As AI reshapes how we work and live, it brings with it both transformative potential and complex challenges. Across the industry, concerns about bias, safety, and transparency are growing.

At Microsoft, we believe that realizing AI’s benefits requires a shared commitment to responsibility—one we take seriously. As a result, we aren’t just creating AI solutions. We’re taking the lead on infusing responsible AI principles into our technology and organizational practices.

Prioritizing responsible AI across Microsoft

The most impressive AI-powered capabilities in the world mean nothing if people don’t trust the technology. Microsoft and many of our customers across all industries are working to strike the right balance between innovation and responsibility.

“We’re on a multi-year journey born out of the need to support innovation—and do it in a way that builds trust. Along the way, we’ve continued to iterate and evolve the program through a series of building blocks.”

Mike Jackson, head of AI Governance, Enablement, and Legal, Microsoft Office of Responsible AI

IT leaders and CXOs aren’t just deploying AI tools. They’re also thinking of the right guardrails to implement around those tools as their organizations mature. Meanwhile, developers and deployers want to be sure they’re building and implementing AI solutions within the bounds of responsibility.

As an organization that’s mapping the frontier of AI while creating business-ready tools for our customers, Microsoft is shaping the global conversation on responsible AI. We don’t only accomplish that through policy and governance, but also by embedding responsibility into the ways we build, deploy, and scale AI.

Laying the foundation for this work is the duty of our Office of Responsible AI (ORA). This team brings policy and governance expertise to the responsible AI ecosystem at Microsoft.

“We’re on a multi-year journey born out of the need to support innovation—and do it in a way that builds trust,” says Mike Jackson, head of AI Governance, Enablement, and Legal for the Office of Responsible AI. “Along the way, we’ve continued to iterate and evolve the program through a series of building blocks.”

ORA advances AI development, deployment, and secure and trustworthy innovation through governance, legal expertise, internal practice, public policy, and guidance on sensitive uses and emerging technology. The team focuses on empowering innovation while ensuring it falls within Microsoft’s governance, compliance, and policy guardrails.

ORA also partners closely with product and engineering teams as well as other trust domains like privacy, digital safety, security, and accessibility. The team created our Microsoft Responsible AI Standard, the cornerstone of our governance framework, and ensures internal AI initiatives align with it.

The Responsible AI Standard translates our six principles into actionable requirements for every AI project across Microsoft:

ORA reports into the Microsoft Board of Directors and collaborates with stakeholders and teams across the company to operationalize these principles, implementing policies and practices that apply to AI applications. They determined that every AI initiative should undergo an impact assessment to ensure it aligns with the standard.

If ORA is our compass for responsible AI, our companywide Responsible AI Council has its hands on the steering wheel.

The council, led by Chief Technology Officer Kevin Scott and Vice Chair and President Brad Smith, was formed at the senior leadership level as a forum and source of representation across research, policy, and engineering. It provides leadership, strategic guidance, and executive support and sponsorship to advance strategic objectives around innovation and responsible AI.

“ORA has established clear principles and a step-by-step assessment framework and tool. Our responsibility is to rigorously follow this process and ensure compliance across our products and initiatives.”

Naval Tripathi, principal engineering manager and co-lead, Microsoft Digital Responsible AI team

Under the council’s guidance, responsible AI CVPs, division leaders, and a network of responsible AI champions across the company operationalize the implementation of our Responsible AI Standard and compliance with our policies.

The structure of these teams is straightforward.

Every division has a designated CVP and division lead to steer the work and connect their team to the overarching Responsible AI Council. Within those divisions, each organization has a lead responsible AI champion or a set of co-leads to steer their team of champions. Those champions act as subject matter experts, reviewers for the impact assessment process, and points of contact for the teams developing AI initiatives.

Implementing AI governance within Microsoft IT

As members of the company’s IT organization, Microsoft Digital’s responsible AI division lead and champion team have a special role to play. They helped develop a critical internal workflow tool, which has now become a mandatory part of our responsible AI assessment process.

“The key is to ensure full alignment of responsible AI practices with ORA,” says Naval Tripathi, principal engineering manager and co-lead for Microsoft Digital’s Responsible AI Team. “ORA has established clear principles and a step-by-step assessment framework and tool. Our responsibility is to rigorously follow this process and ensure compliance across our products and initiatives.”

This tool logs every project, guides AI developers through initial impact assessments all the way to final reviews, and facilitates those workflows for champions.

“As organizations develop a diverse ecosystem of AI agents, often created by multiple engineering teams, it becomes essential to establish a standardized evaluation process. This ensures every agent adheres to enterprise-level standards before we deploy and distribute it to end users.”

Thomas Po, senior product manager, Microsoft Digital

By streamlining the process through a unified portal, the tool increases efficiency and minimizes errors that can arise from manual processes. It also encourages teams to make responsible AI part of the software development lifecycle (SDL) itself, not a hurdle or an afterthought.

“As organizations develop a diverse ecosystem of AI agents, often created by multiple engineering teams, it becomes essential to establish a standardized evaluation process,” says Thomas Po, a senior product manager working on Campus Services agents. “This ensures every agent adheres to enterprise-level standards before we deploy and distribute it to end users. That makes it more manageable in the long term, and having it all in one tool gives us more transparency.”

Our unified internal workflow looks like this:

• Project initiation and system registration: During the design phase for an AI initiative, the engineering team accesses the portal and registers a new AI system. From there, they fill out fields with crucial information, including a title, description, the developer team’s division, whether the project will include internal or external resources, the relevant champion who should review their initiative, and other details. Within this initial form, different scenarios will trigger different review parameters and requirements, for example, when a team intends to publish a tool externally or engage with sensitive use cases.
• Release assessment: After the system registration is complete, the team initiates the release assessment, a much more thorough review designed to ensure the AI-powered solution is ready to go live. At this point, the engineering team needs to provide detailed documentation. That includes the volume and kinds of data the system will use, potential harms and mitigations, and more. A release assessment includes experts in our Office of Responsible AI, Security, Privacy, and other teams, who review sensitive use cases or initiatives that include generative AI.

If the project clears all the requirements and reviews, it’s ready to go live. Crucially, we don’t think of these stages as a set of hurdles teams need to clear to complete their projects. Instead, the process guides engineering teams through the design elements they need to consider and provides opportunities for feedback from subject matter experts.

“The tool captures all the requirements from ORA and incorporates them into a developer-friendly workflow,” says Padmanabha Reddy Madhu, principal software engineer and responsible AI champion for Employee Productivity Engineering in Microsoft Digital. “It’s also a great way to pull AI champions into the design phase so we can support our colleagues’ work.”

With more than 80 AI projects currently underway across Microsoft Digital, logging and streamlining are essential. Teams are working on all kinds of ways to boost enterprise processes and employee experiences, like the following examples from Campus Services that users can access through our Employee Self-Service Agent:

• A facilities agent helps employees take action when they discover an issue at one of our buildings, like a burnt-out light, a spill, or physical damage. The agent creates a ticket to alert a Facilities team so they can resolve it and allows the submitter to follow up on progress.
• A campus event agent makes onsite gatherings like talks and Microsoft Garage build-a-thons more discoverable through simple queries. Using this agent, employees can more easily discover and plan around events that interest them, adding value to the in-person experience and incentivizing community.
• A dining agent addresses the challenges of multiple on-campus restaurants featuring menu options that shift daily. Employees can use natural language queries like “Where can I get teriyaki today?” The agent does the rest. This kind of agent can be especially helpful for employees with allergies or dietary restrictions, providing a boost to accessibility for the on-campus dining experience.

“AI is rapidly becoming a standard part of how we build and operate. As adoption accelerates, Responsible AI becomes imperative and enables teams to innovate at speed while maintaining safety and accountability at scale.”

Qingsu Wu, principal group product manager, Microsoft Digital

Our policies and practices have embedded a culture of responsibility and trust into our internal AI development processes. With that trust comes the confidence to experiment.

“AI is rapidly becoming a standard part of how we build and operate,” says Qingsu Wu, principal group product manager in Microsoft Digital. “As adoption accelerates, Responsible AI becomes imperative and enables teams to innovate at speed while maintaining safety and accountability at scale. By embedding Responsible AI into our engineering practices, teams have the clarity and confidence they need to manage risk proactively and deliver value without compromising safety or trust.”

Far from thinking of responsible AI assessments as an administrative or policy burden that creates additional work, teams now recognize their benefits. They look at the process as an extra set of eyes from a trusted partner. By minimizing legal and compliance risks through our Responsible AI Council’s expertise, our teams save time and stress, and we avoid problems like delayed releases or rollbacks.

“What we’re doing is entirely novel in the tech world. Microsoft is really the lead learner here, and we have a passion for corporate citizenship that we’re embedding in our tools.”

Jamian Smith, principal product manager and co-lead, Microsoft Digital Responsible AI team, Microsoft Digital

Lessons learned: Embedding responsible AI into our development efforts

Throughout this process, we’ve learned lessons that will be helpful for other organizations just beginning their AI journeys:

• We empowered early adopters and enthusiasts as responsible AI champions. They act as anchors and resources for developers who use AI, so we made sure they had the knowledge and training they needed to unlock downstream value.
• Culture has been crucial to our success, especially our growth mindset and our focus on trust. Emphasizing these aspects of our company culture helped us embed responsible AI into core SDL processes and naturalize it on our engineering teams.
• Processes are one thing, and tooling is another. If your responsible AI assessment workflow isn’t attuned to your needs, simply building a review portal tool won’t get you the rest of the way. First, we thought about the process we needed to put in place to solidify responsible AI practices and support our teams’ work. Then we built a tool that supports those workflows as easily and seamlessly as possible.
• Accuracy is reliant on data, and data has a tendency to reflect the biases of the humans who organize it. It’s necessary to correct bias actively through introspection and testing.

“What we’re doing is entirely novel in the tech world,” says Jamian Smith, principal product manager and co-lead for Microsoft Digital’s Responsible AI team. “Microsoft is really the lead learner here, and we have a passion for corporate citizenship that we’re embedding in our tools.”

As your organization begins to experiment with its own AI projects, take these concrete steps to infuse responsibility into the solutions you create:

1. Establish a strong foundation based on core principles and standards that align with your organizational culture. The Microsoft Responsible AI Standard is a great place to start because it reflects our experience and the expertise we’ve built as AI technology leaders and providers.
2. Seek out the activators across your organization: people with a passion for AI, security, transparency, and other challenge areas, along with a willingness to learn and the ability to lead. Think about how to place them in both centralized and distributed positions.
3. With the rapidly evolving regulatory climate around AI, it’s crucial to have a broad understanding of compliance and continue to follow its developments. Involve dedicated regulatory, compliance, and legal professionals in researching and monitoring global standards while communicating that information to your organization, particularly through training and updates that help teams adapt new regulations into their core processes.
4. Create a process for responsible AI assessment. Consider ways to break it into stages that propel projects forward rather than hindering them. Enlist the right people to assess projects, and consider tooling that streamlines actions for both creators and assessors. Our AI Impact Assessment Guide can help you get started.
5. Benefit from pioneers in the space, including our experts at Microsoft. Our journey has produced ready-to-use resources that can accelerate your progress. Examples include our Responsible AI Toolbox for GitHub, hands-on tools for building effective human-AI experiences, and our AI Impact Assessment Template.

“It’s not about how fast you can move, but how prepared you are. Responsible AI processes might seem like speed bumps, but ultimately they’re accelerators.”

Naval Tripathi, principal engineering manager and co-lead, Microsoft Digital Responsible AI Team

Building your capacity to create AI tools responsibly won’t happen without careful planning and strategy. As part of that process, embed responsible AI into your development workflows by emulating the practices we’ve pioneered at Microsoft.

“It’s not about how fast you can move, but how prepared you are,” Tripathi says. “Responsible AI processes might seem like speed bumps, but ultimately they’re accelerators.”

By prioritizing responsible AI, businesses of all kinds, all over the world, can ensure that the AI revolution is a truly human movement.

Key takeaways

These insights can help you as you begin your own journey through responsible AI:

• Realize that this isn’t just a technical transition. It’s also a gradual evolution and an ongoing journey.
• Work with people across your organization to establish goals and standards, because different disciplines bring different expertise and insights to the table. This will also align your responsible AI standards with your organizational values.
• Start with the basics and build from there. Establish principles, create processes, and construct tooling around those structures.
• A wide array of tooling is readily available in the world of AI. Seek out providers that model responsible values.
• Lean on your existing experts across privacy, security, accountability, and compliance. Their skills will be crucial in this new technological landscape.
• Conducting your own responsible AI groundwork is crucial, but you can also partner with Microsoft. We run on trust, and we’ve thought about these issues to pave the way for your success. Follow our lead, consider the best ways to adapt our lessons to your organization, and come to us with questions.

Try it out

Learn more about our responsible AI principles here at Microsoft.

Related links

• See how we’re responding to the AI revolution with an AI Center of Excellence.
• Learn how a data council is powering our unified data strategy at Microsoft.
• Read our guide to becoming a Frontier Firm in the age of AI.
• Explore ways that we’re accelerating employee support with our new 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 Responsible AI: Why it matters and how we’re infusing it into our internal AI projects at Microsoft 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.

That’s why we built our own optical network at our headquarters in Washington state, and that’s why we’re building similar networks at other regional campuses around the United States and the rest of the world.

With so much on the line, we need to make sure these in-house networks never go down.

But how are we doing that?

We’re applying the same robust Zero Trust approach we take to security and identity. While our optical networks are extremely reliable, any complex system can be knocked offline. In alignment with the Zero Trust mentality we have as a company, we trusted the integrity of what we’ve built, but we needed a resilient backup system that went beyond redundancy to provide true resilience.

Driven by this goal, we created a Zero Trust Optical Business Continuity Disaster Recovery (BCDR) network that combines two fully independent optical systems designed to sustain uninterrupted services, even during systemic failures. The result is more confidence for our employees and vendors, less pressure on our network engineers, and comprehensive network resilience that will protect us against a major outage.

The urgency of resilience

In 2021, our team in Microsoft Digital, the company’s IT organization, deployed our first next-generation optical network to serve the exclusive network needs of our Puget Sound metro campuses. It offers more bandwidth on less fiber for a lower operational cost than leasing from traditional carriers.

“Puget Sound is a highly concentrated developer network where we need to provide very high throughput,” says Patrick Alverio, principal group software engineering manager for Infrastructure and Engineering Services within Microsoft Digital. “Our optical system is the backbone of all that traffic.”

Our state-of-the-art optical network fulfills our need for fast and reliable connectivity at up to 400 Gbps between core sites, labs, data centers, and the internet edge. We built this network on the Reconfigurable Optical Add/Drop Multiplexer (ROADM) technology, delivering dynamic reconfiguration, colorless, directionless, contentionless (CDC) capabilities, flexible grid support, remote provisioning, and automation. It also features a full-mesh topology that provides a layer of redundancy.

But what if the entire ROADM-based system fails?

There are plenty of operational risks that can derail even the most robust network. Anything from misconfigured automation scripts to policy changes to misaligned software versioning to simple human error can cause outages.

“We don’t want even a second of downtime. We needed a life raft for when failures occur that could also function as a standby network for core site migrations or platform upgrades.”

Vinoth Elangovan, senior network engineer, Hybrid Core Network Services, Microsoft Digital

To some degree, those kinds of minor disruptions are inevitable. But catastrophic events like fiber cuts, failures in the ROADM operating system, or even natural disasters have the potential for even more wide-ranging disruption.

During a catastrophic outage, thousands of engineers, developers, researchers, and other technical employees who need access to crucial lab environments and data centers could lose connectivity. That can sabotage feature delivery, disrupt product patches, interrupt updates, and halt all kinds of core product functions.

On top of normal software development operations, new AI tools demand massive bandwidth and consistent uptime. Finally, our hybrid networks feature paths integrated with Microsoft Azure that consume on-premises resources, so they also stand to benefit from increased resilience.

A catastrophic network outage can cause incredible damage to all of these business functions. In fact, we experienced exactly that in 2022.

A fiber cut combined with a ROADM system hardware reboot caused a five-minute outage at our Puget Sound metro region. In this environment, every minute of lost connectivity can result in significant financial impact, making network resilience absolutely essential.

“We don’t want even a second of downtime,” says Vinoth Elangovan, senior network engineer, who designed and implemented the Zero Trust Optical BCDR network for Microsoft. “We needed a life raft for when failures occur that could also function as a standby network for core site migrations or platform upgrades.”

Delivering greater network resilience

To ensure we could deliver uninterrupted network connectivity even in the midst of a catastrophic outage, we needed to consider the technical demands of a truly resilient system. Five design pillars helped us assemble our architectural criteria:

1. Independent optical systems: To provide true resilience, our primary and BCDR platforms needed to operate autonomously.
2. Physically independent paths: Circuits should avoid shared conduits, fibers, and splices to operate completely independently.
3. Separate control software: The primary and backup networks should operate through dedicated network management systems (NMSs), automation, and provisioning domains.
4. Unified client interface: Both systems needed to terminate into the same interface to unify service for clients and applications.
5. Survivability by design: We couldn’t assume that any system would be immune to failure. Instead, we built for the best possible outcomes.

The result was the Zero Trust Optical BCDR architecture, a layered approach to optical networking. It consists of our primary, ROADM-based transport layer and a secondary, MUX-based transport layer, both terminating into a single logical port channel.

“Our core responsibility is the employee experience, so our main design thrust was making sure service is seamless and uninterrupted—even during an outage.”

Vinoth Elangovan, senior network engineer, Hybrid Core Network Services, Microsoft Digital

Both systems are live and active, which means they deliver production services through their own independent fibers, power supplies, and software stacks. By layering fully independent optical domains and logically unifying them at the Ethernet edge, the network can sustain a complete failure of one system and maintain continuity.

That physical and operational independence is the difference between simple redundancy and robust resilience.

“Our core responsibility is the employee experience, so our main design thrust was making sure it’s seamless and uninterrupted—even during an outage,” Elangovan says.

Optical network backed by a BCDR network

A typical ROADM optical network connects campus and data center sites to the internet edge. Our design features three interconnected optical rings, with two internet edges as multi-directional nodes, while other sites operate as dual-degree nodes with bidirectional redundancy. Meanwhile, our campuses and datacenters are designated as critical sites and equipped with Optical BCDR links to ensure enhanced resiliency. In the event of a complete Optical ROADM line failure, these critical sites retain connectivity.

In the event of an outage on the primary network, the port channel handles forward continuity automatically, shifting WAN traffic between optical paths in real time.

The transition occurs seamlessly and transparently, with no noticeable impact to clients.

“Our initial goal was to provide high-throughput connectivity for major labs, with less than six minutes of downtime per year. That represents a service level of 99.999% network continuity, and we’re aiming for even better moving forward.”

Blaine Martin, principal engineering manager, Hybrid Core Network Services, Microsoft Digital

Coupling at the Ethernet layer provides clients and applications with one logical interface, automatic load balancing and traffic distribution, and seamless failover, regardless of which optical domain is providing service.

“Our initial goal was to provide high-throughput connectivity for major labs, with less than six minutes of downtime per year,” says Blaine Martin, principal engineering manager for Hybrid Core Network Services in Microsoft Digital. “That represents a service level of 99.999% network continuity, and we’re aiming for even better moving forward.”

A new era of confidence for network engineers

For the network engineers who keep Microsoft employees and resources connected, the Zero Trust Optical BCDR network relieves much of the pressure that comes from resolving outages.

“Before, we were dependent on a single system, even with redundancies, so the human experience was like firefighting. Now, if the primary optical network is having a problem, I don’t even see it.”

Kevin Bullard, principal cloud network engineering manager, Microsoft Digital

When a network goes down, engineers have an enormous set of responsibilities to manage: processing the incident report, assigning severity, performing checks, notifying internal teams, providing updates, and engaging with physical support teams—all with a profound urgency to restore productivity.

Dialing those pressures back has been a huge benefit.

“Before, we were dependent on a single system, even with redundancies, so the human experience was like firefighting,” says Kevin Bullard, Microsoft Digital principal cloud network engineering manager responsible for maintaining WAN interconnectivity between labs. “Now, if the primary optical network is having a problem, I don’t even see it.”

There will always be pressure on network engineers to restore connectivity during an outage, but they can breathe easier knowing it won’t cost the company millions of dollars as the time to resolve ticks away. And in non-emergency situations like core site migrations, the BCDR network provides a much easier way to shunt services while the main network is offline.

“Our internal users have become more confident that they can stay connected, no matter what,” says Chakri Thammineni, principal cloud network engineer for Infrastructure and Engineering Services in Microsoft Digital. “That gives the people responsible for maintaining our enterprise networks incredible peace of mind.”

Fortunately, there hasn’t been a substantial network outage in the Puget Sound metro area since 2022. But our network engineering teams know that if and when it happens, the BCDR network will be ready to maintain service continuity.

“We’re always looking ahead into industry trends to stay at the bleeding edge, whether that’s in the technology we provide for our customers or the networks we use to do our own work.”

Patrick Alverio, principal group software engineering manager, Infrastructure and Engineering Services, Microsoft Digital

With our Puget Sound network protected, we have plans in place to extend this model to other metro areas. Naturally, we have to balance population, criticality, and the knowledge that elevated reliability and availability come with a cost.

Our selection criteria for new BCDR networks have largely centered around two factors: expansions of AI-critical infrastructure and concentrations of secure access workspaces (SAWs) for technical employees. With these criteria in mind, we’re planning new BCDR networks first in the Bay Area and Dublin, then in Virginia, Atlanta, and London.

Zero Trust optical BCDR architecture represents a paradigm shift in enterprise network resilience, and we’re committed to expanding the model to benefit both conventional workloads and the expanding infrastructure demands of AI.

“We’re always looking ahead into industry trends to stay at the bleeding edge, whether that’s in the technology we provide for our customers or the networks we use to do our own work,” Alverio says. “We refuse to accept the status quo, and we’re elevating the experience for employees across Puget Sound and Microsoft as a whole.”

Driving AI innovation in optical network resilience

Our journey towards an AI-driven optical network is gaining momentum.

As part of our Secure Future initiative, we’ve automated our Optical Management Platform credential rotation and are actively developing intelligent incident management ticket enrichment, auto-remediation, link provisioning, deployment validation, and capacity planning.

AI plays a central role in this transformation.

With Microsoft 365 Copilot and GitHub Copilot integrated into our engineering workflows, we’re accelerating development cycles, improving code accuracy, and uncovering optimization opportunities that would otherwise take hours of manual effort.

These Copilots are also helping our engineers analyze network patterns, simulate outcomes, and validate deployment logic before execution, reducing human error and strengthening our Zero Trust posture. Over time, we’re evolving toward a system where AI not only assists but proactively predicts potential disruptions, recommends remediations, and continuously learns from operational telemetry.

These advancements are paving the way for a future where our optical infrastructure can anticipate issues, recover faster, and operate with the agility and assurance expected in a Zero Trust environment.

Key takeaways

If you’re considering implementing your own optical and BCDR networks, consider these tips:

• Understand the technical components of resilience: Independent optical systems, physically independent paths, separate control software, a unified client interface, and survivability by design are the key technical components of true resilience.
• Plan from a preparedness and value perspective: Evaluate the critical points in your infrastructure and determine where you can get the most value out of resilient connectivity.
• Ensure your teams have the right skillset: Carefully consider the right workforce to run those systems and be accountable for their operation.

Try it out

Learn about and start exploring how to make similar investments and find similar investments at your company by exploring our Microsoft Azure Virtual Network technology. You’ll need a subscription to Microsoft Azure—go here to sign up for a free trial.

Related links

• Learn how we’re boosting connectivity with our own next-generation optical network.
• See how we’re maintaining better network performance at Microsoft with real-time telemetry and performance visualization.
• Find out how Microsoft kept its underwater datacenter connected while retrieving it from the ocean.
• Learn about enhancing network reliability at Microsoft with AIOps and Network Infrastructure Copilot.
• Explore five principles that guided our network journey to Microsoft Azure and the cloud at Microsoft.
• Discover ways we’re using AI to reinvent our network security.
• Find out how we’re finding and fixing network outages in minutes—not hours—with real-time telemetry at Microsoft.
• Read how our team is working with Ciena to deliver resilient metro connectivity with Zero Trust-based optical design.

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 Keeping our in-house optical network safe with a Zero Trust mentality appeared first on Inside Track Blog.

People are using Microsoft 365 Copilot as their personal AI assistant and employing agents to power new workflows. Meanwhile, our teams are building and deploying AI-powered solutions to meet our enterprise needs.

But advancing along the AI maturity curve means more than just adoption. It’s about fundamentally reworking our daily habits to boost productivity and empower our AI assistants to help us accomplish meaningful work.

At Microsoft, we’re dedicated to helping our employees weave Copilot and other AI tools into the fabric of their workdays. To get there, we’ve used the lessons from our early skilling efforts and our experience with peer-to-peer adoption leadership as the foundation for a new learning path.

This is the story of Copilot Expo.

A new approach to skilling

Thanks to the success of our Camp Copilot adoption efforts, we learned valuable lessons about rolling AI out across a company like ours.

We took what we learned working with our champ community and turned it into a more formal Microsoft 365 Copilot adoption program that evolved into an extended company-wide event called Copilot Expo. Our change leaders within Microsoft Digital, the company’s IT organization, drove this three-week online skilling path with the support of our dedicated community of AI peer leaders, the Copilot Champs.

“We saw daily adoption move a lot more when we were presenting content that was bespoke to people’s roles and organizations.”

Stephan Kerametlian, business program management senior director, Microsoft Digital

As AI technology matured, we knew we needed to update our skilling offerings along with it. Some key lessons helped us make that a reality:

• AI adoption is about more than monthly active usage (MAU) and daily active usage (DAU). It’s about depth of engagement with the tools.
• Peer leadership is a must. Seeing people you know use a tool makes it much more accessible and attainable.
• Gamification was one of the most successful features of our early efforts, so we knew we needed to deepen those elements.
• Making content on-demand extends the life of an event like this, leading to easier knowledge discovery and further engagement.
• Company-wide initiatives are powerful, but divisions crave events tailored to their work, on their teams, in their disciplines.

“We saw daily adoption move a lot more when we were presenting content that was bespoke to people’s roles and organizations,” says Stephan Kerametlian, a business program management senior director within Microsoft Digital. “Copilot Expo was able to go a lot deeper into different roles and processes to make Copilot more real in people’s day-to-day jobs.”

Copilot Expo: Advancing along the AI maturity curve

Copilot Expo extended throughout three weeks, with plenty of opportunities for learning at different levels of AI maturity.

Our curriculum included three main sessions for the week. To accommodate different time zones with live presentations instead of recordings, each of those sessions took place three times across 12 hours. After each main session, breakouts expanded on their themes, highlighting different areas of Microsoft 365 Copilot.

Some breakouts covered day-in-the-life scenarios that resonated with a wide cross-section of employees, but we also tailored use cases to more specific disciplines and tasks. As a result, the learning path included more role-specific breakouts like “Copilot for Product Managers,” more technical topics outside Copilot like GitHub and Azure DevOps, and more advanced learning like deep dives on prompting.

To help land the lessons for the week, we offered gamified experiences on Microsoft Viva Engage. These activities typically involved a creative prompting exercise, which participants would then share with their Viva Engage communities. As an added bonus, the social aspect helped drive further groundswell for Copilot Expo.

“Peer influence can scale further and faster than policy alone. Employees show a lot more interest in content their colleagues create than material handed down from IT or adoption professionals.”

Cadie Kneip, readiness business program manager, Microsoft Digital

The sheer number of sessions meant we needed to expand the involvement of Microsoft Digital subject matter experts and change leaders, but it was absolutely essential that we involve our Copilot Champs and maintain the peer-to-peer aspect that made Camp Copilot such a success.

Why?

Because we find that our employees respond well when a respected colleague shows them how to do something or shares why they are excited to try something new.

“Peer influence can scale further and faster than policy alone,” says Cadie Kneip, a readiness business program manager within Microsoft Digital. “Employees show a lot more interest in content their colleagues create than material handed down from IT or adoption professionals.”

When participants completed the learning path, we handed out awards, shared resources, and provided opportunities for feedback. All of these elements helped employees feel a sense of accomplishment while providing our adoption team with valuable insights.

We also updated our key metrics around Copilot usage and sentiment. To make sure these metrics demonstrated meaningful change, we tracked them for comparable periods both before and after Copilot Expo.

Gamification drives deeper engagement

When we developed the plan for Copilot Expo, we knew gamification was one of the most powerful levers we could pull. Not only does it provide a fun way for participants to practice the skills they’ve learned, but it boosts retention and uptake.

Our internal research suggests that fun and gamification amplify engagement by 24% and increase productivity by 50%. They also reduce the time it takes to form habits by 40%.

“You need to think about the activities you can do to inspire your employees to recognize the value AI can hold for their work.”

Sandra Hausfelder, global adoption lead, Microsoft Digital

One of the most exciting components was a live leaderboard featuring participants’ avatars and gamertags created using Microsoft 365 Copilot. The dashboard assigned people points when they completed different components of the curriculum, and the friendly competition boosted engagement through a sense of pride.

We also increased the number of gamified activities that took place throughout the learning path. Yet again, our presenters and peer-to-peer leaders provided essential support, and we were able to crowd-source many of these gamification ideas.

Gamified activities included:

• Creating a new digital avatar by prompting Microsoft 365 Copilot.
• Building a unique superhero.
• Writing a song with Copilot’s assistance.
• Creating digital swag by designing an enamel pin.
• Going on a scavenger hunt by trying out 10 Copilot scenarios.

“You need to think about the activities you can do to inspire your employees to recognize the value AI can hold for their work,” says Sandra Hausfelder, a global adoption lead for Copilot in Microsoft Digital.

At the end of Copilot Expo, we offered MVP badges designed using Credly for everyone who completed all the necessary steps. In addition to solidifying the learning with a final motivator, providing a badge encouraged participants to share their journey with their networks, further promoting Copilot Expo as an opportunity for professional growth.

Decentralization and on-demand learning

One of the most important aspects of Copilot Expo is its capacity for extending learning opportunities beyond our centralized event series. We’re accomplishing that in two ways.

First, we make all of our Copilot Expo content available on demand as part of a persistent SharePoint page accessible to both participants and non-participants. These resources aren’t just for passive discovery. We also use them for active adoption efforts like our “Copilot Daily Discoveries” campaign on Microsoft Viva Engage.

Since the end of Copilot Expo, employees have accessed these resources thousands of times—even people who didn’t participate in the event series itself. That demonstrates a real hunger for opportunities to learn about AI.

The greatest potential impact may come from decentralizing this learning model. Company-wide events can only do so much to bridge time zones, languages, and discipline-specific scenarios.

As a result, we’ve designed a system for enabling more tailored events within individual regions and Microsoft divisions. Essentially, we’ve templatized the Copilot Expo experience, and leaders can reach out to the Microsoft Digital team to help assemble and run their own events with more customized learning paths.

Building momentum with activities

We start by conducting discovery sessions and interviews that uncover how employees might use Microsoft 365 Copilot in their roles. We also look at existing usage metrics and identify Copilot Champs who can act as advisors and ambassadors.

“We have a baseline package of material, and then we partner with organizational executives and change leaders who want to bring it to their own teams,” Kneip says. “Then we work with Copilot Champs to tailor it to their organizations.”

These focused events typically take shape as three-day learning paths. They tend to cover similar elements to the company-wide expo across the basics, leveling up, and building daily habits. The difference is that they’re highly scenario-specific.

For example, we might provide example scenarios for the Cloud + AI team, like “Give me suggestions for optimizing our next datacenter.” On engineering-heavy teams, we might focus on opportunities for AI in the software development lifecycle.

“Every mini-expo looks a little bit different because we customize it to the organization,” Hausfelder says. “We work hard to create a span of customization by looking into the details of what the organizations need us to land for their employees.”

Continuous impact through more effective adoption

Whether they’re division-based or specific to a region, these learning paths have been highly effective. In one instance, we ran a three-day event specific to Central America and the Caribbean. That led to a 15% increase in DAU and a 17% increase in week-over-week Microsoft 365 Copilot usage.

“Copilot Expo sets us up for success in the future, because it’s a delivery mechanism for employees, by employees, scaled through Copilot Champs.”

Alexandra Jones, director of business programs, Microsoft Digital

Our company-wide Copilot Expo also demonstrated substantial impact. Before-and-after tracking of key metrics over equivalent testing periods revealed substantial boosts:

• Average DAU increased substantially.
• Copilot-assisted hours climbed sharply.
• Copilot actions taken jumped significantly.
• Copilot-assisted value nearly doubled.
• The perception of the quality work done with Copilot measurably increased.

It’s a testament to the power of coordinated efforts that reach across the company as a whole and resonate with individual organizations.

“We’ve created this persistent platform as a recognizable brand for skilling, and it enables us to continue driving change,” says Alexandra Jones, a director of business programs within Microsoft Digital. “Copilot Expo sets us up for success in the future, because it’s a delivery mechanism for employees, by employees, scaled through Copilot Champs.”

Key takeaways

Adopt the lessons we’ve learned during the Microsoft Copilot Expo to successfully run your own AI skilling event.

• Listen to stakeholders: Collaborate with organizational insiders to think about the gaps they see and the content that will be relevant to their teams.
• Design your content for discovery: Evolve your offerings to be more self-serve and self-directed while maintaining crucial opportunities for connection.
• Start small and apply the lessons you learn: Begin with a pilot. Bring eager adopters together and run a small and focused expo.
• Gamification gets results: People take delight in demonstrating progress and participation. Incorporate badges, certifications, leaderboards, and other elements of fun.
• Identify your key metrics: Don’t just think about usage percentage. Focus on metrics that really demonstrate value. Examples include the number of actions, Copilot-assisted hours, and sentiment.

Try it out

Get step-by-step instructions for creating an engaging Microsoft 365 Copilot training series with our Copilot Virtual Skilling Event Framework.

Related links

• See how we made Microsoft 365 Copilot adoption fun with Camp Copilot.
• Try our 7 tips for driving Microsoft 365 Copilot adoption with a virtual skilling event.
• Learn how we’re driving Microsoft 365 Copilot adoption with our Copilot Champs Community.
• See how we’re transforming our employee experience with AI.
• Supercharge your business transformation with Microsoft Viva.
• Unleash API-powered agents at Microsoft: Our internal learnings and a step-by-step guide.
• Unlock your productivity with these Top 10 tips for using Microsoft 365 Copilot every day.

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 Enabling meaningful AI adoption at Microsoft with a Microsoft 365 Copilot Expo appeared first on Inside Track Blog.

To meet these demands, many of our teams within Microsoft Digital, the company’s IT organization, have been experimenting with API-based agents. This approach combines the best of two worlds: accessing diverse apps and data repositories and eliminating the need to build an agent from the ground up.

We want to empower every organization to unlock the full power of agents through APIs. The lessons we’ve learned on our journey can help you get there.

The need for API-based agents

The vision for Microsoft 365 Copilot is to serve as the enterprise UX. Within that framework, agents serve as the background applications that streamline workflows and save our employees time.

For many users, the out-of-the-box access Copilot provides to Microsoft Graph is enough to support their work. It surfaces the data and content they need while providing a foundational orchestration layer with built-in capabilities around compliance, responsible AI, and more.

But there are plenty of scenarios that require access to other data sources.

“Copilot provides you with data that’s fairly static as it stands in Microsoft Graph,” says Shadab Beg, principal software engineering manager on our International Sovereign Cloud Expansion team. “If you need to query from a data store or want to make changes to the data, you’ll need an API layer.”

By using APIs to extend agents built on the Copilot orchestration layer, organizations can apply its reasoning capabilities to new data without the need to fine-tune their models or create new ones from scratch. The possibilities these capabilities unlock are driving a boom in API-based agents for key functions and processes.

“Cost is one of the most critical dimensions in how we design, deploy, and scale our solutions. Declarative API-driven agents in Microsoft 365 Copilot offer a path to unify agentic experiences while leveraging shared AI compute and infrastructure.”

Faisal Nasir, AI Center of Excellence and Data Council lead, Microsoft Employee Experience

In many ways, IT organizations like ours are the ideal places to implement API-based agents. Our teams are adept at creating and deploying internal solutions to solve technical challenges, and IT work is often about enablement and efficiency—exactly what agents do best.

“Cost is one of the most critical dimensions in how we design, deploy, and scale our solutions,” says Faisal Nasir, AI Center of Excellence and Data Council lead in Microsoft Employee Experience. “Declarative API-driven agents in Microsoft 365 Copilot offer a path to unify agentic experiences while leveraging shared AI compute and infrastructure. By aligning with core architectural principles such as efficiency, scalability, and sustainability, we can ensure these agents not only drive intelligent outcomes but also maximize value across service areas with minimal overhead.”

{Learn more about our vision and strategy around deploying agents internally at Microsoft.}

The Azure FinOps Budget Agent

Our Azure FinOps Budget Agent is a perfect example of a scenario for API-based agents.

The team responsible for managing our Microsoft Azure budget for IT services was looking for ways to reduce costs by 10–20 percent. To do that effectively, service and finance managers needed the ability to track their spending quickly, accurately, and easily.

The conventional approach to solving this problem would be creating a dashboard with access to the relevant data. The problem with a UI-based approach is that it tends to cater to more specific personas by providing data only they need while oversaturating others with information that’s irrelevant to their work.

“Azure spend is basically the lifeline for our services,” says Faris Mango, principal software engineering manager for infrastructure and engineering services within Microsoft Digital. “Getting the information you need in a concise format that provides a nice, holistic view can be challenging.”

With the advent of generative AI and Microsoft 365 Copilot, the team knew that a natural language interface would be much more intuitive. The result was the Azure FinOps Budget Agent.

The team created the agent and the necessary APIs using Microsoft Visual Studio Code. Its tables and functions run on Azure Data Explorer, allowing the APIs and their consumers to access data almost instantaneously, thanks to its low latency and rapid read speeds.

The tool retrieves data by running Azure Data Factory pipelines that pull and transform data from three sources:

• Our SQL Server for service budget and forecast data
• Azure Spend for the actual spending amounts
• Projected spending, a separate service stored in other Azure Data Explorer tables

Processing the information relies on our business logic’s join operations, followed by aggregations by fiscal year and service tree levels. These summarize the data per service, team group, service group, and organization.

After the back end processes the day’s data, it ingests the information into our Azure Data Explorer tables, which the agent accesses by calling via Kusto functions (the query language for Azure Data Explorer). The outcome is very low latency. Typically, the agent returns results in under 500 milliseconds.

For users, the tool is stunningly simple. They simply access Copilot and navigate to the Azure FinOps Budget Agent.

The agent provides three core prompts at the very top of the interface: “My budgets,” “Service budget information,” and “Service group budget information.” Clicking on one of these pre-loaded prompts returns role-specific information around budget, forecasts, actuals, projections, and variance, all at a single glance. The interface even includes graphs to help people track spending visually.

If users are looking for more specific information, they can input their own queries. For example:

• “Get me the monthly breakdown of service Azure Optimization Assessment analytics.”
• “Find me the service in this tree with the highest budget.”
• “Show me the Azure budget for our facilities reporting portal.”
• “Which service deviates most from its budget forecasts?”

The Azure FinOps Budget Agent primarily serves two groups: service managers who directly oversee spend for Azure-based services and FinOps managers responsible for larger budget silos.

Mango is responsible for the internal UI that helps network employees access parts of the Microsoft network. With 18–20K users per month, budgeting and forecasting are highly dynamic due to traffic fluctuations and the resourcing that supports them. He also oversees the internal portal that helps service engineers manage our networks. The tool is growing rapidly as we onboard more teams, so forecasting is anything but linear.

For both of these services, keeping close track of spending is essential. Mango finds himself checking the Azure FinOps Budget Agent about twice a month to gauge how his services are trending.

“It’s taking me less time to do analysis and come up with accurate numbers. And the enhanced user experience just feels more natural, like you’re asking questions conversationally rather than engaging with a dashboard.”

Faris Mango, principal software engineering manager for infrastructure and engineering services, Microsoft Digital

For FinOps managers, the value is more high-level. They are responsible for overseeing tens of services featuring vast volumes of Azure usage across storage and compute while managing strict budgets. That requires constant vigilance.

Switching context from one dashboard to another to track different Azure management groups was a constant hassle for them. Now, they use the Azure FinOps Budget Agent to get an up-to-date view of the overall spend picture. It gives them a place to start. From there, they can drill down if he sees any abnormalities.

“It’s taking me less time to do analysis and come up with accurate numbers,” Mango says. “And the enhanced user experience just feels more natural, like you’re asking questions conversationally rather than engaging with a dashboard.”

The arrival of the Azure FinOps Budget Agent is just one example of how agents take your context and get your people the answers they care about faster at less cost.

Benefits like these are spreading across teams throughout Microsoft. Overall, we’ve been able to save 10–12 percent of our overall Azure cost footprint for Microsoft Digital, and individual users are thrilled at the amount of time and effort they’re saving.

“Now the info is at people’s fingertips. The advantage of an agent is that users don’t have to understand a complex UI, so they can get quick answers and get back to work.”

Shadab Beg, principal software engineering manager, International Sovereign Cloud Expansion

Five key strategies for building an API-based agent

After seeing what we’ve accomplished with API-based agents, you might be wondering how to put them into action at your organization. This step-by-step guide can help you get there.

Building an API-based agent needs to fulfill multiple requirements. It has to expose APIs, align with real user needs, integrate seamlessly with Microsoft 365 Copilot, and work reliably, efficiently, and scalably. Achieving those outcomes depends on five key strategies.

Start with user intent, not the API

Start by asking a simple but powerful question: What will users actually ask your agent? Instead of designing the API first, flip the process:

• Gather real user queries to understand actual use cases.
• Refine the queries using prompt engineering techniques to align them with expected AI behavior.
• Design the API to provide structured responses to those refined queries.

By starting with user intent, you ensure your agent answers real user questions directly, avoids over-engineering unnecessary endpoints, and delivers meaningful results without excessive back-end processing.

“Now the info is at people’s fingertips,” Beg says. “The advantage of an agent is that users don’t have to understand a complex UI, so they can get quick answers and get back to work.”

The advantage of an agent is that users don’t have to understand a complex UI, so they can get quick answers and get back to work.”

Design APIs for Microsoft 365 Copilot Integration

It’s important to build an API schema that returns precise and structured data to make it easy for Copilot to consume. This ensures your APIs return data in a format that directly answers user queries. Copilot expects responses in under three seconds, so focus on optimizing API responses for low latency.

Once you have your list of key questions, design your API schema to return the exact data you need to answer those questions. Your goal should be to ensure every API response has a structure that makes it easy for Copilot to understand.

Teach Microsoft 365 Copilot to call your API

Copilot needs to know how to call your API. Manifests and OpenAPI descriptions accomplish that training.

Create detailed OpenAPI documentation and plugin manifests so Copilot knows what your API does, how to invoke it, and what responses to expect. You’ll likely need to adjust to these files through a process of trial and error.  

Scale APIs for performance and reliability

Once you have your schema and integration in place, it’s time to move on to the primary engineering challenge: making your API scalable, efficient, and reliable.

Prioritize the following goals:

• Fast response times: Copilot expects quick answers.
• High scalability: This ensures seamless performance at scale.
• Reliable uptime: The system needs to remain robust.

We recommend setting a very strict latency limit while implementing your API to retrieve data, since Copilot needs time to generate its response. Existing API endpoints often involve complex data joins rather than simply returning rows from data tables. This complexity can lead to longer processing times, particularly with intricate queries that involve multiple data stores.

To address these potential delays, pre-cache results to significantly enhance performance. This can help overcome the latency requirements imposed by Copilot.

At this point, you’ll see why starting with user intent and iteratively refining API design is important. By grounding your work in user behaviors, you’ll align with the following best practices:

• Structure your response to directly address user queries.
  Instead of just returning raw data, the API should provide meaningful insights Copilot can interpret. Prompt engineering marries user intent with the most understandable API schema.
• Keep your API flexible enough to adapt to evolving business needs.
  Real-world workflows change over time, and an API should be able to support those changes without massive refactoring.
• Avoid performance bottlenecks caused by unnecessary complexity.
  Understanding the exact data requirements up front prevents heavy joins, excessive filtering, and inefficient data retrieval logic.
• Optimize for Copilot’s real-time response constraints.
  With a strict limit on latency, consider pre-optimization techniques like pre-caching results and simplifying query logic from the very beginning of your API implementation.

If you attempt to build a scalable, reliable API without first understanding how users will interact with your agent, you’ll spend months reworking the schema, debugging inefficiencies, and struggling with integration challenges.

Consider compliance and responsible AI

Unlike custom agents or OpenAI API integrations, knowledge-only agents require far less effort to meet Microsoft’s Responsible AI Standard. Microsoft tools’ built-in compliance capabilities handle much of the complexity. As a result, you can focus on efficiency and optimization rather than regulatory hurdles.

“Agent-based automation must balance speed with responsibility,” Nasir says. “We embed compliance, cost control, and telemetry from the start, so our systems don’t just scale, they mature.”

APIs and the agentic future

Building API-based agents is more than just an integration exercise. It’s about creating scalable, intelligent, and compliant AI-driven workflows. By aligning your API design with user intent, you set Microsoft 365 Copilot free to retrieve and interpret information accurately. That leads to a seamless AI experience for your employees.

Thanks to Copilot’s built-in security and compliance features, API-based Copilot agents are some of the most efficient, compliant, and enterprise-ready ways to deploy AI solutions. They represent another step into an AI-first future tailored to your employees’ and organization’s needs.

Tools like API-based agents democratize the information we all need to do our jobs better, because we’re all getting the same data from the same place. This is why an AI-first mindset is actually human-first.

Key takeaways

Here are some things to keep in mind when designing agent-powered experiences that are fast, reliable, and aligned with user expectations.

• Response time is key. Choose single APIs that have low latency to facilitate both the technical requirements of Copilot and users’ needs.
• Consider the source. Data has to be high-quality on the backend. It’s worth reviewing your data and ensuring the hygiene is good.
• Agents and APIs need to align. Design with task-centric, well-structured agents. Determine your high-level goals, then use the OpenAI standard, OpenAPI, or graph schemas to describe task endpoints. Define each API’s capability, input schema, and expected outcome very clearly.
• Plan ahead to avoid surprises. Design your APIs to minimize potential side effects, especially through enabling natural-language-to-API mapping, because that’s the biggest change in methodology.
• Design for visibility. Agents need to be observable and explainable, so implement metrics-driven monitoring. Having API-level telemetry in addition to Copilot-level telemetry enables continuous improvement.

Try it out

Create and deploy an agent in Microsoft Copilot Studio.

Related links

• Learn how we’re enabling modern support at Microsoft with AI.
• Find out how we’re embracing this new ‘agentic’ moment at Microsoft.
• Check out how we’re riding the wave of agents washing over Microsoft with good governance.
• Discover ways our employees are extending enterprise AI with custom retrieval agents.

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 Unleashing API-powered agents at Microsoft: Our internal learnings and a step-by-step guide appeared first on Inside Track Blog.

These agents help employees reach beyond Microsoft Graph and Microsoft 365 applications to do their work more thoroughly and efficiently. By empowering users to experiment with AI-driven assistance and capabilities internally at Microsoft, we’re unlocking efficiency, process automation, and data-driven insights tailored to specific individuals’ or teams’ needs.

One tool is making Copilot extensions accessible to more employees than ever before: Microsoft Copilot Studio.

This low-code solution makes it possible for both technical and non-technical users to create their own agents and tailor Copilot’s capabilities to their work. At Microsoft Digital, the company’s IT organization, we’re the first to implement Copilot Studio and develop a methodology for empowering our employees to create while establishing guardrails to keep our organization’s data safe.

As a result, we’ve built best practices that help us protect employees while enabling helpful agents—from individualized tools to organization-wide utilities. We’ve also learned lessons that can help customers navigate their own Copilot Studio journey.

Extending enterprise AI with Microsoft Copilot Studio

Microsoft Copilot Studio, a part of Microsoft Power Platform, empowers employees to build their own agents or use them to extend Microsoft 365 Copilot’s value. It uses the same low-code connector model as Power Platform to power actions through first-party and third-party services.

“Copilot Studio is a way for a non-technical person to spin up an agent quickly.”

Amy Rosenkranz, principal product manager, Copilot Extensibility, Microsoft Digital

As a result, users can create their own agents tailored to specific professional needs and business functions. These agents can narrow the focus of knowledge within the Microsoft 365 Graph, reach outside of it, and even take actions.

There are several ways to create agents. They range from simple natural language queries in Copilot Studio agent builder through Copilot Chat in Microsoft Teams and SharePoint to the full-featured Copilot Studio graphical authoring environment to a combination of Copilot Studio and Azure AI.

“Copilot Studio is a way for a non-technical person to spin up an agent quickly,” says Amy Rosenkranz, principal product manager responsible for Copilot extensibility at Microsoft Digital. “You can pull from a SharePoint site, from a graph connector, or from the web, and so employees are using it to tailor their experience to their business process.”

Building agents with Copilot Studio

“There’s an important role for Copilot Studio in helping customize the solutions our employees create, whether they want to use existing functionality, extend their knowledge, or expand their skill compatibility.”

Eileen Zhou, senior program manager, Microsoft Digital

Ultimately, the goal is to help employees work more efficiently by putting them in the driver’s seat through the power of self-directed agent creation. It also helps alleviate strain on business functions by getting people to the answers they need faster, without the need for human intervention.

“There’s an important role for Copilot Studio in helping customize the solutions our employees create, whether they want to use existing functionality, extend their knowledge, or expand their skill compatibility,” says Eileen Zhou, senior program manager in Microsoft Digital. “And it provides opportunities for both non-technical creators who want to create individualized solutions and people with advanced knowledge who are building more enterprise-focused agents.”

To empower our employees for this kind of creativity, we needed to put guardrails in place that ensure they can build agents confidently without putting themselves or the company at risk.

Managing the scale and sophistication of Copilot Studio creations

Building guardrails around agent production meant developing a system for classifying them according to their purpose, reach, and potential risk.

On one end of the spectrum, simple retrieval agents might only access content that individuals author and own. Non-technical employees typically create this kind of agent through natural language prompts in Copilot Studio agent builder.

“There’s a time and place for personal agents that integrate with business workflows, but if something is a business-critical service, we need to think security-first.”

Jake Visser, principal architect manager, Copilot and AI apps

On the other end, more elaborate tools—task or autonomous agents that combine knowledge, action, and orchestration—need to cross data boundaries to accomplish their work. More technically advanced IT employees and professional developers build these agents for larger-scale business functions using the full-featured Copilot Studio authoring environment.

Agent capabilities

This simple taxonomy doesn’t capture the whole picture though. As a result of the varying reaches and risk profiles for different agents, we tend to group them into three categories:

• Personal self-service agents created by employees to meet highly individual business needs.
• Line-of-business agents created by individual organizations within Microsoft to fulfil discipline-specific work functions.
• Agents intended for publishing across the entire organization.

“If an employee is building a service, we need to manage it like a service,” says Jake Visser, principal architect manager for Copilot and AI apps. “There’s a time and place for personal agents that integrate with business workflows, but if something is a business-critical service, we need to think security-first.”

Microsoft Digital is responsible for developing and enforcing guidelines for managing those services.

“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

Governance, processes, and policy for enabling Microsoft Copilot Studio

Establishing guardrails around the different agents our employees can create in Microsoft Copilot Studio involved asking a lot of questions. What Power Platform features apply to Copilot Studio workflows? What additional areas of risk do agents introduce? How can we build policies and processes around low-code AI creations? How can we help employees understand the implications of the agents they create?

“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.”

Since Copilot Studio exists within Power Platform, that tool’s capabilities provided a solid foundation for managing agents. We have extensive experience empowering citizen developers while maintaining good governance through Microsoft Power Platform. So it was easy for us to apply existing administration and governance best practices to this new framework.

At the outset of our journey, we already had robust systems in place for securing custom connectors, and Microsoft 365’s built-in governance capabilities ensure Microsoft 365 agents respect our labeling taxonomy and the policies it articulates. Finally, we have the power to introduce sharing limits that restrict how widely creators can distribute agents depending on their purpose and scope.

Together, these features and capabilities helped us extend existing administration and governance structures to the new world of agents. But thoughtful process and policy are equally important.

For the simpler self-service agents that individual employees create and use, we’re able to define our policies at the Copilot Studio environment level. Tenant administrators and partners on the Microsoft Security team apply data loss prevention policies to configure what individual employees can and can’t do. At this level, everyone in the company has the same configuration and tools available, and automation largely handles agent reviews and assessments based on pre-configured settings.

For more wide-reaching apps that operate at the line-of-business level or that we might publish enterprise-wide, we need to apply greater rigor. Thanks to our experience administrating and governing Power Platform, Microsoft Digital already had a robust process in place to review internally created enterprise apps. Discipline-specific professionals in security, privacy, and other spaces conduct these reviews to ensure internal teams meet our high standards.

By building onto that structure, we’ve updated our custom environment review process for agents created in Copilot Studio. We step through a review process that includes phases for security assessments, threat modeling, privacy assessments, and Responsible AI reviews.

Our goal is to properly scope our governance controls into what people are building. If we can easily enable things we consider low-risk like retrieval agents, we let employees build those in their personal development environment, but more powerful or far-reaching custom agents require more thorough oversight.

Configuration, review, and assessment are only parts of the puzzle. We also flighted user awareness efforts to help employees understand not just how to use Copilot Studio, but also its implications for security, privacy, and Responsible AI.

These campaigns included field readiness through Viva Learning, Copilot Champs sessions, newsletters, marketing campaigns through Viva Amplify, office hours, internal roadshows, and elite programs. We even launched an agent-building contest that invited employees to design whatever they liked.

Providing employees with opportunities for learning and experimentation has helped jumpstart interest in creating agents. Together with product features, process, and policy, it ensures we unlock the full value of Copilot Studio safely and effectively.

Unlocking Copilot Studio value

With the freedom to create using Microsoft Copilot Studio and the protection of robust guardrails, individuals and teams are flexing their imaginations to create highly useful agents. We’re in the early days of our own Copilot extensibility journey, but agents are already driving faster and more accurate access to information and greater productivity.

Two examples stand out:

• The IDEAS Copilot, a retrieval agent, empowers informed decision-making by democratizing access to our IDEAS knowledge base and its insights on app usage. Through natural language queries, IDEAS lets users take action on crucial usage data without the need for technical expertise.
• The Employee Self-Service Agent in Microsoft 365 Copilot, a more advanced and organization-spanning agent, provides access to HR, IT, and facilities-related information and tools through two interfaces: Copilot or our company sites.

As the capabilities of Copilot Studio continue to grow, Microsoft Digital is actively collaborating with the product team to ensure administration and governance features keep pace with its technical elements. Our experience as the first and largest adopters of this new framework mean that every lesson we learn internally helps the product accommodate businesses’ needs more effectively.

“Everyone wants to move fast, and people are enthusiastic to explore this new framework for enterprise AI. Our guiding principle is making the product secure by default so businesses can make it happen safely.”

David Johnson, principal program manager, Microsoft Digital

Thanks to our experience at Microsoft, the product has incorporated several new features:

• A set of controls for Copilot Studio connectors that allow guardrails for self-service.
• The ability to specify data sources including SharePoint sites, public URLs, internal documents, or others.
• Connector endpoint filtering that lets administrators govern the SharePoint sites and other connectable endpoints when creators build apps, flows, or agents.
• Different channels for publishing agents, like Microsoft Teams, websites, or integrations into tools like Dynamics 365.
• Suggested configuration defaults, for example requiring authentication so people can’t create anonymous Copilots.

Between built-in features and emerging best practices, Copilot Studio is unlocking the freedom to create like never before while maintaining organizational safety. For our customers and Copilot users, that means multiplying AI’s impact by setting employees free to create tools that will help them do their work faster, better, more creatively, and more insightfully.

“Everyone wants to move fast, and people are enthusiastic to explore this new framework for enterprise AI,” says David Johnson, principal program manager architect for governance at Microsoft Digital. “Our guiding principle is making the product secure by default so businesses can make it happen safely.”

Key takeaways

Here are some tips for getting started with Copilot Studio at your company:

• Have an all-up tenant strategy. Create separate Power Platform environments based on what people want to build, what data they want to use, and what controls you need as a result.
• Take this opportunity to make sure that your governance is up to date and aligns properly between Power Platform and Microsoft 365.
• Educating your users is key. Recognize that most difficulties arise from inefficiency and error, not nefarious intention.
• Evaluate your risk tolerance for different kinds of Copilot Studio creation and structure your security and governance efforts around that.
• Take advantage of dev environments to learn and practice.

Try it out

• Curious what Copilot Studio can accomplish for your business? Try a demo here.

Related links

• Learn how we’re using good governance to ride the wave of agents washing over Microsoft.
• Find out how we’re embracing this new ‘agentic’ moment at Microsoft.
• Check out our guide for deploying and driving adoption of Microsoft 365 Copilot at your company.
• Discover how we’re driving deeper AI value with Copilot extensibility.

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 Unlocking enterprise AI extensibility at Microsoft with Microsoft Copilot Studio appeared first on Inside Track Blog.

But how are we implementing this new framework?

Thanks to our team at Microsoft Digital, the company’s IT organization, we’re extending Copilot’s value by taking better advantage of our Microsoft 365 Graph in more connected and efficient ways. As a result, Copilot extensions can connect with widely dispersed organizational information to help our employees find answers more effectively, work more efficiently, and think more creatively.

Taking Copilot to this next level is enabling us to extend its reach into more specific business scenarios. Those include quickly spinning up specialized agents that range from large, companywide experiences—like an agent that’s streamlining how our employees interact with HR and IT—to small, citizen developer-built solutions that solve specific tasks for individual employees or small teams.

Using Copilot Studio, organizations from across the company can build agents that provide tailored AI assistance to unlock new experiences for our employees, optimize our core processes, and provide deeper business insights.

Opening new horizons for intelligent assistance

Out of the box, Microsoft 365 Copilot provides powerful access to company data across our Microsoft tenant, discoverable through the Microsoft Graph. But not all information lives in the Microsoft Graph, and our employees do their work using more than just one set of tools.

“Our needs as employees don’t conform neatly to the different tools that we use to fulfill them. Copilot extensions are a way to collapse that complexity.”

Matthew Marzynski, product manager, Microsoft Digital

Many companies have data spread across an expansive digital landscape. Within Microsoft, our employees access a vast quantity of content within Microsoft 365 apps and in other data and systems. That breadth can create issues with discoverability and block our employees from taking action effectively. On top of that, some processes benefit from narrowing search parameters instead of widening them.

Microsoft 365 Copilot extensibility is the framework that makes closing those gaps possible. It enables users and developers to customize Copilot’s behavior with additional instructions, grounding, and actions while providing a clear and discoverable entry point in the user interface.

“Organizations have mountains and mountains of data available, with an ever-increasing number of tools and experiences,” says Matthew Marzynski, product manager with Microsoft Digital. “The problem is that our needs as employees don’t conform neatly to the different tools that we use to fulfill them. Copilot extensions are a way to collapse that complexity.”

Through Copilot extensibility, employees no longer need encyclopedic knowledge of each and every app, tool, or repository that pertains to their work, enabling them to avoid time-consuming manual exploration. Instead, users and organizations can configure Copilot extensions to intelligently surface the information they need within a single pane. And at the center of this shift is a new kind of interface: the agent.

Agents enable users and developers to customize Copilot’s behavior with additional instructions, grounding, and actions, and they provide a clear and discoverable entry point through a single, accessible user interface. As a result, it’s now possible to extend the power of Copilot beyond our first-party product portfolio to deliver highly transformative and personalized employee experiences.

Users have enormous flexibility in terms of the kinds of agents they can create, their level of complexity, and how they create them. Creation approaches include Microsoft Copilot Studio Agent Builder, Copilot Studio itself, or working with both Copilot Studio and Azure AI.

For the simplest agents, creators can access Microsoft Copilot Studio Agent Builder right in Teams through Microsoft 365 Copilot Chat. They can use it to walk through a streamlined process driven by natural language. Simple prompting and configuration panes make this interface accessible to anyone who wants to create agents.

“We’re looking at every workflow, process, and interaction to find ways of applying a Copilot-first perspective.”

Nitul Pancholi, AI Center of Excellence lead, Microsoft Employee Experience

Accessing Copilot Studio directly provides more power and flexibility. Based on Microsoft Power Platform, this tool provides a low-code or pro-code environment for creating and enhancing agents with custom experiences.

By focusing Copilot intelligence on specific repositories and apps, agents created in Copilot Studio provide greater discoverability outside the Microsoft 365 data estate while unlocking custom workflows. Most importantly, they make it possible to explore different information silos and take different kinds of actions from one interface, accessed through Copilot.

“We’re looking at every workflow, process, and interaction to find ways of applying a Copilot-first perspective,” says Nitul Pancholi, a lead in the AI Center of Excellence in Microsoft Employee Experience. “It’s an opportunity to redefine how we do work and drive greater impact than ever before.”

Whether an employee creates a personal agent tailored to their role or a line of business builds an enterprise tool to support their team’s work, Copilot Studio brings their vision to life. It lets users create agents using two building blocks, connectors and plugins, plus the ability to customize those elements.

Kinds of Copilot agents

“Through extensibility, we’re enabling anyone to create a Copilot-powered solution tailored to their team, suited for their organization, and focused on the right content,” says Dodd Willingham, program manager for internal deployment of search and chat in Microsoft Digital. “Graph connectors and plugins make the right content easily identifiable for their agents so they can target the data they need appropriately.”

Our Copilot extensibility journey

Microsoft is actively building and deploying agents. The Microsoft Digital team has been instrumental in creating and implementing these early scenarios using Copilot Studio through Microsoft Elite Builders, our internal program that encourages Microsoft employees to build and share their custom agents with fellow employees.

“The copilot extensibility concept is really about creating agents that are low-maintenance and high-value for users.”

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

Simple retrieval agents are enabling much of this early work. This kind of extension powers scoped, task-specific experiences to accomplish specialized tasks in Copilot by accessing Microsoft Graph data alongside additional semantic ground.

The IDEAS Copilot is one example. It democratizes access to our IDEAS knowledge base’s insights on app usage to empower informed decision-making. Through natural language queries, it enables users to take action on crucial usage data without technical expertise.

“The copilot extensibility concept is really about creating agents that are low-maintenance and high-value for users,” says Aisha Hasan, Power Platform and Copilot Studio product manager for Microsoft Digital. “Anyone on the tenant can create their own agents, while engineering teams can build enterprise-level solutions using Copilot Studio to solve business problems and boost productivity on a wider scale.”

Our most ambitious project so far has been an agent that unlocks scoped, role-specific Copilot experiences we can embed in public and private apps. The Employee Self-Service Agent in Microsoft 365 Copilot grants employees access to HR, IT, and facilities-related information and tools through their choice of interface—Copilot or our company sites. It’s now available in a limited public preview.

The agent connects to SharePoint, Microsoft Teams, Microsoft Outlook, and other resources that comprise the Microsoft Graph to retrieve the right information. Depending on what area the employee’s query is related to, the agent integrates their personalized data from a variety of knowledge bases and third-party apps. From there, it provides the employee with an answer that creates a single, reliable starting point for resolving their query or need.

“As Customer Zero, we need to balance product innovation with security and operational needs.”

Mykhailo Sydorchuk, Customer Zero lead, Microsoft Digital

Employees are finding answers more accurately and faster, without the need for extensive searches across wide-ranging toolsets. In our initial pilot, people who use the Employee Self-Service Agent for HR receive 42% greater accuracy in answering their questions. On the IT side, the overall self-help success rate increased by 36%. But the greatest benefit is the way this agent keeps employee productivity flowing by allowing users to seek out crucial information in a single pane within their flow of work.

Learning from early extensibility projects

As one of the first enterprises to explore Microsoft 365 Copilot extensibility, developing and implementing these solutions comes with its own challenges and learnings.

“As Customer Zero, we need to balance product innovation with security and operational needs,” says Mykhailo Sydorchuk, Customer Zero lead for Microsoft 365 integrated apps in Microsoft Digital. “We’re balancing the priorities of driving productivity for the business, supporting the product teams in deploying new features, and also maintaining the guardrails to protect employees and our organization.”

Within Microsoft Digital, we have two chief advantages as we address these IT challenges:

• A trustworthy technology ecosystem operating at an incredible scope and scale across a huge product suite, ripe with the kinds of data that empower AI tools.

• A mature IT organization that has decades of experience in adopting and operationalizing new technologies and mitigating risks.

One of the most important lessons we’ve learned has been about adapting our existing governance structures to the framework of Copilot extensibility.

Agents rely on connections with existing tools that have well-established parameters for reasoning over data and governing information. Because Copilot respects Microsoft 365 governance and data loss prevention protocols, it honors all the access controls, security policies, and personally identifiable information (PII) data-handling structures that an organization puts in place across its tenant. As a result, businesses can rely on Microsoft 365’s robust foundation of security even as they forge ahead into new AI capabilities.

But this is a new approach to technology, so we’ve adapted our review process for new agents alongside our implementation to ensure governance and security keep pace with innovation. Those reviews largely revolve around key questions we ask about all our technology, with an added layer around Responsible AI, where we ask ourselves questions like these:

• Security: How does data move from one app to another across the Microsoft 365 tenant boundary, and how does an agent interact with that data?
• Privacy: Where does the agent handle and store PII?
• Accessibility: Does the UI make this technology equally available to all users?
• Responsible AI: Does the agent meet our standards for fairness, reliability and safety, inclusiveness, transparency, and accountability?

From a security and governance perspective, it can be daunting to implement internally built extensions that have access to your organizational data and incorporate them into your business workflows. By asking the same questions we’ve embedded into our review framework and relying on the robust security and governance features of Microsoft 365, you can ensure you maintain control over your organizational data.

It’s also important to realize that adopting this new framework will take time. There’s a natural progression from simpler extensions to more complex tooling. It’s all part of accelerating along an adoption maturity curve with the next iteration of AI tools.

“A cornerstone of Copilot extensibility is understanding your data and the scenarios you think will be most impactful for optimizing processes.”

Amy Rosenkranz, principal product manager, Microsoft Digital

The technical aspects of enabling Copilot extensibility require forethought, but they don’t exist in a vacuum. If your team maintains robust governance policies through your Microsoft 365 tenant and they’re experienced with Power Platform, much of the legwork is already done.

But if your organization is new to this space, our internal experience governing Copilot can act as a guide for keeping your data secure. We’ve also created resources tailored to helping first-time users get up to speed with Copilot Studio. We’ve also made the Employee Self-Service Agent in Microsoft 365 Copilot available to customers in limited public preview to provide a straightforward on-ramp to extensibility.

It starts with considering where Copilot extensions might fit into your workflows and what data it needs to access, starting with simple implementations, then deliberately building from there.

“A cornerstone of Copilot extensibility is understanding your data and the scenarios you think will be most impactful for optimizing processes,” says Amy Rosenkranz, principal product manager for Customer Zero Extensibility in Microsoft Digital. “Then ensure your endpoints are ready to hook into natural language processing and build your instructions.”

A principled approach to employee usage and adoption is also important. Eagerness among IT professionals and early adopters won’t necessarily drive business-wide transformation. As a result, we’re actively working to inform employees about the value of these tools and provide skilling opportunities.

“One of the main things we observed is that there’s a certain level of change management involved,” Pancholi says. “In order to build these habits, we’ve focused on creating simple workflows with tangible impacts so employees can see the value and start building Copilot-first habits.”

Finally, we’ve discovered that keeping agents lean in scope helps them function more easily. It’s important to think about back-end processes as you create extensions. For example, including too many data sources can become a serious tax on processing power. From both a performance and scenario standpoint, it’s a better strategy to keep agents narrowly focused.

Next steps into the era of extensibility

As we continue our Microsoft 365 Copilot extensibility journey, we’re looking to our internal experience to guide the product for our customers, especially in IT. Our team is currently exploring ways to further unify the ecosystem until administration and management of extensions can all occur through a single layer. That will reduce operational costs and enable successful adoption on a greater scale.

We’re also exploring ways to shift more aspects of governance to Copilot itself. Since many agents access data and third-party apps outside our tenant, those sources might not benefit from Microsoft 365 data protection policies. Allocating more of the burden of governance to agents themselves may help fill that gap.

“The vision around extensibility is that Copilot can be the single place where all tools coalesce into one single pane. It’s a way to make your time much more effective and reduce the cognitive tax of changing channels or swiveling seats, and it’s ultimately a way to make your employee experience more rewarding.”

Matthew Marzynski, product manager, Microsoft Digital

For now, we’re still exploring what’s possible. And employee uptake tells a strong story about extensibility’s impact. Since the release of our initial Copilot extensions a few months ago, usage of retrieval agents has shot up by a factor of 10. Initial results from our rollout of the Employee Self-Service Agent in Microsoft 365 Copilot are equally promising.

It’s all coming together to demonstrate the profound value Copilot can provide for businesses.

“The vision around extensibility is that Copilot can be the single place where all tools coalesce into one single pane,” Marzynski says. “It’s a way to make your time much more effective and reduce the cognitive tax of changing channels or swiveling seats, and it’s ultimately a way to make your employee experience more rewarding.”

Key takeaways

Here are some tips for getting started with Microsoft 365 Copilot extensibility at your company:

• Be curious: Don’t limit your imagination, because it’s a chance to redefine workflows.
• Be patient but continue driving forward. This is the beginning of a more long-term journey, and it’s important to get more comfortable with the technology.
• Hackathons produce amazing results. It’s important to give people time to experiment together.
• Have a strong change management program. No matter how wonderful the tech is, people need to see helpful use cases and real value.
• Use your existing investment, processes, governance, and management practices for Microsoft 365 and scale it out.
• Build a well-documented review process.
• Start with only allowing approved apps, or enable guardrails for self-service to ensure IT maintains control and security, then grow from there. When it comes time for citizen developers, open the door to retrieval agents.
• Think in terms of data. It’s about what data you have, if it’s properly governed, where it’s being accessed, and what tenant boundaries it crosses.

Try it out

Get started with Microsoft 365 Copilot extensibility at your company.

Related links

• Discover Microsoft Copilot Studio.
• Learn how we’re embracing this ‘agentic’ moment at Microsoft.
• Explore the use of good governance to manage the wave of agents washing over Microsoft.
• Read more about our Employee Self-Service Agent.
• See how we’re powering our AI transformation with our AI Center of Excellence.

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 AI value with Microsoft 365 Copilot extensibility at Microsoft appeared first on Inside Track Blog.

This is a time of enormous possibility, but it comes with difficult questions.

How do we put AI into action to solve problems and drive impact? How do we ensure we’re pursuing initiatives that deliver real business value? And finally, how do we equip our teams with the skills they need to realize this potential? Across Microsoft, we’re adopting a methodology to ensure we make the most of this moment: continuous improvement.

“We exist to empower every individual and team at Microsoft to embrace continuous improvement powered by AI in all that we do—simplifying and improving business processes to accelerate growth and boost performance.”

Kirsten Paust, corporate vice president of Continuous Improvement, Microsoft

Our vision for AI and continuous improvement

Continuous improvement is central to our ambition for an AI-powered, human-led future. At its core, it provides a systematic, repeatable framework of methods and behaviors that help teams operate with speed, clarity, and discipline as they progress toward an enterprise enabled by AI.

As a methodology, continuous improvement enables our teams to identify and solve high-impact problems, establish a customer mindset to drive accountability, and codify practices that make progress sustainable and measurable. It’s a fundamentally iterative process based on identifying opportunities, executing initiatives, analyzing results, and making course corrections.

“We exist to empower every individual and team at Microsoft to embrace continuous improvement powered by AI in all that we do—simplifying and improving business processes to accelerate growth and boost performance,” says Kirsten Paust, corporate vice president of Continuous Improvement at Microsoft.

Continuous improvement isn’t new, but generative AI is. That’s why our approach at Microsoft involves redesigning end-to-end workflows with AI at their center, aligning technology, people, and processes to reduce human effort and deliver outcomes more efficiently.

“At Microsoft, we see a lot of benefit to applying continuous improvement and AI together,” says Becky West, leader of the Continuous Improvement Center of Excellence within Microsoft Digital, the company’s IT organization. “The way we do that is, is first initiate our continuous improvement workflows, which makes our processes as efficient as possible, and then we apply AI. Conducting continuous improvement in that order keeps you from automating a broken process and focusing AI’s abilities in the wrong direction.”

Our Continuous Improvement CoE works closely with our overarching, companywide Continuous Improvement team and our Microsoft Digital AI CoE, which is responsible for guiding our internal AI transformation. These organizations partner with each other and teams across Microsoft Digital to build our AI and continuous improvement muscles as an organization.

The result is a process of constant, iterative improvement aligned with our organizational goals, with AI as one of its most powerful drivers.

“Continuous improvement has been around for decades, but AI is providing new opportunities for process improvement because the technology has reached the level of maturity where it can fill gaps and smooth corners,” says Nitul Pancholi, principal and leading member of the AI CoE. “AI is ready for action, and continuous improvement is here to show us how to use it best.”

Continuous improvement in action

Continuous improvement provides us with a structured methodology for establishing rapid learning cycles that deliver tangible improvements across our processes, whether those enhance security, quality, delivery, innovation, or productivity. It helps us apply rigor to solving the right problems to capture the value we want.

“Culturally, continuous improvement helps us emphasize progress over perfection and do a little bit better every day.”

Matt Hansen, director, Continuous Improvement, Microsoft

We define a high-performing continuous improvement system according to four principles:

1. A clear definition of winning based on expectations
   We define success through the lens of what our teams value most and align our priorities accordingly.
2. Disciplined execution
   Teams operate within a simple, repeatable rhythm consisting of four stages: Plan, Do, Check, Adjust.
3. Constrained problem-solving with urgency
   We focus on root causes, not symptoms, and tackle problems head-on.
4. Sustained replication and acceleration
   When we discover improvements, we standardize and embed them into our operations to compound improvements.

“Culturally, continuous improvement helps us emphasize progress over perfection and do a little bit better every day,” says Matt Hansen, a director of Continuous Improvement at Microsoft. “It’s really about understanding your teams, their needs, and the value they can deliver to the business, then focusing their efforts to become as efficient as possible and do it all at scale through replicable techniques.”

The process centers on the disciplined execution of a four-stage cycle: Plan, Do, Check, Adjust.

Our continuous improvement system

Our Continuous Improvement System represents a disciplined approach to process improvement that leads to a virtuous cycle. “Do” is only one phase, which means we don’t take action for action’s sake. Instead, deliberate planning guides our projects, and a highly intentional approach to measurement helps us adjust initiatives as we learn what works and what doesn’t.

To put this system into practice, our continuous improvement methodology includes several processes and tools that underlie a structured approach to identifying opportunities, executing changes, and learning from our experiences to drive greater impact. These processes are informing and guiding several initiatives already in progress within Microsoft Digital.

The Bowler Method

Named for the scorecards used in bowling, Bowlers provide a disciplined method and visual tool for defining, tracking, and driving the outcomes that matter most. They define ownership, use clear KPIs arrayed along a linear progression, and identify urgent actions to close performance gaps. We review our progress on these cards during monthly operating reviews to develop a consistent habit of accountability.

We translate strategy to execution by cascading ownership, accountability, and measurement to the point of impact where the work happens and results are produced. That involves two levels of Bowler scorecards:

• The top-level Bowler defines the enterprise outcomes that matter most, tied to customer value, growth, cost, and risk.
• Cascaded Bowlers translate those outcomes into operational drivers that help deliver the desired results.

A Bowler scorecard

Action plans

Action plans are living tools that drive execution by clearly demonstrating what needs to happen, who owns it, when it needs to be done, and what impact it should have.​ This is where we initiate the Plan, Do, Check, Adjust cycle.

Gemba walks

As part of the planning process, Gemba walks involve observing teams and seeking an understanding of how they do their work. This concept originated from the Japanese phrase “Going to where the work happens.” During these sessions, we walk through a scenario to understand pain points, unpack the employee experience, and observe waste.

Kaizen events

A Kaizen event is a high-intensity, multi-day, in-person, team-based sprint designed to improve processes, solve problems, and close gaps. During the event, we define the opportunity, prepare for action by gathering data, observing work, and mapping processes, run a working session with the relevant parties, and deliver an improvement.

Value stream mapping

As part of a Kaizen event, value stream mapping involves charting the current state of a process to identify waste and pain points, pinpoint and prioritize improvements, design the future state, and create an improvement roadmap.

“Continuous improvement equips us to study our business processes in detail, uncovering how actions connect, where friction slows us down, and where automation can unlock new potential,” says Faisal Nasir, principal architect within Microsoft Digital, member of the AI CoE leadership team. “By combining this discipline with AI, we can turn those insights into transformative outcomes.”

Learning from our approach to continuous improvement

AI-driven continuous improvement initiatives are well underway at Microsoft, and some are producing results already, especially within Microsoft Digital. As the organization responsible for maintaining operational excellence and an exceptional employee experience within Microsoft, we’re applying AI-empowered continuous improvement to several different areas.

Our teams are using this framework to improve everything from third-party software license auditing to network hardware asset management. In one case, a new agent is helping designated responsible individuals (DRIs) on our Digital Workspace team save time resolving network outages, resulting in a 40% boost to a key network performance metric.

“What we’re building is a system of rigor around rapid cycles of accelerated learning to help us determine what works and what doesn’t for delivering the outcomes we want,” says Sammi Clute, a director of Continuous Improvement at Microsoft. “At the most basic level, it requires discipline around metric setting and review, but it also relies on establishing better connections between financial outcomes and executional work.”

As a result of our experience, we’ve established a process for launching continuous improvement initiatives. If you’re considering ways to use continuous improvement in support of your own AI projects, you may want to incorporate elements of our workflow.

First, think about who should be involved. Everyone has a role to play. When done properly, these efforts will have both horizontal and vertical implications, reaching across different teams and functions to foster participation at every level of the organization.

At Microsoft, we identify two major groups of stakeholders:

• The leadership team, responsible for defining business priorities and corresponding key metrics, assigning responsibility, and setting expectations for targets and pace.
• The execution teams build and test bowler cards, create and own execution plans, cascade key metrics if necessary, and conduct the work behind the initiative itself.

From there, consider working through a four-step process similar to Microsoft’s:

1. Understand your business’s priorities
   Clarify what matters most in terms of customer and stakeholder expectations, identify the capabilities your AI initiatives need to deliver, assemble clear and distinct priorities, and stack rank them.
2. Build your top-level bowler
   Once your business priorities are clear, you need to translate them into key metrics and assign ownership. Establish your measurements, set ambitious but realistic targets, and build out your bowler card.
3. Cascade your top-level bowler
   Connect your strategic priorities to the work that drives impact. This is where you clarify accountability, define how you measure progress, and ensure everything aligns with business goals. It’s largely a process of breaking your priorities into components and identifying leading indicators of success.
4. Build action plans for delivery
   With your measurement framework in place, it’s time to translate your key metrics into concrete, time-bound activities with named owners and clear outcomes. Start from your goals, define the components of progress, build actions to push those forward, identify enablers or prerequisites, and quantify the impact you want.

These four steps articulate the process, but AI has the potential to make it transformative. As you’re building out your action plans, put thought into ways that AI can enable continuous improvement by doing what it does best: automating routine tasks, eliminating waste, and augmenting decision-making.

Continuous improvement as a cultural mindset

As we move into the AI-powered future, we’re betting big on continuous improvement as a core methodology to ensure we put it to good use. By modeling this process internally, we’re creating a blueprint that enables our customers to reimagine their own operations.

“As Microsoft’s IT organization, we’re typically the first to scale out new technologies and processes,” says Nathalie D’Hers, corporate vice president of Employee Experience. “Now we’re excited to take on a leading role in defining how AI and continuous improvement work together to accelerate transformation, empower employees, and unlock greater value than before.”

All of this has required both cultural and operational development.

“Continuous improvement will serve as an engine for accelerating transformation and impact from AI.”

Carolina Dybeck Happe, executive vice president and chief operations officer, Microsoft

The “learn-it-all” mentality that Satya Nadella instilled in Microsoft when he became CEO in 2014 has been a crucial foundation as we operationalize and reinforce AI-enabled continuous improvement opportunities. In many ways, it’s an extension of the growth mindset that permeates our company’s cultural makeup.

We’ve also had to ensure we have the guidance, sponsorship, and skilling in place to help teams and individual employees feel comfortable taking accountability for continuous improvement initiatives.

It doesn’t happen by accident, but the effort is worth it.

“AI is a catalyst for innovation, growth, and value creation,” says Carolina Dybeck Happe, executive vice president and chief operations officer at Microsoft. “As we build a system of rigor around how we use these next-generation tools, continuous improvement will serve as the foundation for evolving Microsoft into an AI-driven Frontier Firm, transforming work as we know it to achieve more.”

Key takeaways

Here are some tips for adopting a continuous improvement mindset to transform your company and the way your employees work:

• People and process are equally important: Systems and tools are essential, but you’ll also need to provide support to help change behaviors and embrace this methodology.
• Empower individuals: Impress the importance of accountability on individuals. Ideally, every employee should continually ask, “How is what I’m doing contributing to our goals?”
• Embrace the red: Negative results are part of progress. When you see red on a bowler card as an initiative stalls, use that as an opportunity to learn and adjust.
• Set aside old assumptions: Approaching continuous improvement with humility leads to the best results. It doesn’t matter why a process is broken or inefficient, only that we fix it and make it better using AI.
• Ambiguity is inevitable: Lean into the messiness and uncertainty of discovery. By its very nature, improvement is about progress, not perfection.

Try it out

Learn more about our role as the company’s Customer Zero.

Related links

• Learn more about how we’re using Microsoft 365 Copilot and AI agents to drive continuous improvement internally at Microsoft Digital.
• Take a look inside the councils steering AI projects at Microsoft.
• Learn about our Microsoft Digital AI Center of Excellence.
• Explore reasons why responsible AI matters and how we’re infusing it into our internal AI projects.
• Read about ways we’re transforming our employee experience with AI.
• Discover our internal learnings and access a step-by-step guide for unleashing API-powered agents.
• Find out how we’re supercharging our SharePoint sites at Microsoft with Microsoft 365 Copilot.

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 Defining the future: How we’re building an AI-powered continuous improvement culture at Microsoft appeared first on Inside Track Blog.

At Microsoft, we’re deploying a spectrum of agents to fulfill different needs, from acting as knowledge sources for our individual employees, to helpers that handle specific tasks for our teams, organizations, and for the full company.

Of the different kinds of agents, the easiest to implement are retrieval agents, which employees can build using Microsoft Copilot Studio agent builder or SharePoint. After a few quick steps, the agents they create retrieve information for them from data grounded in our Microsoft 365 tenant, like a SharePoint library or collection of libraries, reason over it, summarize it, and answer their questions.

As one of the first enterprise IT organizations to deploy this capability to our employees, we’re starting to see their impact first-hand, and along the way, we’re learning lessons that our customers can use to unlock their own agentic abilities.

Copilot + retrieval agents: A new way to drive enterprise AI value

So, what are retrieval agents?

First, it’s important to understand where these Microsoft 365 Copilot extensions fit within the emerging agentic environment.

Copilot agents expand Copilot’s knowledge and skills, and they can even operate autonomously to complete tasks or automate processes. Retrieval agents operate at the simplest end of the agentic spectrum and are the easiest for employees to create.

Types of agents

“Retrieval agents wrap around knowledge sources and data sets, and they include system prompts so they behave the way their creators want,” says Aisha Hasan, Power Platform and Copilot Studio product manager for Microsoft Digital. “They’re AI helpers that our employees can create to find what they want without having to search around manually.”

“If we think of Copilot as the UI for AI, retrieval agents are a further layer on that UI, that can access and reason over their organization’s data.”

Mykhailo Sydorchuk, Customer Zero lead for Microsoft 365 integrated apps, Microsoft Digital

A retrieval agent is essentially Copilot, plus its creator’s instructions, plus grounding in a particular data set. These extensions can accomplish a wide variety of jobs, from acting as an event planning assistant to sourcing insights into business optimizations to surfacing internal guidance around leadership best practices.

“If we think of Copilot as the UI for AI, retrieval agents are a further layer on that UI, that can access and reason over their organization’s data,” says Mykhailo Sydorchuk, Customer Zero lead for Microsoft 365 integrated apps at Microsoft Digital. “They can also address other data sets and systems using Copilot, without the need to build custom connectors or orchestration.”

At Microsoft, retrieval agents are accelerating our AI journey by enabling employees to tailor Copilot’s capabilities to their own work and specific knowledge sources. Their value comes from creating micro-experiences that meet specialized needs to enhance productivity and information discoverability.

“With Copilot Studio agent builder and retrieval agents, we’re empowering our employee citizen developers to experiment freely and create agents easily, then share them out, all surrounded by the right governance and management process.”

Amy Rosenkranz, principal product manager for Customer Zero Extensibility, Microsoft Digital

Creating retrieval agents couldn’t be easier. One option is through Microsoft Copilot Studio agent builder, accessible through Copilot Chat within Microsoft Teams. Employees can use natural language prompts and a simplified configuration process to provide custom instructions, tell their agents how to behave, and provide specific data and knowledge sources.

SharePoint agents are another opportunity to add AI assistance into everyday work. These enable users to turn SharePoint sites and documents into scoped agents that are subject matter experts for your business needs. Site owners or admins simply customize their SharePoint agent’s branding and purpose, specify the sites, pages, and files it should get information from, and define customized prompts tailored to its purpose and scope.​​​​​​​

“We’re targeting our core enterprise professional developer scenarios with more advanced tooling,” says Amy Rosenkranz, principal product manager for Customer Zero Extensibility in Microsoft Digital. “But with Copilot Studio agent builder and retrieval agents, we’re empowering our employee citizen developers to experiment freely and create agents easily, then share them out, all surrounded by the right governance and management process.”

Enabling retrieval agents while ensuring our organization’s integrity

While agents represent a leap forward in AI-powered productivity, capturing that value means balancing the freedom to explore with the need to protect our company.

Microsoft is one of the first and largest organizations to extend Microsoft 365 Copilot by enabling agents. As a result, our team here in Microsoft Digital, the company’s IT organization, has been hard at work ensuring those agents don’t put the company at risk.

“The beauty of retrieval agents is that, for the most part, they’re grounded in Microsoft 365 data, so they provide a single-pane view within Teams, instead of forcing users to go from one source to another to seek out information.”

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

The level of risk an agent presents largely depends on its access to data sources and the actions it can take. More advanced task and autonomous agents need to cross Microsoft 365 tenant boundaries to enable actions. But retrieval agents are much simpler.

Retrieval agents typically only access data within tenant boundaries through graph connectors. Although they occasionally need to connect with information outside the tenant, they only retrieve data and don’t transmit it externally. As a result, administrating and governing these agents is much simpler.

“The beauty of retrieval agents is that, for the most part, they’re grounded in Microsoft 365 data, so they provide a single-pane view within Teams, instead of forcing users to go from one source to another to seek out information,” Hasan says. “Whatever your window of productivity might be, you can interact with the information you need without constantly switching context.”

We started small, experimenting with retrieval agents with trusted stakeholders and reviewing each one to ensure they didn’t present unacceptable risks to the company. Through what we learned during that process and the data safety controls we maintain across our tenant, we’ve minimized the scenarios where agents require reviews, which only come into play for more complex agents that build on bespoke graph connectors, API plugins, or custom orchestration to access external knowledge sources and take actions.

Our confidence in retrieval agents’ safety comes from a few key factors.

Administration and configuration

Retrieval agents’ simplicity also helps us keep the risk of data overexposure low. Unlike more complex agents that require security assessments, threat modeling, privacy assessments, and Responsible AI reviews, we’re able to define our policies for retrieval agents at the agent builder environment level.

We empower tenant administrators and our partners on the Microsoft Security team to apply data loss prevention policies that configure what individual employees can enable for their retrieval agents. At this level, everyone in the company has the same configuration and tools available, and automation largely handles agent reviews and assessments. We based these pre-configured settings on the same security, privacy, and regulatory compliance standards we apply to any internally built application.

Approved graph connectors

Graph connectors increase the discoverability of external data by integrating it into an agent’s grounding. At Microsoft, we’ve onboarded a series of approved connectors that creators can use to incorporate additional data for their agents to reason over. They include connectors for external websites as well as tools like Azure DevOps and ServiceNow.

Our criteria and review process for connectors ensure that agents don’t put our tenant at risk. As long as a connector is approved, employees are free to use it to create their agents.

Ensuring Responsible AI standards at the platform layer

Microsoft has been at the forefront of establishing Responsible AI principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. To ensure we enabled retrieval agents that would respect Responsible AI standards, we needed to translate those concepts into concrete policies we could apply at the platform level.

Microsoft’s Office of Responsible AI has been an indispensable resource during this process. They maintain a comprehensive and evolving list of policy statements around restricted uses for AI capabilities. Those include things like using AI to infer emotions or personal characteristics, assess employee performance, or social scoring.

As our implementation of retrieval agents matured, we instituted controls at the platform layer to block these restricted uses for AI, identifying what kinds of information an agent can retrieve. Now, Copilot Studio agent builder knows how to evaluate responsibility against a wide array of parameters and make determinations based on the parameters we’ve set out.

For example, if a manager attempted to create a retrieval agent that would assess employee performance based on meeting attendance, guardrails at the platform layer would curtail that ability. Naturally, as we develop our policies around responsible AI further, the parameters of Responsible AI will shift and grow, and we’ll continue to nuance our configurations.

Thanks to these foundations, we’re now at the point where we feel comfortable giving every Microsoft employee access to Microsoft Copilot Studio agent builder and the freedom to create retrieval agents. It’s all part of our principle of employee self-service with guardrails.

“It’s a constant evaluation,” says Hasan. “Our goal is to allow as much freedom as we can with retrieval agents so employees can increase productivity without going down the path of greater customization that requires more intensive review.”

Different organizations are at different stages of their AI maturity journey. As you experiment with Copilot extensibility, it will be important to define your organization’s level of experience implementing AI tools, your employees’ state of readiness and training, key risk areas, and sensitive scenarios.

“Users who want to build agents with no code can select from premade templates using natural language, or they can fill out a few fields.”

Brian Moran, senior product manager, Employee Experiences team, Microsoft Digital

From there, you’ll be able to use out-of-the-box configuration capabilities in Copilot Studio agent builder to establish guardrails that work for you. It will take careful collaboration across security, privacy, legal, and IT teams, but we’re already learning that the benefits are worth the effort.

Ease and access drive creativity and new ways to work

Now that we’ve empowered our employees to build retrieval agents organization-wide, examples of creativity and innovation are popping up all over the company. Ease of use and freedom have a lot to do with this proliferation.

Using Copilot Studio agent builder

“Users who want to build agents with no code can select from premade templates using natural language, or they can fill out a few fields,” says Brian Moran, senior product manager on the Employee Experiences team at Microsoft Digital. “They can get their agents up and running in minutes.”

Creative examples of the ways that employees and teams are using retrieval agents include:

• IDEAS Copilot democratizes access to our Insights, Data, Engineering, Analytics, AI, and Systems (IDEAS) knowledge base to help users act on crucial usage information without the need for technical expertise. The agent fully integrates with Microsoft Teams, so employees can dig into data across sales, marketing, finance, operations, and more using natural language queries in their familiar working environment.
• Security Comms Agent helps our communications team create blog posts by providing a prompt that includes the content’s purpose and context. It accesses internal documents about business objectives, positioning frameworks, voice guidelines, and our Microsoft Digital communications and marketing plan, as well as the internet and specific Microsoft-owned learning sites for added context. From there, the agent creates a first draft that aligns with our Microsoft Digital positioning, objectives, and voice.

“Empowering our people to create retrieval agents in a responsible environment is the ideal combination of human creativity and AI capabilities, and we’re confident it will unlock a new era of innovation.”

Nathalie D’Hers, corporate vice president, Employee Experience

• Know Your Customer leverages AI to provide a comprehensive view of customer profiles. It accesses an overview of a customer’s tenant, usage metrics for Copilot, service incident reports, and more to provide usage statistics and health data for Microsoft 365 apps, email, meetings, Microsoft Viva, and other products to enhance customer engagement and support. The agent can even generate a tenant-specific Microsoft PowerPoint dossier for ease of use.
• Prompt Buddy Agent helps employees discover ready-to-use prompts that eliminate the need for experimentation and prompt engineering. Employees use natural language queries to discover AI prompts their colleagues have shared across industries, roles, personas, and topics, all without leaving Copilot Chat. As a result, they can save valuable time by streamlining AI-assisted workflows.
• Communications Plan Assistant accesses a library of prompts our Microsoft Viva communications team has developed to quickly draft content. The team communicates with the agent conversationally, providing feedback and selecting from the options it provides, then populates pre-defined sections in their communications plan template. At the end of the interaction, they can request a summary with all the final content that will go into the plan.

“By trusting our employees to imagine and create their own extensions for Microsoft 365 Copilot, we’re making it possible to personalize enterprise AI like never before,” says Nathalie D’Hers, corporate vice president of Employee Experience. “Empowering our people to create retrieval agents in a responsible environment is the ideal combination of human creativity and AI capabilities, and we’re confident it will unlock a new era of innovation.”

Key takeaways

Here are some tips for getting started with retrieval agents at your company:

• Establish early communication and collaboration with members of your security, legal, compliance, IT, and any other teams who can help you define ways to configure Copilot Studio agent builder safely.
• Agents rely on data, so ensure your enterprise data is clean, well-governed, and accessible through scalable pipelines.
• Start slowly. Enable retrieval agents for smaller, select groups to work through any configuration issues or concerns before widening access. Plan to review everything you do at each step, and use those learnings as a basis for configuration and automation as time progresses.
• Balance employee empowerment with organizational safety. That balance will evolve as your organization’s AI maturity progresses.
• Use simple retrieval agents as a springboard to more complex extensions that require a structured review process.

Try it out

Want to explore the possibilities for creating agents with Microsoft Copilot Studio? Try it free here.

Related links

• Witness AI-powered agents in action to see how we’re embracing this new ‘agentic’ moment at Microsoft.
• Learn how we’re finding deeper AI value at Microsoft with Microsoft 365 Copilot extensibility.
• Discover ways we’re unlocking enterprise AI extensibility at Microsoft with Microsoft Copilot Studio.
• Check out how we’re riding the wave of AI agents washing over Microsoft using good governance.

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 How our employees are extending enterprise AI with custom retrieval agents appeared first on Inside Track Blog.

To adapt to that shifting mindset, we’re reimagining how the tools employees use meet them in the moments that matter. That’s especially true for things they use every day, like Microsoft Outlook, the app that has long been the tool our employees “live in” at work.

With that in mind, how do we provide new opportunities for productivity and AI-first workflows without disrupting the deeply ingrained habits that drive so many of our employees’ and customers’ days? How do we respect those patterns while enabling new ones?

Innovative capabilities in the new Microsoft Outlook and Microsoft 365 Copilot features are streamlining communication through enhanced email while helping people prioritize their work and time with intelligent calendaring. These features operate with a profound understanding of an employee’s role in the business, the projects they’re working on, their team landscape, and their communication style. They augment the user’s workflows through the strength of large language models, giving them superpowers that a human assistant would ordinarily handle.

This is the story of how we’re using a continuous improvement mindset to make Outlook more supportive, intuitive, and impactful for our employees at Microsoft and our customers.

“People have an emotional attachment to their email. Everybody interacts with email according to their own highly personalized workflows, so we have to be very careful to factor that human element into any evolution or transformation of these tools.”

Mark Stratford, senior product manager, Microsoft Digital

Readying Outlook for a new era of work

As our product teams explored ways to align Microsoft Outlook with the age of AI, they started with the needs of the employees who use it.

“People have an emotional attachment to their email,” says Mark Stratford, senior product manager within Microsoft Digital, the company’s IT organization. “Everybody interacts with email according to their own highly personalized workflows, so we have to be very careful to factor that human element into any evolution or transformation of these tools.”

At the same time, the changing nature of work is introducing new challenges for both businesses and their employees. High productivity is becoming a greater and greater necessity.

But according to the Microsoft 2025 Work Trends Index, 80% of the global labor force says they lack the time or energy to do their work.

“Outlook continues to evolve, building on its legacy as a tool that millions of people rely on. We’re transforming it into a dynamic partner that helps users navigate new demands.”

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

Microsoft 365 Copilot is poised to support the parallel needs for personalization and productivity that will help employees excel. That requires a shift away from thinking of Outlook as a simple pane for communications and scheduling.

“As the pace and complexity of work accelerate, Outlook continues to evolve, building on its legacy as a tool that millions of people rely on,” says Matthew Marzynski, a principal product manager of core experiences within Microsoft Digital. “By integrating AI and continuous improvement, we’re transforming it from an organizer for emails and meetings into a dynamic partner that helps users navigate new demands. This will empower people to make better decisions, take meaningful action, and stay focused on what matters most in an accelerating modern work context—without disrupting the familiar workflows they depend on.”

To enable this shift, our product teams prioritized three characteristics that capabilities in the new Outlook Copilot in Outlook should embody:

• On-demand: Features should provide assistance in real time, collaborating with the user within the flow of their work, whether that’s in the Outlook app or Copilot Chat. They should demonstrate personalized understanding and facilitate multimodal interaction to provide tailored support as users need it.
• Proactive: AI assistants should anticipate the user’s needs without explicit direction. Outlook and Copilot should act as safety nets by providing reminders and insightful briefings, recognizing urgency, and suggesting actions and next steps.
• Automatic: Features should initiate assistance for users without the need for them to ask. Agentic autonomy doesn’t eliminate decision-making for humans. Instead, it anticipates user needs intelligently and offers tailored support.

“The human needs are largely the same—we need to interact with each other, communicate, share materials, connect,” says Margie Clinton, group product manager for Outlook. “What AI introduces are new opportunities to enhance and streamline how we perform those tasks while offloading the responsibility for managing them onto Copilot.”

AI in Outlook: Transforming communications and scheduling

Together, advanced capabilities within the new Microsoft Outlook combine with Copilot in Outlook to bring the power of AI to employees’ inboxes and calendars. Rich, contextual insights make it easier to navigate communications, advanced reasoning capabilities help employees prioritize their work and their time, and proactive recommendations and automated workflows reduce the time people need to spend on administrative tasks.

There are several different ways to add ease and automation to employees’ Outlook workflows.

Beyond Copilot Chat, users can access a suite of capabilities designed to streamline and enhance communication and prioritize their work and time.

Streamlining and enhancing communication

New email features and Copilot are game-changers for business communication. From assistance drafting emails to understanding the narrative behind a conversation, they boost employees’ abilities to understand their peers and be understood themselves.

Prioritizing work and time

Meetings dominate many employees’ days. Outlook and Copilot have several new capabilities that help users manage those meetings, conduct them more smoothly, and take follow-up actions more effectively.

The unified Microsoft 365 Calendar is at the center of the AI-enhanced scheduling and meeting experience. By centralizing the calendar function across Microsoft 365, Copilot can provide contextual, personalized experiences wherever employees access them. Outlook also brings new capabilities to the table to help people keep abreast of events.

Continuously improving and innovating in Microsoft Outlook

New features for the new Microsoft Outlook and Copilot in Outlook wouldn’t be possible without the commitment to continuous improvement that infuses so much of our work. Careful research, attainable planning, honesty and humility around how we measure outcomes, and the agility to adapt to what’s working and what’s not—these are all muscles the Microsoft Digital and product teams are strengthening throughout our ongoing AI and continuous improvement journey.

“We’re an agile organization, and we continue to iterate across teams and features,” says David Gorelik, principal group product manager for Copilot in Outlook engagements, focused on email features. “The learning that comes with hearing from our employees and customers just pours more value into that feedback loop.”

“In an environment where people need to be hyper productive but feel completely inundated with inbound requests, it’s really clear that the ways they work need to evolve. The tools they use need to evolve as well.”

Sarah Spieler, product marketing manager, Microsoft Outlook

The evidence is in how employees are using the new Outlook and Copilot. We’ve seen a virtuous cycle that starts with new features accessed through Outlook and leads to greater AI adoption overall. Without concerted adoption efforts, 50% of Microsoft Digital employees have toggled to the new Outlook of their own accord, simply because the tool is available and its features provide value.

It’s becoming evident that the new Outlook makes for an effective entry point into AI-first behaviors. That’s all the more remarkable considering the decades-long legacy of the tool and the habituation to certain workflows it’s fostered. Users who have switched over to the new Outlook are 3.5 times more likely to engage with Copilot. Outlook is also the third-largest driver of Copilot usage after Microsoft Teams and Microsoft 365 itself.

“In an environment where people need to be hyper productive but feel completely inundated with inbound requests, it’s really clear that the ways they work need to evolve,” says Sarah Spieler, a product marketing manager within Microsoft Outlook. “The tools they use need to evolve as well.”

Key takeaways

As we’ve witnessed the evolution of Microsoft Outlook usage among our employees, we’ve learned lessons that can help you empower your own people to reimagine their workflows. Here are some trends we’ve noticed and ways we’re approaching them internally at Microsoft:

• Everyone’s problems are unique. Some people struggle with drafting, some with keeping up with emails, some with coordination and scheduling. As a result, a one-size-fits-all approach to skilling and adoption around Copilot in Outlook isn’t likely to work. Throughout our wider Microsoft 365 Copilot adoption efforts, we’ve seen firsthand the power of scenario-specific adoption support. As you encourage your employees to build new behaviors that incorporate AI, it will be helpful to provide use cases and examples of workflows that directly apply to their roles or organizations. Your early adopters can help you assemble these scenarios from their own experience. Use these videos as a jumping-off point.
• For many people, the biggest blocker is that the new Outlook is more than a fresh skin on an old product. Once they try it out, they understand that it’s different from the previous iteration. In spite of similarities in look and feel and features, the new Outlook provides opportunities for employees to change their relationship with email and scheduling. In your adoption efforts, emphasize that the goal is the same but the pathways are different, with much more capacity for ease of use and productivity.
• Even when people get on board with new ways of working, it can take time for them to reconfigure their personalized workflows and fully adopt Copilot. The new Outlook is a very effective inroad into those behaviors. To accommodate people’s attachment to their Dual use, the ability for employees to use both classic and new Outlook side by side is a substantial accelerator for this process. Instead of expecting employees to adopt the new Outlook in one go, encourage them to use their legacy workflows where they feel most comfortable while trying out new processes. From what we’ve experienced, that will help them grow bolder about building new workflows and experimenting with Copilot.

Try it out

Here’s how to get started with Copilot in Outlook.

Related links

• Learn how we’re wrangling our email with the Prioritize My Inbox feature in Microsoft Outlook.
• Find out how we’re transforming how Microsoft executives use their time with Microsoft Outlook calendar analytics.
• Learn about the ways we’re evolving how we use Microsoft 365 Copilot Chat at Microsoft.

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Microsoft Digital readiness guide

AI transformation is one of the most profound business changes in decades. Making the most of AI tools will require careful planning, thoughtful communication, comprehensive employee enablement, and diligent tracking.

Fortunately, Microsoft Viva fills all of these roles and more.

“Viva’s all about helping people thrive amidst transformation. At the intersection of how people communicate with each other, and companies communicate with employees, at the junction of how people feel at work with how they do their work, that’s where Viva makes an impact.”

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

Microsoft Viva is a suite of applications designed to help organizations create an engaged and productive workforce. These apps can help you continuously improve employee experiences and business performance with powerful insights, meaningful communications, and genuine connections.

“Viva’s all about helping people thrive amidst transformation,” says Kirk Gregersen, corporate vice president of product for Microsoft Viva and Microsoft 365 Copilot Experiences. “At the intersection of how people communicate with each other, and companies communicate with employees, at the junction of how people feel at work with how they do their work, that’s where Viva makes an impact.”

As you embark on your AI transformation and drive adoption for Microsoft 365 Copilot, we created an eBook to help you plan and implement your change initiatives effectively: Ushering in the era of AI with Microsoft Viva. We based this readiness guide on our internal Copilot deployment and adoption efforts, and it’s based on insights from our teams of change managers, IT professionals, product experts, and business leaders.

Key takeaways

Our readiness guide will walk you through four stages of using Viva to drive your transformation:

1. Get ready: Identify opportunities, secure sponsorship, and apply insights to the planning process.
2. Onboard and engage: Drive awareness, provide opportunities for knowledge and skill building, and scale across communities.
3. Deliver impact: Measure and understand your progress, communicate learnings and success, and address knowledge or skill gaps.
4. Extend and optimize: Deepen the maturity of your transformation and provide opportunities for further success.

In each section, you’ll read examples of how we used apps across the Viva suite, the lessons we learned along the way, and hands-on checklists and resources that will help you propel your adoption efforts to success. When you’re finished reading, you’ll have everything you need to start your journey and use Viva to enter the era of AI securely and effectively.

{Download our “Ushering in the era of AI with Microsoft Viva readiness guide.”}

Try it out

Curious about what Microsoft Viva can do for your business transformation efforts? Try it free today.

Related links

• Learn how we drove Microsoft 365 Copilot adoption internally with an assist from Microsoft Viva.
• Access our readiness guide: Deploying Viva Engage at Microsoft in three chapters.
• Read our guide for getting started with Microsoft 365 Copilot.

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The post Supercharge your business transformation with Microsoft Viva appeared first on Inside Track Blog.

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.

Microsoft SharePoint is one of the most ubiquitous and highly trusted content storage and sharing solutions in modern business.

Around the world, organizations add over 2 billion pieces of content to SharePoint and create more than 2 million sites every day. It’s the place where people connect with each other and share their content, doing everything from creating files to hosting videos to managing processes to publishing organizational intranets.

Now, Microsoft Copilot in SharePoint and other AI-enabled features are making this foundational tool even more useful for sharing knowledge, powering collaboration, facilitating automation, and conducting communication. At Microsoft Digital, the company’s IT organization, we’re using these new features to enable enterprise content sharing in exciting ways.

A new era for enterprise content sharing

In the decades since its initial release, SharePoint has had an incredible journey. From its origins as a pure content-sharing platform with very little focus on UI, the software has gradually modernized to include easier authoring, more standardization, and simplified page construction elements.

Now, SharePoint has entered the era of AI. Far from just a content repository, SharePoint is a place to create and share beautiful and engaging pages, all with the intent of providing knowledge to employees and driving impact for organizations.

“With AI, we have a chance to reimagine our existing product surface,” says Melissa Torres, a principal product manager for SharePoint and OneDrive. “Our goal is to make workflows that used to be highly manual easier than ever before.”

AI-driven capabilities are the crucial enablers for this evolution. Thanks to Copilot and other AI-powered features, creating and curating SharePoint pages is faster, smarter, and easier than ever before.

The vision behind an AI-enabled Microsoft SharePoint

Microsoft SharePoint is the hub for knowledge, collaboration, automation, and communication for organizations of all sizes, and AI has the ability to enhance all its different functions. Most importantly, AI capabilities provide an assistive layer on top of recent features that deliver more aesthetic and engrossing user experiences.

“Through the combination of authoring improvements and the power of AI, we’re making it easier than ever to create a professional, compelling SharePoint page.”

 Sam Crewdson, principal program manager, Microsoft Digital

To boost SharePoint’s power to communicate, the product team prioritized three key pillars:

• Beautiful content: They’ve added more intuitive tools to make content creation quick, easy, and streamlined, allowing non-experts to produce visually compelling pages.
• Simple authoring: The team has transformed the process for creating and editing pages, featuring AI support for authoring content.
• Deeper engagement: They’ve reimagined how people discover and consume content to better connect with vital organizational knowledge.

“Through the combination of authoring improvements and the power of AI, we’re making it easier than ever to create a professional, compelling SharePoint page,” says Sam Crewdson, a principal program manager within Microsoft Digital.

In the business content space, aesthetics and easy authoring aren’t always top of mind, but they have important roles to play for helping people access and share vital knowledge.

“Making delightful spaces is something we see in the consumer market all the time. For organizational resources, it’s important to make beautiful content and get the brand and visual identity to surface in everything you do.

Melissa Torres, principal product manager, SharePoint and OneDrive

Three AI-powered features making waves in SharePoint

Copilot in SharePoint acts as an overarching authoring and design assistant. It can draft and create pages from scratch or by using templates through user prompts. Beyond the ability to generate whole pages, these new features are helping site owners get more creative and support their teams more effectively.

As we layer AI-enabled capabilities on top of Microsoft SharePoint, we’ve been testing and using three new features that really highlight the power of this breakthrough technology.

“Some features are available to customers already, and we’re trying others out internally before they release,” Crewdson says. “But they’re already helping our Microsoft Digital teams create more beautiful, engaging, and effective SharePoint pages.”

That’s what the improvements are all about.

“Making delightful spaces is something we see in the consumer market all the time,” says Melissa Torres, a principal product manager within SharePoint and OneDrive. “For organizational resources, it’s important to make beautiful content and get the brand and visual identity to surface in everything you do.”

Creating sections with Copilot in SharePoint

Although site owners can use Copilot in SharePoint to generate entire pages, they also want to add sections to their pages or fine-tune their work. Fortunately, Copilot can get more granular.

Users simply enter a prompt (we suggest prompts based on what’s on the page), and Copilot creates a section using relevant content. Context awareness is key, because this allows Copilot to suggest and pull content from SharePoint based on what’s already on the page. It also automatically adopts matching visuals and layouts to ease the design process.

Sam Crewdson, principal program manager in Microsoft Digital, works on different aspects of SharePoint, SharePoint Online, Viva Amplify, Viva Connections, and Microsoft 365. As a result, he often needs to create SharePoint pages to communicate with colleagues across a variety of topics.

As content evolves, Crewdson frequently needs to add sections to pages to account for new or changing information. He just pops into edit mode, hits the Copilot button, and provides a prompt. Copilot does the rest.

Crewdson often prompts Copilot to add content from Microsoft Loop, Microsoft Word, Microsoft PowerPoint, and any other source that contains key knowledge.

“Thanks to the combination of the new Flexible Sections feature and Copilot-powered authoring, you are no longer constrained by this fixed, blocky framework,” Crewdson says. “You can make your content as interesting as your personality.”

For Crewdson, Copilot makes it easy to keep SharePoint pages up to date and fresh, helping him maintain agile and flexible resources. He can simply add new sections in a matter of seconds, so his pages keep up with the pace of modern enterprise knowledge.

Flexible sections

While Copilot in SharePoint assists with authoring, flexible sections, now generally available to customers, provides easy-to-use design assistance as users create and modify pages. Using a simple drag-and-drop interface, it lets site owners freely place web parts anywhere within the section, drag them from one section to another, and resize, overlap, rearrange, group, and ungroup them on a 2-dimensional grid. The tool offers complete control over a page’s layout and look.

Eric Jaffe is the director of employee advocacy and US regional communications at the company. He’s responsible for overseeing Microsoft Web, the comprehensive internal platform our employees use to access a wide range of content, resources, and tools across the company.

It’s essential that the Microsoft brand permeates every part of our internal pages while maintaining excellent navigability and discoverability. Flexible sections enable this design ethos through easy-to-use drag-and-drop tools that help site owners experiment with placement, branding, and overall flow.

Jaffe and his team often look for design inspiration from the web, then apply those ideas to their internal pages. Frequently, they’ll lead with a header image to grab attention, then create a page that flows through cleanly spaced sections with plenty of imagery and dynamism.

It’s as simple as populating your sections, then experimenting and arranging them until they look just right.

“We live in a world where we’re competing against other highly engaging form factors, so having something that’s visual and draws the employee into the experience really enhances our impact. With these new tools, if you can dream it, you can build it.”

Eric Jaffe, director of employee advocacy and US regional communications

FAQ web part

Employees will always have questions, and SharePoint is often the authoritative source for the answers they need. Now, AI is making it easier than ever to anticipate, structure, and present that content from your existing knowledge base.

Page authors can now use a new FAQ web part to quickly generate accordion-style FAQ modules from relevant sources like policy documents or key meeting and event transcripts. They can use the tool to easily refine and reorder categories, questions, and answers to ensure accuracy and relevance, then publish them to their pages.

“We live in a world where we’re competing against other highly engaging form factors, so having something that’s visual and draws the employee into the experience really enhances our impact,” Jaffe says. “With these new tools, if you can dream it, you can build it.”

Jon Norris is a senior product manager responsible for the TechWeb Hub, our internal company resource for technical support and the primary vector for people to access our helpdesk organization. Within that hub, there are more than 50 individual SharePoint sub-hubs and sites.

FAQ modules are a big part of any technical support page. They give employees a chance to solve their own problems before escalating to the helpdesk, which saves time for everyone involved.

In the past, Norris’ team members had to search through content, anticipate user questions, and populate their FAQ modules manually. Now, they simply provide a prompt like, “Use this known issues document to create an FAQ,” and the FAQ web part takes it from there. The site authors just need to look over the output to verify that everything is accurate, add relevant links, or make any other needed tweaks.

Importantly, the new FAQ supports intelligent refresh behavior when grounding documents are updated. It keeps FAQ content fresh and accurate by monitoring changes in the source files. These are human-in-the-loop workflows, which means content authors can review, refine, and approve AI-generated updates before they are published. This means that while the refresh is not entirely automatic (to preserve editorial control), the system does intelligently detect changes and assist authors in updating the FAQ content accordingly.

The feature also has downstream benefits. The FAQ content it creates is consumable by Microsoft 365 Copilot or agents, making updates easy and increasing consistency across different pages and their FAQ modules.

“The FAQ web part saves us a lot of time on the initial page creation. Where we used to have to spend hours looking through documents to find the right answers, then copy them into an FAQ, now the tool does that for us. We can act in more of a supervisory role.”

Jon Norris, senior product manager, Microsoft Digital

A powerful suite of authoring and design tools

Each of these features offers simplicity, speed, and creativity on its own. But it’s the combination of the three that makes for a fluid, intelligent authoring and design experience.

We’re currently experimenting with these features internally, and we’ve seen some powerful results already. Most importantly, internal SharePoint site owners report that these AI-enabled capabilities make their work much easier than before.

“The FAQ web part saves us a lot of time on the initial page creation,” Norris says. “Where we used to have to spend hours looking through documents to find the right answers, then copy them into an FAQ, now the tool does that for us. We can act in more of a supervisory role.”

It’s about easily making SharePoint what you want it to be.

“People have been craving this level of customization for a while,” Torres says. “Page authors who feel like they don’t have the design chops or the time to invest in endlessly tweaking their SharePoint pages can now get the speed and assistance they need.”

It isn’t just about time savings and design improvements. It’s about engaging teams with attractive, compelling content that promotes better knowledge sharing, communication, and collaboration.

“We’re excited to see how much time the average user saves—not just the SharePoint super-user,” Crewdson says. “Almost anyone can build a compelling, interesting, attractive SharePoint collection, and these new features mean they can save the 30, 60, even 90 minutes the task used to take and do it in 30 seconds instead.”

Key takeaways

Here are some important principles to keep in mind if you are thinking of using Microsoft Copilot in SharePoint and related AI-driven features to help power collaboration and content sharing at your organization:

• Promote peer-to-peer support: Enable your site owners to build a consistent community of practice through tools like Microsoft Viva Engage and Microsoft Teams channels.
• Learn as you go: Dive in. Play with the tools. We designed these features to be intuitive, so the best way to build your skills is by trying them out.
• Apply these AI-driven tools where they’ll have the most impact: Some pages are fine with minimal design, especially information-heavy pages. For more advanced design and authoring, choose high-profile pages that will benefit from enhanced navigation. You can even choose to enhance just a few sections in specific pages.

Try it out

Get started with Microsoft SharePoint today.

Related links

• Find out how to create pages using Copilot in SharePoint.
• Learn more about using flexible sections in your SharePoint pages.
• Read about how to use SharePoint in the age of AI.
• Explore lessons learned in using SharePoint agents at Microsoft.

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

The post Supercharging our SharePoint sites at Microsoft with Microsoft 365 Copilot appeared first on Inside Track Blog.