain traceability for compliance, incident investigation, and quality assurance across all of your data flows.
• Deployment control: Manage where, when, and how you roll out new versions of the agent to reduce disruption and ensure consistency.
• Rollback: Prepare a fast, safe path to reverting your changes if something breaks.

We found that addressing these considerations early in the process creates a governance structure that is proactive rather than reactive, increasing the quality of responses and setting your organization up for success.

Architecture essentials

Understanding the architecture of our agent helped our governance teams make informed decisions about our configuration and integration. To do that, they needed to review and understand its key architectural components. You’ll need to do the same.

Here’s a list of the different architecture components that our team assessed, to help you get started on your own process:   

• Topics: Structured intents (e.g., “view paystub”) that align to employee questions and drive consistent answers.
• Domain packages: Pre-curated bundles for different agent segments (like HR and IT support) that provide reusable patterns, prompts, and integrations.
• Knowledge sources: Documents, intranet pages, FAQs, and databases that ground responses in authoritative content.
• Connectors: Secure integrations to systems of record (like Workday or SAP SuccessFactors) can help enable read/write operations. (Because the Employee Self-Service Agent was built with Copilot Studio, it has access to more than 1,400 different connectors.)
• Instructions: Governance-approved rules and prompts that shape tone, guardrails, and escalation behavior.

Assessing and preparing your content

A key early governance step is to audit all relevant content in your knowledge bases. This process should include assessing, updating, and, if necessary, restructuring this information before it is ingested by the agent.

An important caveat here is that the agent’s ability to understand which policies and procedures apply to which employee relies on your content having consistent metadata, permissions, and content structure. We found that before feeding your data into the agent, you need to:

• Inventory existing content: Your content will incorporate many different types, such as SharePoint pages, Microsoft Teams posts, PDFs, intranet articles, and knowledge-base documents. The goal of the inventory process is to identify content that is complete rather than outdated, duplicative, or siloed; if there are issues with the content, they should be addressed before loading into the agent.
• Assign knowledge owners: The owners should be SMEs who can help validate, tag, and maintain the content going forward. Part of this process is training up knowledge owners to be able to prepare and maintain content in ways that make it easily consumable by both agents and people.
• Structure content for discoverability: All your content needs to have accurate metadata, well-defined topic pages, and consistent naming so that the agent can surface the right information at the right time.

We found that completing a thorough content audit helps us ensure that the Employee Self-Service Agent isn’t just chatting—it’s delivering trusted, up-to-date answers that save your workers time and effort as they go about their day.

Be aware of tone and conversational flow

Providing vetted and well-structured data to the agent is important, but it’s not the entire battle. You’ll also need to make sure your agent is given clear guidance on conversational tone and instructions on what to do in specific scenarios.

Make sure you incorporate:

• Global instructions: Define the agent’s voice, behavior, and escalation rules to ensure consistency and trust. 
• Topic-level triggers: Map natural language phrases to specific workflows (such as “reset password” or “check PTO”) so the agent routes these common queries correctly.
• Advanced knowledge rules: Prioritize which data sources to use in ambiguous scenarios, and define when the agent should ask clarifying questions.

Taking these steps gave our agent a better chance of being accurate, helpful, and aligned with our organization’s specific preferences.

Addressing common scenarios with “golden” content

Another vital aspect of your content audit is identifying the most frequently accessed information in each topic area.

A good example comes from the preparation of our IT support content for ingestion by the Employee Self-Service Agent. One of the focuses of this effort was on so-called “golden prompts:” the 20 or so topics that generate up to 80 percent of our employee queries (a version of the famous “80/20 rule”).

Our golden prompts are a curated set of scenarios that:

• Represent our critical user workflows and edge cases
• Possess clear, expected responses (golden responses)
• Cover core functionality that must never break

We made sure that the agent was providing high-quality responses for these common scenarios—we recommend you do the same.

Including “zero prompt” content

Another important aspect of your content process should be to develop “zero prompts.” These are preconfigured prompts in the agent that the user can simply click on to get an answer for a common issue or request.

For example, if one of your employees wants to understand how to set up a VPN, they simply click on the zero prompt provided for that topic. The tool then gives them complete instructions on how to set one up.

During our deployment of the agent, one case where we prepopulated the tool with content for a specific, high-demand scenario came when Microsoft made a major announcement regarding employees returning to the office. We knew this policy change would generate a lot of questions from our employees.

In preparation for this, we asked Microsoft 365 Copilot to create a single document that pulled in all the “return to office” material found in its verified HR content database. We then made this document available to the agent. Just by taking that simple step, we saw our user satisfaction ratings in the tool jump from 85 percent to 98 percent for that issue!

In your own deployment, think about what issues and topics generate the most questions from your employees. You can then prepare specific content to address these scenarios, which will increase your chances of success with the agent.

Data security and compliance

Data security was a high priority when we developed our agent, especially because it must necessarily access sensitive HR information on a regular basis. During product development, we made sure that the agent adhered to enterprise-grade security standards, including identity federation, least-privilege access, and encrypted storage.

Because the agent is built on Copilot Studio, it supports robust data-loss prevention features. The agent also complies with regulatory frameworks like General Data Protection Regulation through built-in auditing and data-retention policies.

One of the big advantages that an AI agent has over a static website or similar data source is the ability to personalize responses for each user. At the same time, we had to make sure that the agent had guardrails in place to avoid overexposing sensitive information. This included detailed disclaimers to help call out these kinds of responses and flag them for more careful handling.

Our agent complies fully with our accessibility standards as well. Like all Microsoft products and services, the tool underwent a rigorous review to ensure it was fully accessible for all users.

Responsible AI

Whenever a new AI application is launched, there may be concerns raised about potential challenges regarding bias, safety, and transparency. That’s why the Employee Self-Service Agent follows the Microsoft Responsible AI principles by default.

When you enable the sensitivity topic in your agent, it screens all responses for harassment, abuse, discrimination, unethical behavior, and other sensitive areas. We tested the agent thoroughly for objectionable responses before it was launched to a broad internal audience at Microsoft.

In addition, the agent includes an emotional intelligence (EQ) option. This feature is designed to make responses more empathetic, context-aware, and relevant for diverse user audiences. It analyzes the conversation’s context and tailors the agent’s replies to ensure that users feel understood and valued throughout their session (which could be particularly relevant for any conversations related to sensitive HR topics, such as family leave). The EQ option is customizable and can be turned off by your product admins.

Key takeaways

The following are important considerations for data governance when you deploy your Employee Self-Service Agent:

• Employee expectations regarding accuracy and relevance are high for employee self-service tools, which makes data governance a key aspect of your deployment.
• Consider which data repositories are best to incorporate into your agent, and make sure they are up-to-date and well-structured. This process requires a thorough content audit.
• Pay special attention to the so-called “golden prompts” that make up a large percentage of expected queries. The agent’s answers to these questions should be top-notch.
• Restructuring content can improve response quality. When we anticipated huge interest in a particular topic, such as workplace policy changes, we restructured our content on that subject and saw a significant jump in user satisfaction.
• Build your agent to meet or exceed high standards for data security, privacy, and Responsible AI. These are vital concerns for any product that has access to sensitive personal information.

Learn more

How we did it at Microsoft

• Learn how we’re getting the most out of agents internally here at Microsoft with good governance. This story shares what our Microsoft Digital governance team learned while deploying AI-driven tools here at Microsoft.   
• Find out how we’re unlocking enterprise AI extensibility internally with Microsoft Copilot Studio. This post explains how we’re empowering our employees to create and extend Copilot-based agents using Copilot Studio.
• Read about how we’re infusing responsible AI principles into all our AI tools and projects at Microsoft. An article that explores the Microsoft Responsible AI Standard and how it informs our work with AI technologies at Microsoft Digital.

Further guidance for you

• Explore Microsoft Learn documentation for Microsoft Copilot Studio to read about key concepts in governance and security.
• Examine Microsoft Learn content related to security and data protection in Power Platform.
• Conduct the Microsoft 365 Copilot Optimization Assessment to understand your level of AI adoption and chart your course.
• Access Microsoft Learn documentation for Microsoft 365 Copilot to learn about data, privacy, security, and Zero Trust principles.

Chapter 2: Implementation with intention

Deploying a powerful and versatile tool like the Employee Self-Service Agent is no simple task. It requires guidance and buy-in from top leaders at the company, as well as detailed planning and execution across disparate parts of your organization. Here, we identify some of the key steps that we took here at Microsoft that can help guide you when launching your own self-service agent.

Determine category parameters

One of the first major decisions around implementing the agent is deciding which business function—we call them agent starters—to choose for your initial implementation.

We recommend starting with HR support or IT help (we started with HR). Both agent starters can be deployed into a single Employee Self-Service Agent experience, but they must be deployed one at a time. 

So you know, we’ve built the Employee Self-Service Agent to be connectable with other first- or third-party Copilot agents, enabling a seamless handoff to these agents without having to navigate to other tools or interfaces.

Understanding your deployment steps

There were four essential stages involved in the deployment of our agent, each with multiple steps. Here’s a quick rundown that you can use at your company:

1. Preparation for deployment
   • Establish roles: Define who will manage, configure, and support the tool, assigning responsibilities to ensure accountability during deployment.
   • Set up your environment: Prepare the necessary hardware, operating system, and network configurations so the agent can run smoothly.
   • Set up third-party system integration: Ensure your infrastructure can securely connect and exchange data with external systems that the agent will need to integrate with.
2. Installation
   • Install the agent: Deploy the core Employee Self-Service Agent software on the designated servers or endpoints.
   • Install accelerator packages: Add any desired connectors that enable the agent to communicate with commonly used systems for HR, payroll, IT support, etc.
3. Customization
   • Configure the core agent: Adjust default settings to align with your organization’s policies and workflows.
   • Identify knowledge sources: Specify where the agent will pull information from, such as internal knowledge bases or FAQs.
   • Provide common questions and responses: Add employee FAQs to improve the agent’s ability to respond quickly and accurately.
   • Identify sensitive queries: Flag questions and responses that involve confidential or regulated information to ensure they’ll be handled securely.
4. Publication
   • Approve the agent: Complete internal reviews and compliance checks to confirm the agent meets your organizational standards before full rollout.
   • Publish the agent: Make the configured agent available to your employees in your production environment.

Customization

The Employee Self-Service Agent operates as a custom agent within Copilot Studio, using our AI infrastructure via the Power Platform. The agent is constructed on a modular architecture that allows you to integrate it with your own enterprise data sources using APIs, prebuilt and custom connectors, and secure authentication mechanisms.

To streamline this integration process, we provide a library of prebuilt and custom connectors through both Copilot Studio and Power Platform. Preconfigured scenarios include connecting to major enterprise service providers such as Workday, SAP SuccessFactors, and ServiceNow. (View the full list of connectors offered by Copilot Studio.)

These connectors facilitate data exchange with the following systems and other agents in this ecosystem:

• HR information systems
• IT systems management
• Identity management
• Knowledge base platforms

We found that third-party integrations require setup effort and technical expertise across stakeholders in your tenant. Be sure to get buy-in and involve all relevant departments that will be impacted.

Rollout: A phased approach

As previously noted, we started our agent with HR content and then added IT support (we later expanded to include campus services help as well). We rolled the agent out to different groups of employees and geographic regions around the world over the course of months, adding new knowledge sources to the different categories at each step along the way. This gave us an opportunity to gather user data and refine performance of the tool as we went.

Adding campus support services required us to handle queries and tasks related to dining, transportation, facilities, and similar subjects. This was a challenging addition, because the facilities and real estate space—unlike the HR and IT support areas—doesn’t have many large service providers, which are easier to provide prebuilt connectors for.

One area that did lend itself to prebuilt connectors, however, was facilities ticketing.

Because many of our campus facilities vendors use Microsoft Dynamics 365, we were able to create an out-of-the-box connector in the agent for their ticketing process. You can take advantage of these kinds of preconfigured tools in your deployment.  

Key takeaways

Here are some things to remember when implementing the Employee Self-Service Agent at your organization:

• Decide which starter agent you will deploy first. We recommend starting with a single agent covering one area (vertical), such as HR or IT support, and then expanding from there.
• Consider a phased rollout to allow time to refine responses and ramp up the number of topic areas and knowledge sources installed in your agent.
• Use the prebuilt connectors to make it easier to integrate the agent with your existing systems.We developed customized connectors for major HR and IT service providers and a Microsoft 365 Dynamics connector to integrate with our many facilities vendors around the world.

Learn more

How we did it at Microsoft

• Learn how we’re embracing this “agentic” moment at Microsoft. This post describes how we’re integrating agents into many of our workflows and processes at the company.
• Get our step-by-step guide to how we’re unleashing API-powered agents at Microsoft. This article describes what we’ve learned from deploying agents internally at the company.

Further guidance for you

• Learn how to prepare for a successful Microsoft Employee Self-Service Agent implementation. This Microsoft 365 Copilot Blog story includes a webinar video on the same topic.
• Discover a step-by-step guide to getting your organization prepared for the Employee Self-Service Agent.
• Check out our Microsoft Learn content about deploying the Employee Self-Service Agent.
• Learn more about the customizable accelerator packs that come with the Employee Self-Service Agent.
• Read our Microsoft Learn content about installing the agent.
• Explore Microsoft Learn content about customizing your agent.
• Dive into detailed information about integrating the agent with Workday, ServiceNow, and SAP SuccessFactors.
• Work through this learning path to discover how you can create agents with Copilot Studio.

Chapter 3: Driving adoption by breaking old habits

Once upon a time, when our employees needed help with a technical issue or an HR question, they literally picked up the phone and called the relevant internal phone number. That quickly evolved into an email-centered system, where employee questions were sent to a centralized inbox that would then generate a service request. Still later, chat-based help was introduced.

Using AI to handle employee questions and service requests is a natural step in this evolution, as large-language models were built to parse vast data repositories and return the right information (often with the help of multi-turn queries and responses). And by encouraging self-service, an AI agent can help meet employee needs faster while saving the organization’s staffing resources for other needs.

But getting employees to change their habits and use a tool like the Employee Self-Service Agent wasn’t going to be as easy as just flipping a switch. Here’s how we handled this important change management task at Microsoft.

Adoption across verticals

A key principle that we learned during the adoption process was that 80% of our change management activities for the agent are applicable to all our verticals (whether it be HR, IT support, campus facilities, or another category). We didn’t need to reinvent the wheel each time we added to the topics that the agent covered.

This allowed us to create a change management “playbook” that we could use each time we expanded to a new category. So, while roughly 20% of the strategies we used were specific to that vertical, the vast majority were the same, which saved time as we moved through onboarding the different categories.

Leadership is key

To get our employees to change the way they ask for help, we found it essential to get the support of our key leaders, something we refer to as “sponsorship.”

We found that good sponsorship doesn’t just come from your central product, communications, or marketing groups. It is equally vital to invest in relationships with local leadership in different regions as you roll out the agent (especially in multinational companies like ours).

Local leaders understand the various regional intricacies—including language, functionality, and the rhythm of the business—that can help inspire their segments of the workforce to adopt a new tool, and then evangelize it to others in turn. Working closely with these kinds of sponsors will help you pull off a successful adoption campaign.

If you have works councils, be sure to seek out your representatives and solicit their feedback on your agent experience early on. You can help them understand how the agent was developed and trained, then address any concerns they raise.

We’ve found that once our works councils are made aware of the careful processes we go through to protect user privacy, and to ensure compliance with our Responsible AI standards, they become enthusiastic supporters and can help promote agent adoption. (Read more about our experience with our works councils and the Microsoft 365 Copilot rollout.)

Defining your messaging

Work with your internal communications team to come up with a well-planned messaging framework for your agent rollout. Based on our experience, it’s likely you’ll need to communicate across a wide variety of teams and organizations like HR, IT, facilities, finance, and so on.

It’s important to be clear about how you’re positioning the product for your employees. This will allow you to develop both overall messaging for general use, but also content tailored to specific teams or employee roles. The more sophisticated your messaging, the more likely it is to be effective in encouraging user adoption of the agent in their regular workflow.

Listening to feedback

As Customer Zero for the company, our employees are our best testers and sources of feedback during our product development process. The Employee Self-Service Agent was no different, and we continue to gather crucial feedback and user data throughout the internal adoption process.

Because the agent is a tool centered on helping your workers resolve challenges and get quick answers to questions, you’ll want to set up your own systems for capturing their feedback and make sure the agent is meeting a high-quality bar.

We found that setting yourself up for success when it comes to listening to your employees involves two major aspects: Developing and deploying a system for gathering employee sentiment about the product, and then creating a system for analyzing that feedback and funneling the findings back to your IT team.

Some of the types of feedback and methods we used to gather it during the development process included:

• User-testing data
• User satisfaction ratings
• User surveys, interviews and other research
• Voice of the customer (in-product feedback)
• Pilot projects and focus groups (smaller segments of users)
• IT support incidents
• Usage data and telemetry
• Community-based early adopter feedback (similar to our Copilot Champs community)
• Social media feedback and comments

You can choose from among these options to set up your own feedback mechanisms, or come up with something customized to your implementation.

Calibrating your usage goals

Remember that the Employee Self-Service Agent is not an all-purpose AI tool like Microsoft 365 Copilot, which your employees might use a dozen times a day. Instead, they may only need assistance from HR or IT support, tools, and information sources a few times a week (or even less). Your usage targets should be calibrated accordingly.

At the same time, the more categories of assistance you add to the agent, the more your usage levels can grow—along with user expectations.

When we decided to add campus support (dining, transportation, and facilities-related needs and queries), one of the motivators was to provide information that users might need on a more regular basis. This addition helped us increase adoption and build daily usage habits for the agent among our employees.

Making the agent your front door for employee assistance

Your employees may have longstanding habits around the ways that they seek assistance, such as moving quickly to email a service request, or immediately engaging a live support technician. There might even be someone helpful in the office next to them that they lean on for IT support. We’re aware that breaking such habits can be a challenge.

That’s why we decided to change our own employee-assistance workflows. In the case of HR, we are planning to remove the option to email a centralized alias for help, which was the default in the past. This forcing function will instead prompt our employees to turn to the agent first for assistance, creating a “front door” for all our HR service requests.

For our IT support function, we are switching from a Virtual Agent chatbot to the Employee Self-Service Agent, which should provide users with a richer experience and a higher rate of resolution.

Of course, our main goal is for the agent to handle an employee’s issue without having to seek further assistance. But what happens when the agent cannot resolve their problem or handle their request? That’s why we’ve also implemented a “smooth handoff”—either to create a service request or connect the user to a live agent for specialized assistance.

There are three key steps in this process:

1. The Employee Self-Service Agent can identify when the user has reached a point where they need to move to a higher level of assistance via a live agent or a service request. (Note that we also allow the employee to make that determination for themselves.)
2. We then give them different options for how they want to connect to live support.
3. When the employee is transferred to a live technician, the Employee Self-Service Agent is able to pass on the chat history from its session with the user. That way, the technician or staff support can quickly get up to speed on the situation, see what the employee has already asked about and tried, and start helping them immediately.

Enabling the employee to quickly and smoothly transition to a higher level of support without leaving the chat increases user satisfaction and makes them more likely to return to the agent the next time they need assistance.

Strategic outreach to employees

Of course your workers, like ours, are busy with their day-to-day job functions. They may be resistant to trying a new tool or going through special training on how to access employee assistance. Or they may just not know about it.

Because of our regionally phased rollout of the agent, email was one of the most effective tools we used to connect with specific audiences and make them aware of the tool. With specific email lists, we could make sure that only employees in that phase of the rollout were seeing the message.

A key aspect of getting our employees to adopt any new tool is reinforcement—the process of sustaining behavior change by providing ongoing incentives, recognition, and support. Some of the reinforcement strategies we used for the agent included:

• Targeted communications: Emails and organizational messages invited employees to try the agent as they received access
• Multi-channel campaigns: Promotion of the agent via portals, newsletters, digital signage, and more to keep it at the forefront of employee minds
• Training: Workshops and micro-learning sessions about the agent
• Social campaigns: Posts highlighting the tool to increase awareness and gather employee feedback (see details below)
• Leadership support: Managers modeled usage of the agent and promoted it regularly
• Processes: The tool was part of regular employee workflows

One very important communications channel that we used in our adoption efforts was Microsoft Viva Engage. We set up a private Engage community for the Employee Self-Service Agent, then populated it with each new wave of users as they were given access to the tool (eventually all were given access when the tool went companywide).

We used this channel for various kinds of messaging:

• General product awareness
• Updates on new or changing functionality
• Answering questions or addressing frustrations (two-way dialogue between users and the product team)
• Fun and helpful “tips and tricks” that users could try (these could come from the product team, leadership, or individual product “champions”)

We also inserted messages about the new agent into our regular communications with different audiences, including HR professionals, IT support personnel, and internal comms staff at the company. And we regularly messaged company leaders about it, so they could encourage their teams and direct reports to support the effort and evangelize for the tool.

One thing we did was make clear to our employees that even though the agent was not able to handle an issue today, it might be able to in a month or two. That’s why ongoing communications to users was important.”

Prerna Ajmera, general manager, HR digital strategy and innovation

Of course, as a natural language chat tool, the Employee Self-Service Agent doesn’t require formalized training. The product itself is designed to guide users and allow them to experiment, simply by stating their needs in plain language. Most employees will already be familiar with AI tools like Microsoft 365 Copilot, so effectively using an AI-powered employee-assistance agent should be a low bar to clear.

Managing expectations

Your Employee Self-Service Agent rollout will be an ongoing journey as you add topic areas, functionalities, and other product features. Your product roadmap will evolve as you learn more about what your employees need with this kind of AI solution.

One factor to consider is how to set realistic user expectations about what the agent can do while the product matures and improves. As we gradually rolled out the tool, we messaged that the agent was in “early preview,” which helped avoid employee disappointment when it couldn’t handle a specific request.

“One thing we did was make clear to our employees that even though the agent was not able to handle an issue today, it might be able to in a month or two,” Ajmera says. “That’s why ongoing communications to users was important, as new capabilities were added and speed and accuracy improved.”

We also created messaging for early users indicating that their testing was an integral part of making the tool more effective. This created a positive feedback loop while also keeping employee expectations reasonable.

How we measured success

Carefully tracking and analyzing your success metrics throughout your development and release of the product is a high priority. Without this step, you are working in the dark.

At Microsoft, we identify the key performance indicators (KPIs) for a particular product and then use them as our North Star for any internal release. But the specifics of those KPIs can vary from product to product.

For example, measuring the monthly average user (MAU) statistics might be extremely important for an all-purpose productivity tool like Microsoft 365 Copilot. But for an employee-assistance tool, the goal is not necessarily regular use, because employees aren’t constantly facing challenges that require help (we hope). Usage statistics may also be affected by certain events or cyclical needs, such as annual employee reviews or a major technology change (like a significant Windows update).

With this in mind, we identified certain key metrics for the Employee Self-Service Agent. In this case, the top KPIs included:

• Percentage of support tickets deflected
• Net satisfaction score
• Latency period
• Reliability
• Total time savings
• Total cost savings
• Identified and prioritized issues (reported back to product group)

Overall, we focused on the rate at which employees were able to resolve issues without opening a support ticket, as this would likely generate the greatest return on time and cost savings. We came up with an overall target across the different verticals of 40% ticket deflection, and we’re making solid progress toward this goal as we continue to refine and improve the agent.

Part of our measurement process is a monthly progress meeting of key project stakeholders, where all KPIs are evaluated to see if our targets are being met. If the results do not meet expectations, we identify the potential causes and discuss what adjustments need to be made to address these shortfalls.

Key takeaways

Here are some key things to remember when it comes to adoption efforts for your Employee Self-Service Agent:

• Don’t reinvent the wheel. Most of your change management and adoption strategies for the agent will be the same across different regions and help categories.
• Line up product sponsors. Finding leaders and others across the organization to help you promote the Employee Self-Service Agent within their own groups, functions, and regions can make a big difference in gaining employee trust and encouraging adoption.
• Set up proper listening channels. You’ll want to gather as much feedback as possible from your employees as you roll out the agent so you can understand what is working well and what needs improvement. This kind of feedback loop can also make your employees feel heard and help them shape the tool.
• Make the shift to agent-first help. Employee habits for seeking assistance can be resistant to change. We decided that turning off the “email to create a service ticket” workflow was a great way to nudge our workers to recognize the agent as the first option for their assistance needs.
• Be strategic in your communications. Use tools like email, Viva Engage, and other appropriate communications channels to target your communications and encourage a two-way conversation with employees about the agent. Sharing fun tips and encouraging peer support are other ways to increase awareness and engagement with product.
• Identify your key metrics. We determined our benchmarks for success for this particular type of agent, then tracked them and made the results available to key stakeholders. This allowed us to measure the impact and effectiveness of the product.

Learn more

How we did it at Microsoft

Although some of the blog posts below are about adoption efforts related to Microsoft 365 Copilot, they can give you ideas on how we promote internal adoption of agentic AI products at Microsoft.

• Find out how we’re reimagining campus support with the Employee Self-Service Agent. This post describes how we targeted popular employee queries—such as “What’s for lunch?”—to drive adoption of our new agentic tool in the facilities and real estate space.
• Read about how we drove Copilot adoption using Microsoft Viva. This article explains how Viva provides a powerful suite of tools that can assist with your adoption efforts.
• Learn how we created an internal Microsoft 365 Copilot Champs community to help drive adoption of the tool. This article covers how we created a special community of Copilot enthusiasts at Microsoft, who provided peer training and support for their coworkers’ Copilot journeys.  
• Discover how we built an AI-powered continuous improvement culture at Microsoft. This article provides a detailed examination of how we use data to track adoption and continuously improve our products and processes within Microsoft.
• See how we’re supercharging our internal communications with Microsoft Viva. This post explains how we use tools like Viva engage to build trust and encourage two-way dialogue with our employees about important topics, company initiatives, and key product rollouts.

Further guidance for you

• Explore the formal Adoption Guide for the Employee Self-Service Agent.
• Read the product group’s guide for deploying an Employee Self-Service Agent.
• Check out our Microsoft Learn content about collecting usage data and feedback on the Employee Self-Service Agent.

Begin your journey with the Employee Self-Service Agent

Agentic AI offers incredible promise to transform employee productivity, giving individuals access to powerful tools that enable them to accomplish more. We believe the Employee Self-Service Agent is another step along that path, allowing workers to get instant help with tasks that used to be cumbersome and time-consuming.

“We’re excited to get the Employee Self-Service Agent out and into the hands of our customers, so that they can reap the same benefits that we’re already seeing from it. As we continue to refine the product and expand the number of verticals it can cover, we expect to realize exponential efficiency gains and capture even more cost savings across our entire organization.”

Brian Fielder, vice president, Microsoft Digital

Now that you’ve read about our experience deploying the tool, it’s time to start your own journey. Successful implementation means your people will spend less time on the phone with support staff or hunting through web pages and other resources for help with routine employment tasks and more time devoted to their productive work, reducing job-related pain points and frustrations.

You can benefit from the lessons we’ve learned and the many helpful features and capabilities that we’ve built into this product, all of which are designed to make your implementation as fast, easy, and effective as possible.

“We’re excited to get the Employee Self-Service Agent out and into the hands of our customers, so that they can reap the same benefits that we’re already seeing from it,” says Brian Fielder, vice president of Microsoft Digital. “As we continue to refine the product and expand the number of verticals it can cover, we expect to realize exponential efficiency gains and capture even more cost savings across our entire organization.”

Key takeaways

Here are some of the essential top-level learnings we gleaned from our deployment of the Employee Self-Service Agent, which you should keep in mind as you start out on your own deployment path:

• Identify and engage the right people. You’ll need buy-in and advocacy from leaders across the organization; the involvement of key stakeholders from HR, IT, legal, and compliance; and technical guidance from admins, license administrators, environment makers, and knowledge-base subject matter experts.
• Develop your plan. Understand the major phases of governance, implementation, and adoption of the tool, and make sure that you have adequate resources and support for each phase.
• Verify the quality of your content. Your chances of success will be better if you undertake a thorough content assessment to address the currency, accuracy, and structure of all relevant knowledge bases. Pay particular attention to the topics and tasks that are in greatest demand by employees when they access help services.
• Consider a phased rollout. Releasing your Employee Self-Service Agent to progressively larger groups of workers across your organization allows you to gather data and feedback and improve the performance and relevance of the agent over time. You can also expand the number of categories that your agent covers as you go, increasing the impact and appeal of the tool.
• Communicate strategically to promote adoption. Convincing employees to break longstanding habits when seeking help is a challenge. Email is helpful for targeting specific groups of employees, but be sure to use tools like Viva Engage to create community, answer questions, provide fun tips and tricks, and announce new capabilities and options.
• Set clear goals and measure against them. Come up with a targeted set of KPIs that reflect your organization’s needs and aspirations, then develop a plan to capture data for each of these indicators and a regular reporting cadence to keep stakeholders informed of progress toward your goals.

Learn more

How we did it at Microsoft

• Read the official Employee Self-Service Agent product release announcement.
• Learn how we’re accelerating employee services at Microsoft with the Employee Self-Service Agent.
• View a series of Microsoft Learning Community videos about deploying the Employee Self-Service Agent.
• Explore the Microsoft Learn content related to the Employee Self-Service Agent.
• Discover how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.
• Explore our leaders’ guide to enterprise AI maturity in five steps.
• Watch a video from the Understanding Microsoft Agents series devoted to the Employee Self-Service Agent.

Try it out

• Learn more about how you can begin your own journey with the Employee Self-Service Agent.

We’d like to hear from you!

• Want more information? Email us and include a link to this story, and we’ll get back to you.

The post Deploying the Employee Self‑Service Agent: Our blueprint for enterprise‑scale success appeared first on Inside Track Blog.

In short, we’re all-in on agentic AI, and we want to help you get there, too.

“We’ve made a lot of progress deploying and driving adoption of Microsoft 365 Copilot since it was released, and we’re now doing the same when it comes to enabling our employees and our teams 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 sell to our customers. Those learnings give us a unique perspective and story to share with you about the journey we’ve been on with AI and agents.”

We have two collections of agentic AI content that we think will be useful to you.

“When it comes to agents, we’re still at the start. We expect to learn much more as we continue, lessons we’ll share here—stay connected and we’ll continue to share our story with you.” 

Brian Fielder, vice president, Microsoft Digital

The first set of stories documents our vision and strategy for agents. They walk you through our experience deploying agentic AI, our work to create tools that enable our employees to dive in, and, through smart governance, empower everyone at Microsoft to be confident and creative with how they use agents while keeping the company safe and secure.

Our second set of stories highlights some of the most interesting and effective agents that our employees, teams, and organizations have built. These stories will not only give you examples of agents that we’ve built, they show how you can go about building  similar agents for your organization based on the collective experience of our employees and teams at Microsoft.

“We hope you find reviewing the journey we’ve been on practical and useful,” Fielder says. “When it comes to agents, we’re still at the start. We expect to learn much more as we continue, lessons we’ll share here—stay connected and we’ll continue to share our story with you.”  

November 13, 2025

Alex Fleck

The agentic future: How we’re becoming an AI-first Frontier Firm at Microsoft

January 30, 2025

Keith Boyd

AI-powered agents in action: How we’re embracing this new ‘agentic’ moment at Microsoft

Deploying agentic AI at Microsoft

Alex Fleck

Riding the wave of agents washing over Microsoft with good governance

Agentic extensibility is expanding the frontier of enterprise AI. By creating agents that surface knowledge, take actions, and even reinvent workflows, people can personalize AI’s power like never before. But how do you move into the agentic future without putting your organization and employees at risk? How do you encourage citizen developers to create agents Read More

Agents we’ve deployed internally at Microsoft

November 13, 2025

David Hirning

Accelerating employee services at Microsoft with the Employee Self-Service Agent

Microsoft is a huge and complex organization, with more than 200,000 full-time employees working in hundreds of locations around the world. Engage with our experts! Customers or Microsoft account team representatives from Fortune 500 companies are welcome to request a virtual engagement on this topic with experts from our Microsoft Digital team. Previously, when our Read More

Key takeaways

We hope that you find our agentic AI stories useful. We wanted to share a mixture of our strategy and vision around enabling our employees to deploy agents, and to share stories that feature some of the most promising agents that our employees and teams have built and deployed.

We also understand that it can feel challenging to know where to start—it was for us. Here are some things we learned along the way that should help you:

• Governing agents is complex, and dependent on the overall AI maturity of your organization. Start slowly to build that maturity before unleashing too many new agents in your environment.
• A strong policy framework is the foundation. Lean on existing app governance policies, then layer agent-specific structures on top.
• Invest in data infrastructure and AI platforms. Building robust data infrastructure ensures your organization is prepared to leverage AI, and supports scalable, innovative, and secure AI-driven solutions.
• Develop a building environment strategy. Decide what scenarios match up with specific environments and make the right environments available to the relevant employees.
• Global regulations around categories like privacy, security, and responsibility provide a good baseline for establishing governance policies. Set relevant teams to work thinking through these regulations and incorporate their insights into your agent governance.
• Foster a culture of creativity and teamwork. Champion an AI-forward culture where innovation and collaboration drive the adoption of agentic AI.
• Develop AI expertise through training and development. As agentic AI transforms workflows and business outcomes across every industry, upskilling will empower your teams to navigate the rapid advances of AI, drive innovation, and ensure your organization stays competitive.
• Align AI initiatives with strategy. Ensuring AI initiatives align with business goals maximizes their impact and positions your organization to succeed in the rapidly evolving world of agentic AI.
• Implement ethical AI practices. You can use Microsoft’s Responsible AI principles as a guide. Adopting ethical AI practices builds trust, ensures responsible innovation, and prepares your organization to navigate the evolving landscape as AI becomes central to business operations and decision-making.

Try it out

• Get started with AI agents with Microsoft 365 Copilot, Azure AI Foundry, and Copilot Studio.

Related links

• Learn how to create and publish agents with Microsoft Copilot Studio.
• Find out how to create and deploy agents with Microsoft 365 Agents SDK.
• Check out these 12 lessons to get started building AI agents.

The post Powering agentic AI adoption at Microsoft: Our ‘Customer Zero’ story appeared first on Inside Track Blog.

Agents are specialized AI tools built to handle specific processes or solve business challenges. Within Microsoft Digital, the company’s IT organization, we’re responsible for unlocking their potential internally at Microsoft.

“This is a generational opportunity. The pace of change is only increasing, and we’re committed to experimenting, learning, and leading the way to the deeper possibilities that agentic AI represents.”

Brian Fielder, vice president, Microsoft Digital

As Customer Zero, we serve as the company’s first and best users of new technologies. It’s our role to confirm that they’re business-ready and establish best practices that others can follow.

We’re doing that by empowering our team here in Microsoft Digital to supercharge their work with AI agents. At the same time, we’re the custodians of the employee experience of employees at Microsoft, so we’re actively guiding deployment and adoption efforts for AI tools across the business.

“This is a generational opportunity,” says Brian Fielder, vice president of Microsoft Digital. “The pace of change is only increasing, and we’re committed to experimenting, learning, and leading the way to the deeper possibilities agents represent.”

By following our lead, you can chart your own course to the agentic future, where employees and agents work as teams to achieve more together.

Our vision for agents and the AI-first future of IT

A new organizational blueprint is emerging. It blends machine intelligence with human judgment to create systems that are AI-operated but human-led.

We call it becoming an AI-first Frontier Firm.

The path to the frontier is starting to reveal itself already. As organizations progress through different phases of AI maturity, they move from foundational Microsoft 365 Copilot capabilities through escalating levels of agentic complexity.

First, humans operate with an assistant like Copilot. Then, human-agent teams work together. But the future lies in humans leading teams of digital workers: AI agents that perform core labor with relative autonomy.

Becoming a Frontier Firm

Pattern 1

Human with assistant

Every employee has an AI assistant that helps them work better and faster

Pattern 2

Human-agent teams

Agents join teams as “digital colleagues,” taking on specific tasks at human direction

Pattern 3

Human-led, agent-operated

Humans set direction and agents execute business processes and workflows, checking in as needed

AI maturity starts at simple AI assistance, then progresses to more complex patterns between humans and agents.

This progression reflects the levels of agentic complexity represented by simple retrieval agents, then knowledge and action agents, and finally workflow reinvention through agents that can perform fully autonomous actions to complete end-to-end business processes. The human-led, agent-operated teams that will drive Frontier Firms forward depend on this advanced stage of agentic maturity.

As the tools used to build agents rapidly mature, we’ve observed that teams can experience these patterns simultaneously. In this rapidly changing environment, it makes sense to think of these as processes that can be targeted to specific business outcomes.

Soon, Frontier Firms will have employees experiencing each of these patterns daily, leveraging the best pattern to complete the task at optimal quality and in the least amount of time. Every business challenge or opportunity is unique, so it makes sense to choose the right tool for the job.  

At Microsoft, we’ve been unlocking opportunities throughout this Frontier Firm curve. At the simpler end of the spectrum, we’re empowering our employees to create their own custom retrieval agents and boosting enterprise knowledge sharing using simple SharePoint agents.

“AI agents are an entirely new kind of tool that presents possibilities we’re only beginning to realize. We capture that potential through a disciplined, rigorous, repeatable process of continuous improvement.”

Tom Heath, senior business program manager, Microsoft Digital

We’re also creating more complex agents that affect processes at the team, division, or even company-wide level. They include our autonomous Employee Self-Service Agent designed to enable modern support on key HR IT, and real estate issues, delivering operational excellence through AIOps, and supporting engineers as they manage complex network environments.

In our role as Customer Zero for the company’s agentic solutions, we in Microsoft Digital work closely with Microsoft’s product groups to ensure that our internal usage insights are helping to shape our products to make them more effective for our customers. This is something we do, so our customers don’t have to.

They also ensure we implement these new tools safely and effectively. That’s important, because AI isn’t without its challenges.

We need to minimize risk by using AI responsibly and securely according to our Responsible AI Principles. We need to assuage AI hesitancy among employees and equip them with the skills they need to succeed. Most importantly, we need to use intentional continuous improvement practices to ensure we apply AI’s potential to processes that drive genuine value.

“AI agents are an entirely new kind of tool that presents possibilities we’re only beginning to realize,” says Tom Heath, senior business program manager for Microsoft Digital.  “We capture that potential through a disciplined, rigorous, repeatable process of continuous improvement.”

The opportunities are worth the effort.

As a company, we surveyed leaders working at Frontier Firms. We found that they’re more likely to say their company is thriving, they’re able to take on more work, and they’re more optimistic about future opportunities than the global average.

All those benefits depend on moving toward agentic maturity.

Lessons learned deploying agents at Microsoft

As Customer Zero, our team within Microsoft Digital is already making progress on agent-based workflows, and the patterns and strategies we’re using can help you on your own journey. Like other digital investments, deploying agents depends on the critical pillars of governance, implementation, change management, measurement, and support.

Culture is also a crucial factor.

AI transformation is about unlocking human potential, not replacing it. So, meeting human needs while reaping the benefits of more intelligent tools is paramount.

Agents’ disruptive potential makes getting these elements right even more important.

Governance and AI-ready data

Our Microsoft 365 Copilot deployment acted as proving ground for governing AI and ensuring our data estate is ready for intelligent tools. We’ve applied our learnings from that experience to agents.

The first and most important lesson is ensuring you have a strong data hygiene foundation for employees to build and use agents. AI-ready data rests on five pillars: Unification, connection, quality and governance, accessibility to all, and the ability to accelerate time to value.

“Thanks to our early experiences with Copilot Studio, we’ve been able to develop gates and controls based on the type of agents that creators want to build.”

Aisha Hasan, Power Platform and Copilot Studio product manager, Microsoft Digital

Agents offer powerful opportunities to enhance employee productivity, but they also introduce risks. For example, how do we keep privileged information where it belongs? How do we keep employees from building agents that violate company policies? And how can we balance the freedom to create agents with the need to prevent sprawl?

Our response has been a matrixed approach to governing agents, where we apply policies and procedures based on an array of attributes.

Examples of agentic attributes that require different governance policies

Fortunately, we have tools—many of which we built ourselves—that are helping us keep the company safe as we navigate our agentic transformation. We’re using them to establish and manage our data, keep our confidential information confidential, and protect our data from unauthorized access, misuse, or disclosures. Microsoft Purview is our primary vehicle for handling data governance.

Finally, rules and a lifecycle for agents are helping us combat sprawl and the risks associated with ownership, access, and identity. The enterprise lifecycle is the model for this work, and attestation is essential for accountability. These structures also include an agent catalog to track these tools and help determine what kinds of AI agents our employees can “hire” as digital workers to help them get their work done.

Structuring your implementation

Implementing AI tools and agents is largely about who, what, and how. For us, it comes down to creating policies that manage which employees can use or create certain agents and how we permit those agents to work within the company.

Our matrixed approach to agent creation

To land on these policies, we considered what out-of-the-box agents in Microsoft 365 can accomplish, what employees in non-engineering roles can safely and easily create for themselves using no-code or low-code tools, and what agents demand the greater experience of AI developers using pro-code applications. Options include simple agents created in Microsoft SharePoint agent builder or Copilot Studio experience lite, then more complex tools like Microsoft Power Platform, Copilot Studio, Azure AI Foundry, and more—each governed, protected, and overseen by its own policies and procedures.

With these policies in place, implementing agents at scale depends on determining the best opportunities for value.

“Thanks to our early experiences with Copilot Studio, we’ve been able to develop gates and controls based on the type of agents that creators want to build,” says Aisha Hasan, Power Platform and Copilot Studio product manager for Microsoft Digital. “Through predetermined groups and rules, we can allow freedom and experimentation at different scales without putting our internal tenant at risk.”

At Microsoft, continuous improvement provides us with a mechanism for discovering which processes to optimize through agentic workflows, then implementing and tracking those changes. This framework helps us reimagine processes as deterministic state machines to enable digital colleagues that complete workflows on employees’ behalf.

Driving adoption through change management

Change doesn’t happen automatically, especially when a new technology fundamentally alters ways of working. At Microsoft, the message is clear: Regardless of your role, there’s an agent for every task.

We have a global change team operating according to Prosci’s ADKAR model combined with the Microsoft 365 Adoption Guide. At the same time, we recognize that there is no one-size-fits-all adoption campaign, so we take efforts to tailor adoption to specific regions and internal organizations.

We’ve taken a multi-pronged approach to adoption, communications, community, and skilling that relies heavily on Microsoft Viva. Communications center on raising awareness, driving engagement, and encouraging feedback while tracking adoption.

Each Microsoft Viva app has a role to play, but Viva Engage has been the most impactful. It provides opportunities for organic connections that enhance employees’ knowledge and ability while providing opportunities to share successes and inspiration.

Adoption communications focus both on encouraging usage of ready-made agents and encouraging employees to create their own using the right tools for their level of technical capability. Campaigns include an ongoing “Agent of the month” series, spotlighting experimental agent releases, how-to content for agent builders, and promotional efforts for enterprise agents that occupy central places in business processes.

The Analyst and Researcher agents built into Copilot are ideal ways to introduce your employees to the power of agents, and “Agent Mode” in Word and Excel can make agentic workflows more intuitive through integration into the tools your employees are already using every day.

• Analyst uses chain-of-thought reasoning like a skilled data scientist to progress through problems iteratively, taking as many steps as necessary to refine its reasoning and provide a high-quality answer.
• Researcher helps employees tackle multi-step research at work—delivering insights with greater quality and accuracy than previously possible. It combines OpenAI’s deep research model with Microsoft 365 Copilot’s advanced orchestration and deep search capabilities.
• Agent Mode in Microsoft Word and Excel transforms how users create documents or spreadsheets by enabling a more interactive and collaborative experience with AI. Instead of just generating responses to single prompts, Agent Mode allows users to engage in a multi-step process where they can guide the AI through various tasks, making document creation or data analysis more intuitive and efficient.

Building the AI habit takes time, but encouraging usage of these pre-built AI agents is the perfect way to accelerate your journey to the frontier.

At every stage of our AI transformation so far, we’ve experienced the power of peer-led adoption efforts.

Our Copilot Champs Community, a team of AI enthusiasts, early adopters, and eager learners, has been incredibly effective both at providing examples of AI usage and supporting change management initiatives run by our Microsoft Digital organization.

Camp Copilot represented our first runaway success in grassroots, peer-led AI skilling. This three-week learning event gave our Copilot Champs an opportunity to showcase emerging best practices in a structured, gamified setting and reached thousands of employees. We’ve recently followed that with a Copilot Expo, which expanded on Camp Copilot with more learning around agents and a templatized format we deployed to different regions and divisions.

As we shift our focus from Copilot adoption to agentic innovation, we’re also evolving our community strategy.

Our Copilot Champs Community is still a vital source of leadership and guidance, but now we’ve augmented its role with the Builders Community, a new group tailored to sharing knowledge and inspiration around creating agents.

It’s also important to have mechanisms in place that guide employees as our company’s agentic maturity increases.

We are accelerating innovation through agent and automation templates that employees and teams are applying to their own scenarios. On top of those resources, our AI Center of Excellence and a dedicated continuous improvement function are helping our teams think through their opportunities, ensure they capture value, and maintain security.

Measuring impact to demonstrate value

Measuring the impact of AI tools has been a unique challenge, and we’re only at the beginning of our journey. That’s especially true for agents.

The Experience Insights dashboard for Microsoft 365 admin center helps our technology decision makers gather information about product usage, feedback, and employee views of help articles. Crucially, this tool allows people outside of our IT apparatus to gain limited, compliant access to adoption data, which supports more effective change management efforts within their scope.

We’ve also devised several measurement areas and key metrics we can track using the Microsoft Digital AI Value Framework. They include:

• Revenue impact: Direct contributions to revenue generation and business growth.
• Productivity and efficiency: Efficiency gains while completing tasks and processes without a reduction in quality.
• Security and risk management: Improvements in identifying, preventing, and managing security vulnerabilities and risks.
• Employee and customer experience: The impact of AI initiatives on employee satisfaction, engagement, and productivity.
• Quality improvement: Enhancements in the quality of deliverables, services, and processes.
• Cost savings: Reduction in operational costs and resource allocation efficiencies.

As our company has dedicated more attention and resources to an AI and continuous improvement framework, these value drivers have become guiding lights for ideating and executing AI initiatives—and most importantly, tracking them. Methodologies like Bowler scorecards and monthly operating reviews align perfectly with our learn-it-all culture to help us measure and adjust AI projects to align them with our business goals more effectively.

Enabling effective support for agents

When you enter an unprecedented new phase of technology, anticipating the support employees need can be difficult. Our role as Customer Zero has been essential for making sure we have enough experience to properly understand the issues that arise from implementing agents.

Our employees in Microsoft Digital have been some of the company’s first movers on agentic AI initiatives. Through our initial experience, we’ve gradually built up our knowledge and widened access to equip support professionals with everything they need to enable employees.

Within Microsoft Digital, we established a solid support base by progressing through seven steps:

1. Preliminary access: We selected our initial support specialists, including people with different Microsoft 365 app focuses, support tiers, and service audiences.
2. Communication hub: We created a community space where our support team could connect and collaborate on issues and invited non-support professionals as needed.
3. Knowledge base: We created a collaborative document where we added learnings, which eventually evolved into our knowledge base for internal support.
4. Widening access: We hosted information sessions with the wider support team and extended access so all relevant support professionals could ramp up.
5. Rehearsal: Role-playing and shadowing sessions helped teams build practical knowledge and confidence.
6. Go-live support: We prepared our support resources and processes and pushed them live in advance of our deployment.
7. Tracking: A pre-determined tracking cadence for gathering data on incidents helps support teams identify trending issues and tickets.

Pushing the frontier forward with agentic AI

It’s clear that agents will be the major driving force behind modern workflows. The AI-first Frontier Firm will be the defining blueprint of this next era.

“The future of IT is increasingly about experimentation and adaptation to accelerating AI technologies. We take our role as Customer Zero seriously, and that means boldly experimenting with agentic AI and leading this next transformation for our company and our customers.”

Brian Fielder, vice president, Microsoft Digital

Knowing the future that awaits, our Microsoft Digital team will continue to explore, experiment, and share what we’ve learned. We want to discover pathways to greater human potential, powered by AI agents.

“The future of IT is increasingly about experimentation and adaptation to accelerating AI technologies,” Fielder says. “We take our role as Customer Zero seriously, and that means boldly experimenting with agentic AI and leading this next transformation for our company and our customers.”

Key takeaways

The lessons we’ve learned throughout our unfolding agentic AI transformation can help you start your own journey:

• Build a solid foundation for governance: Take stock of your data hygiene and ensure your general governance policies are sufficiently robust before deploying agents widely.
• Consider the who, what, and how: Think carefully about how to structure agent creation across different toolsets, levels of complexity, sharing options, and more.
• Find and engage your peer leaders: Create a community tailored to agent exploration and peer-led adoption support and promote their work among your employees.
• Use a multi-pronged adoption strategy: A good strategy will include a mix of centralized communications, peer-driven leadership, learning events, and asynchronous opportunities. Don’t forget measurement and opportunities for feedback.
• Determine your metrics for success: Identify the impact you want to drive with agents, isolate them into primary value drivers, and cascade those down into key metrics.
• Build toward successful support: Use your technical team’s experience during pilots and early implementation to build a base for effective support material.

Try it out

Learn more about our journey with agentic AI.

Related links

• Learn how we’re Customer Zero for Microsoft and it’s AI products.
• See how we’re building an AI-powered continuous improvement culture at Microsoft.
• Get a look inside the councils steering AI projects at Microsoft.
• Learn how we answer the key question: Should I use Copilot Studio or Azure AI Foundry to build my agent?
• Check out what we learned using a virtual skilling event to drive Microsoft 365 Copilot adoption.
• Walk through our guide for deploying Microsoft 365 Copilot.
• Find out how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post The agentic future: How we’re becoming an AI-first Frontier Firm at Microsoft appeared first on Inside Track Blog.

Previously, when our employees had a question or a problem—whether it be a technical issue, an HR query, or just wanting to know what’s for lunch—they had to navigate through a variety of different apps, tools, and SharePoint sites to find the answer or get help with their task.

It was a time-consuming and frustrating experience. But the advent of generative AI has given us a new opportunity.

Microsoft 365 Copilot and the power of agentic AI have created a world where people simply type in questions or requests to get prompt and helpful assistance. Now we’re applying the capabilities of Copilot and agentic technology to the ongoing challenge of employee assistance.

“At Microsoft, our mission is to transform the employee experience with AI solutions that provide personalized and seamless interactions for our employees throughout the workday. What we’ve created with the Employee Self-Service Agent is a powerful example of a solution doing just that.”

Nathalie D’Hers, corporate vice president, Employee Experience

The result is the new Employee Self-Service Agent, a “one-stop shop” providing vetted and personalized solutions to our workers across a range of high-demand topics and tasks, including human resources (HR), IT support, and facilities and real estate.

The agent combines the help functions for human resources, IT support, and facilities and real estate into one tool, allowing our employees to handle a range of tasks, such as requesting parental leave, resolving a problem with their device, or getting something fixed in their office. The Employee Self-Service Agent is available to all Microsoft employees worldwide and is also now available to customers.

“At Microsoft, our mission is to transform the employee experience with AI solutions that provide personalized and seamless interactions for our employees throughout the workday,” says Nathalie D’Hers, corporate vice president of Employee Experience. “What we’ve created with the Employee Self-Service Agent is a powerful example of a solution doing just that.”

The power of a ‘single pane of glass’

The essential premise of the Employee Self-Service Agent is that it serves as the one place for Microsoft employees to go when they need assistance. This means that they don’t have to remember what tool or website offers the best way to handle their question or task—it’s all available in one seamless, AI-powered interface.

“With this agent, we wanted a ‘single pane of glass’ for our employees and managers,” says Rajamma Krishnamurthy, principal PM architect manager for Employee Experience in Microsoft HR. “The idea is that they can come in and get all their questions answered, rather than have to go to multiple tools or URLs in different areas.”

Employee-Self Service screenshot

The workflow is simple—launch Microsoft 365 Copilot, select “Employee Self-Service,” and type in your query. The agent then orchestrates an authoritative response and/or offers a form that can be used to carry out the desired action (auto-populating the form with details from the chat where possible).

“Many support tools that could benefit employees go unused because of limited awareness and the friction involved in completing tasks. This tool gives employees a new way to access that helpful information.”

Prerna Ajmera, general manager, HR digital strategy and innovation

If the question or task can’t be resolved by the agent, it hands the employee off to the appropriate tool, subagent, or support person.

The Employee Self-Service Agent is driving usage of support tools that our employees often overlook.

“Many support tools that could benefit employees go unused because of limited awareness and the friction involved in completing tasks,” says Prerna Ajmera, general manager for HR digital strategy and innovation. “This tool gives employees a new way to access that helpful information.”

An early focus on HR and IT Support

In developing the Employee Self-Service Agent, we initially identified two main categories of employee assistance to focus on: HR and technical support. These are areas that generate millions of internal queries and support cases (help tickets) from our employees every year, which means the potential for a significant return on investment (ROI). (We subsequently added real estate and facilities later in the process.)

In the case of human resources, this meant looking at all the HR experiences that employees need help with and figuring out what could be handled with AI. Whether it was a question or task related to personal time off (PTO), performance, compensation, learning, internal job listings, well-being, or something else, we needed to make sure that the information the agent returned was relevant and helpful to that employee.

This is what distinguishes the Employee Self-Service Agent from Microsoft 365 Copilot Chat, which provides a more general answer that may not apply to that particular worker’s situation, and can’t access all relevant information about that employee.

“When it comes to HR, you need to make sure the answers are coming from authoritative sources, because HR is a very sensitive and vital part of how a company runs.”

Rajamma Krishnamurthy, principal PM architect manager, Employee Experience, Microsoft HR

With Copilot, you might ask for an overview of everything to do with a given project. But when it comes to employee-assistance topics, casting a wide net is not the desired outcome. An employee doesn’t want to hear about HR policies in India when they work in the U.S., or to get Mac-focused tech help when they use a PC. The needs of each of our employees are different, and so we built the agent to reflect that.

A major task in developing the agent was making sure that all the content that it draws from is accurate and up to date. This was especially important for HR-related responses, which sometimes deal with sensitive topics. We’ve carefully thought through privacy and security issues, are following our company Responsible AI principles, and making sure the agent adheres to regulations for each country or region.

“When it comes to HR, you need to make sure the answers are coming from authoritative sources, because HR is a very sensitive and vital part of how a company runs,” Krishnamurthy says. “Our new agent was built so that only vetted sources are responding to these questions.”

One advantage of the Employee Self-Service Agent is its ability to provide real-time assistance. Rather than having to file a ticket and then wait 24 to 48 hours for a response, the employee can get on-demand help and hopefully resolve their problem without waiting. 

“Previously, resolving an HR help request could take a couple of days,” Ajmera says. “These delays often came from the back-and-forth of traditional support channels—‘OK, you told me this; now, what’s the policy for that? What’s next?’ With the agent, employees can get answers in minutes. That’s the beauty of it.”

“The agent’s content is specifically grounded in our authoritative IT service sources, and it also knows relevant details about you as a user. All of this context makes it better at guiding employees to solve their own support issues.”

Trent Berghofer, general manager, Microsoft Digital Modern Support

Agentic assistance to accomplish more

Another differentiator from previous employee assistance tools is that the Employee Self-Service Agent enables task completion, not just information retrieval.

For example, consider technical support (such as dealing with an audio issue on an employee’s device). Our workers are now able to get detailed, contextual, and specific help with their technical issues, helping them solve the issue without having to engage with assisted support and get a ticket created.

An agentic solution for employee assistance

Retrieve

The agent retrieves information from authoritative sources and delivers responses based on contextual data about the employee.

Take action

The agent helps the employee take action right from the chat and avoid having to navigate multiple tools and workspaces.

Extend

The agent is designed to be flexible and customizable, based on the organization’s existing software workflows and third-party solutions.

The Employee Self-Service Agent retrieves authoritative information with natural-language queries and enables users to take action from within the chat.

“The agent’s content is specifically grounded in our authoritative IT service sources, and it also knows about you as a user—that you have this particular device, and the compliance state of that device, and what country you’re located in,” says Trent Berghofer, general manager of the Microsoft Digital Modern Support team. “All of this context makes it better at guiding the employee to solve their own problem, versus doing a generic search on the issue.”

If the employee does have to connect to live support via phone or chat, the technician will have access to their conversation with the agent. This way, the support professional can view details the user has already provided and the solutions that have already been tried. This saves time and decreases frustration.

Task completion is a primary gauge of return on investment (ROI) for the Employee Self-Service Agent. The overall goal across all help categories is for the agent to result in at least 40% fewer support tickets.

Each ticket represents a significant cost to any organization, and those costs add up, especially at large companies. With more than 2 million IT support interactions (via Virtual Agent, chat, and phone) across Microsoft annually, we project that the Self-Service Agent will produce substantial savings in tech support alone.

HR is another area where we hope to generate impact, as employees meet their needs with the Employee Self-Service Agent. Our specific goals include:

• Reduce monthly HR tickets by 44% by mid-2026 through expanded self-service capabilities
• Save employee time with rapid, frictionless fulfillment of requests 
• Boost overall discovery and use of HR programs to deliver increased ROI
• Increase business agility and reduce end-to-end process time

“Once it’s fully adopted, we’re expecting the agent to manage somewhere between 400,000 and 600,000 employee interactions a year that used to result in an HR support ticket,” Ajmera says. “That’s a significant shift and learning curve for our organization, in terms of how employees get help. Scaling the agent up to have this major business impact has been one of the biggest challenges for us.”

Saving time with AI support

Employee time savings is another significant driver of ROI. This is a key part of the third vertical we’ve targeted with the Employee Self-Service Agent—real estate and facilities.

“Before we had the Employee Self-Service Agent, the employee-assistance experience was kind of fragmented across mobile, websites, and physical kiosks. The new agent unifies all of these experiences and puts them in the same place.”

Becky West, principal group product manager, Microsoft Digital

With hundreds of office buildings around the world, including dozens of cafés and other specialized sites, Microsoft must handle a constant stream of employee inquiries and activities related to real estate and facilities. These include things like:

• Transportation – calling a shuttle for a ride between buildings
• Dining – learning where your favorite dish is being served (and ordering it to go)
• Booking a room – locating a space to relax or connect with colleagues
• Lobby and visitor services – registering a campus guest
• Facilities tickets – getting help with a repair or other building issue
• Parking registration – recording where your car is parked
• Maps – finding your way around a building or a campus

“Before we had the Employee Self-Service Agent, the employee-assistance experience was kind of fragmented across mobile, websites, and physical kiosks,” says Becky West, principal group product manager in Microsoft Digital. “The new agent unifies all of these experiences and puts them in the same place. Now our employees can ask questions in natural language, and it guides them through whatever campus experience they need to do—invite a guest, find dining options, create a ticket, etc.”

The number of working hours currently spent by our employees trying to find the answer to their facilities-related question or filling out a form to complete a task is difficult to quantify precisely across such a large organization. But consider just one common exercise: registering a visitor at a Microsoft building.

According to Digital Workplace Services data, in 2024 there were 2 million registered visitors at Microsoft buildings worldwide, with roughly 1.2 million of these considered business-related.

Previously, employees had to email or talk to lobby hosts (front-desk staff) to invite guests to Microsoft; the host would then enter the guest details into the Guest Management System.

Now, the Employee Self-Service Agent provides a simple form within the chat, asking for details like guest name, email, purpose (business or personal), building number, and date. Once the form is submitted, the system generates a confirmation and sends a QR code directly to the guest via email. That alone has the potential to save us 50,000 hours of employee time per year.

“One benefit of this is that anything you can do with Copilot Studio in terms of a custom engine agent, you can do in the Employee Self-Service Agent. Our product documentation goes into detail on how to configure it based on your particular needs.”

Kyle von Haden, principal group product manager, Microsoft 365 Copilot product group

Another great example is a common facilities request, like replacing a light bulb, reporting broken furniture, or workspaces that require cleaning. Instead of having to figure out which tool to use to report the issue and then filling out a request, the individual can go straight to the Employee Self-Service Agent and upload a photo.

“The agent detects the problem based on the image, fills in details, and enables the user to file their service request right from the chat,” West says.

Customizable and extensible

The Employee Self-Service Agent was built with Microsoft Copilot Studio, a tool that enables users to create and extend AI agents. The product is intentionally designed so that our customers can customize it to fit their own business needs using preconfigured workflows and accelerator packs that come with the agent.

“One benefit of this is that anything you can do with Copilot Studio in terms of a custom engine agent, you can do in the Employee Self-Service Agent,” says Kyle von Haden, a principal group product manager for the Microsoft 365 Copilot product group. “Our product documentation goes into detail on how to configure it based on your particular needs. We’re even including code samples that show you how to extend the agent further than what you get right out of the box.”

For instance, many of our customers rely on third-party solution providers such as Workday, SAP, or ServiceNow. So, our development process included producing connectors for some of these third-party offerings, making it easier for customers to integrate the Employee Self-Service Agent into their existing workflows.

This extensibility is an advantage of adopting the Employee Self-Service Agent, according to von Haden.

“The beauty of this product is that it comes with all these accelerators that help customers jumpstart their ability to deliver AI-driven employee assistance, because there’s no inherent limitations,” he says. “They have all the same flexibility they’d get by building a solution from scratch, but they get to build on this Copilot Studio foundation that offers powerful capabilities and will continue to grow as we invest more in it.”

The role of Customer Zero

With a new product like the Employee Self-Service Agent, having Microsoft employees use it as part of their everyday work and then provide detailed feedback was a valuable aspect of the development process. This is the essence of the company’s commitment as Customer Zero.

“For the Employee Self-Service Agent, the role of our internal users as Customer Zero has been incredibly important—in this case, doubly so,” says Kirk Gregersen, corporate vice president of product for Microsoft Viva and Microsoft 365 Copilot Experiences. “Because not only are we learning how to deploy the product in a real, complex environment, but we’re doing it in a world that’s completely new, given all of the changing variables around AI.”

To that end, we began rolling the agent out to employees more than a year ago in a geographically phased approach—first to the United Kingdom and Canada, then India, then to the United States and the rest of the world. Regular communications to employees—via email, Microsoft Viva, and other channels—raised awareness and encouraged use of the agent. And a sophisticated plan for listening and gathering product telemetry was implemented, so that all feedback could be captured and routed back to the product team.

This process was particularly important for building stakeholder trust in the tool. For example, our HR professionals worked closely with the product group to make sure the answers produced by the Employee Self-Service Agent met their high bar for accuracy and reliability.

“Engaging our stakeholders early was key,” Ajmera says. “We iterated with them as they went through the various prompts and responses manually and rated them for accuracy. We learned a lot. It’s still a work in progress, but we’ve gotten to the point where the agent is able to automatically generate responses that meet stakeholder expectations.”

“This product is very significant for us, both from the user perspective and the cost-savings angle. We can get the right answers to and solve issues for our employees faster, which increases their satisfaction and helps them be more effective.”

Kirk Gregersen, corporate vice president, Microsoft Viva and Microsoft 365 Copilot Experiences

This “virtuous flywheel” development process played a role in making the Employee Self-Service Agent better and preparing it for general release, as a feature available to all Microsoft 365 enterprise customers with a Copilot license. That release is expected soon.

Because the agent is built on Microsoft Copilot Studio, it gives us flexibility to adapt and grow as needed. We plan to eventually expand the Employee Self-Service Agent to other key areas across the company, like finance, legal, and more—to become a true single-pane-of-glass portal for all our employees’ needs.

In the end, the agent offers the potential to deliver the kind of impact that only truly breakthrough business software can: delighted users and major ROI.

“This product is very significant for us, both from the user perspective and the cost-savings angle,” Gregersen says. “We can get the right answers to and solve issues for our employees faster, which increases their satisfaction and helps them be more effective. And the solution scales up to real cost savings for the organization.”

Key takeaways

Here are some things to consider when tackling employee assistance at your organization:

• Approach it from the user perspective. Offering a “single pane of glass” portal from which an employee can access help on a wide variety of topics may present some technical challenges, but it meets users where they are and resolves their pain points.
• Start with high-demand categories. We launched our Employee Self-Service Agent journey with two core verticals that offer potential for ROI: HR and IT support. We then added facilities and real estate, in part because the high usage rates (such as for dining and transportation) would drive greater employee awareness and boost user-session numbers.
• Think about task completion. Employees need to not only access authoritative information, they also want the ability to accomplish their goal right from the agent interface. If their issue can’t be handled by the agent, it should be able to make a smooth handoff to the tool that can.
• Spend time up front on data governance. An employee-assistance agent must supply clear, current, and accurate information that is highly relevant to that user. Vague, inaccurate, or irrelevant answers can damage product credibility with your employees.
• Customizable rather than a turnkey solution. It’s important to note that the Employee Self-Service Agent is a flexible template built on top of Copilot Studio; it requires customization by your organization in terms of implementation, categorization, data selection, third-party integration, privacy, legal considerations, and other factors.
• Make sure to collect feedback and iterate. Generative AI tools are still new, and your help solutions can be improved by listening to your employees and acting on what they tell you about their experience.

Try it out

Learn more about the Employee Self-Service Agent.

Related links

• Learn more about our strategic approach to agentic AI internally at Microsoft.
• Find out how we’re transforming the way our employees get help on campus with the Employee Self-Service Agent.
• Read how the Employee Self-Service Agent is helping Puget Sound-based Microsoft employees with their transportation needs.
• Explore how Microsoft HR is using Viva and Copilot to empower our employees.
• Learn how we’re enabling modern support at Microsoft with AI.
• Discover our five-step guide that helps IT leaders get to enterprise AI maturity.

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