Enter the power of sophisticated data tools and agentic AI. 

A great example of this came when our Microsoft Digital engineers and product managers were trying to get a handle on our sprawling software licensing landscape—thousands of third-party tools that our employees rely on in their work.

“We realized there were all these fragmented, scattered repositories of licensing data across many teams, all with different ownership,” says Ahmed Musa, a senior software engineer in Microsoft Digital, the company’s IT organization. “There was no visibility into what contracts existed or how they were being used. We needed a single solution.”

The answer was IntelLicense, an enterprise-wide intelligence platform that collects product information, licensing contracts, cost data, employee usage telemetry, and supplier details in one system. This all comes together in our Software Asset Management (SAM) portal, where we deliver enterprise-grade governance through a modern user experience.

“IntelLicense is a game-changer for us. Before, internal software licensing was manual and labor-intensive—it could take months to make sense of the data. Now, an answer that used to take up to six months for us to track down can be generated immediately using this platform we’ve created.”

Ahmed Musa, senior software engineer, Microsoft Digital

Our IntelLicense platform uses the advanced capabilities of agentic AI to answer queries and generate insights on the data, giving us much greater understanding and visibility while enabling us to reduce license duplication, simplify procurement, and cut spending.

This benefits our employees who need to license software, our software asset managers, and our Procurement team, which manages the process on our back end to make sure the company isn’t wasting money and resources—especially considering the company makes significant annual investments in third-party software licensing.

This solution shows how at Microsoft we’re constantly looking for ways to apply AI to help solve enterprise-level challenges at scale—the hallmark of a Frontier Firm.  

“IntelLicense is a game-changer for us,” says Musa, the principal architect for the project. “Before, everything around internal software licensing was manual and labor-intensive,—it could take months to make sense of the data. Now, an answer that used to take up to six months for us to track down can be generated immediately using this platform we’ve created.”

Uncovering the challenge

With more than 200,000 employees working across over 100 countries worldwide, attempting to centralize information at an organization the size of Microsoft is never easy. The state of our third-party software licensing system was no different.

“As we looked beyond just employees finding software and deeper into the process, we began to see the challenge was also about purchasing, how we dealt with suppliers, and how we managed the licenses at a higher level. That’s where we saw the big opportunity.”

Revanth Chandra Pydimarri, senior product manager, Microsoft Digital

We began this journey nearly three years ago. The first big need we identified came from employee feedback that indicated it was difficult to figure out how to identify and license third-party software tools. But as we began to analyze the larger picture, we realized that the problem was much more layered and complex.

“As we looked beyond just employees finding software and deeper into the process, we began to see the challenge was also about purchasing, how we dealt with suppliers, and how we managed the licenses at a higher level,” says Revanth Chandra Pydimarri, a senior product manager in Microsoft Digital. “That’s where we saw the big opportunity.”

But by expanding the scope of the project, we were setting off on a long and technically daunting quest.

“I think we counted 19 different systems that contained relevant licensing data. Working with all the different teams to pull that data together was the first big challenge we had to go after.”

Jay Selveraj, principal software engineering manager, Microsoft Digital

Tackling the data first

The first step was to gain visibility into all our third-party software contracts, our suppliers, and the actual product usage across the company. But our teams were operating in silos, each maintaining their own agreements and data about software licenses.

“This was fundamentally a data problem,” says Jay Selveraj, a principal software engineering manager in Microsoft Digital. “The enterprise data for license management is highly distributed, non-standard, and spread across the company. I think we counted 19 different systems that contained relevant licensing data. Working with all the different teams to pull that data together was the first big challenge we had to go after.”

To fully understand the software asset management process, Selveraj and Chandra Pydimarri were charged with creating a journey map to show the steps, dependencies, and stakeholders involved.   

“It was a very daunting task for us,” Selveraj says. “We identified so many different bottlenecks. And that’s when we decided we can’t just troubleshoot the existing process—we needed to build a new platform that would span the enterprise.”

To accomplish this, they turned to Microsoft Fabric, which at the time was a relatively new product. Fabric provided the power and flexibility needed for this kind of project.

“Microsoft Fabric was designed as a unified data platform for engineers, making it an ideal fit for this project.”

Misrak Ararso, senior software engineer, Microsoft Digital

And as Customer Zero for Microsoft, we were excited to be early adopters of Fabric (it had just gone into public preview). The fact that we were able to try it out on a real enterprise challenge we were facing was both a strategic advantage and a bonus.

“Microsoft Fabric was designed as a unified data platform for engineers, making it an ideal fit for this project,” says Misrak Ararso, a senior software engineer in Microsoft Digital, who also worked on IntelLicense. “It has great features like Data Wrangler, which allowed us to drill down on the data and clean it up quickly. We also used Microsoft OneLake, which meant we avoided having to duplicate data before working on it.”

Ararso appreciates how Microsoft Fabric continues to evolve with new AI capabilities, making it an increasingly powerful and beneficial tool for data engineering.

“Early adoption wasn’t always smooth,” she says. “We encountered challenges, sharing feedback when we did, and we benefited from improvements as the platform matured alongside our implementation.”

Reducing waste and saving money in procurement

Before we developed IntelLicense, our Procurement team at Microsoft also struggled to answer basic questions about our software licenses.

“It was very difficult to gauge usage, consolidate agreements, and do cost optimization. And when we tried to audit our contracts and move licenses around, it all had to be done manually and took a lot of time and effort. IntelLicense addresses that.”

Rasa Amiri, senior sourcing manager, Financial Operations

The Procurement team is responsible for negotiating contracts, pricing, and terms and conditions with thousands of different suppliers. However, it can be difficult to negotiate volume discounts and manage the other aspects of licensing if you don’t have a holistic view across the enterprise.

In a typical example, one group at Microsoft might purchase 20 software licenses from a particular supplier, but then only use 15 of them. Another team needs 5 licenses, but they have no idea that there are unused licenses they could tap from the other group, so they purchase their own. And when an employee moves teams or leaves the company, their software licenses often go unused rather than get reassigned.

“It was very difficult to gauge usage, consolidate agreements, and do cost optimization,” says Rasa Amiri, a senior sourcing manager in our Financial Operations group. “And when we tried to audit our contracts and move licenses around, it all had to be done manually and took a lot of time and effort. IntelLicense addresses that.”

IntelLicense structure

The IntelLicense solution consists of three parts: a UX layer, an agentic AI layer, and a data layer.

According to Amiri, one helpful feature of IntelLicense is the ability to see if a software license is not being used, and then directly contact that employee (or license owner) to say, “Hey, it looks like you’re not using this license. Can we reallocate it?”

“We have a real-time dashboard called the SAM portal that we can now use for that, focused on our top 200 suppliers,” Amiri says. “Now, every time we negotiate a deal, it’s uploaded into IntelLicense with all the details—the cost, the contract, the number of licenses. Not only does it help us with reallocation, it helps us quickly resolve issues we have with suppliers who want to charge us for overuse.”

Musa agrees.

“The IntelLicense platform can identify overlapping tools already in use and surface relevant alternatives, enabling more informed, cost-efficient decisions across the organization,” he says.

Introducing these kinds of efficiencies can quickly generate significant cost savings at an organization the size of Microsoft. Our internal data shows that IntelLicense drove substantial savings in software licensing fees over the last fiscal year. And we have greater ambitions for the future—Chandra Pydimarri cited industry studies that show up to 20% of third-party software spending is unnecessary. That’s huge potential savings for an enterprise organization.

“As we evolved the platform, we realized that users don’t want just another dashboard—they need decision intelligence. They need a system that can connect signals across datasets, surface actionable insights, and guide decisions in real time, so they can move faster and act with confidence.”

Urvi Sengar, senior software engineer, Microsoft Digital

Adding an AI layer

The Software Asset Management portal was a strong foundation for centralizing licensing data, but we wanted to take the solution further.

It was one thing to centralize and surface data with all the relevant data about third-party software licenses. It was a whole different challenge to build a system that helped the user understand the data, ask the right questions, and turn insights into decisions.

“As we evolved the platform, we realized that users don’t just want another dashboard—they need decision intelligence,” says Urvi Sengar, a senior software engineer in Microsoft Digital. “They need a system that can connect signals across datasets, surface actionable insights, and guide decisions in real time, so they can move faster and act with confidence.”

So Sengar and her fellow engineers set to work adding an agentic layer to IntelLicense that could provide those AI-driven insights. They used Microsoft Foundry to create a multi-agent solution that could handle all the various needs users of the system might have.

“With the multi-agent architecture that we followed, we have a workflow manager that delegates any user query to specialized agents,” Sengar says. “One agent handles license management, another deals with supplier management, another can support audit scenarios. Each agent understands the user’s intent and can call any deterministic workflows when needed.”

Sengar sees the agentic layer as the transformation of IntelLicense from a reporting tool into an intelligent system that can deliver contextual, on-demand insights and help users take action through workflows. It also aligns with the growing expectations for a more conversational, Copilot-like AI experience, where users can ask questions naturally and receive meaningful, actionable responses in real time.

“The platform delivers proactive insights through the portal while also enabling users to explore them on-demand, in the context of their work,” Sengar says.

She goes on to describe a scenario where a software asset manager is in the middle of negotiating a contract with a supplier. If they have a new idea, question, or strategy they want to validate, the portal can surface relevant recommendations and insights right away. If they want to go deeper, they can use the chat interface to ask questions and get instant access to the latest context-aware information in a dynamic way, without having to leave the flow of their work.

“That’s where we see the future of AI-driven work going,” Sengar says. “It’s using AI not only to surface insights, but to help people explore them further, act on them, and make better decisions faster.”

Applying intelligence across the enterprise

Large enterprise organizations like Microsoft face this kind of challenge in many areas: how to maximize efficiency by centrally managing a process that is scattered across many different teams and systems, with data that is often inaccessible or systems that are incompatible. Teams have often developed different ways of accomplishing the same task and are reluctant to change.

“We want to make the biggest difference for the company—that’s the ultimate goal. At the end of the day, we want to make sure there is plenty of cost savings produced. Beyond that, we want to apply as much intelligence as possible to the problem, so that AI is impacting all aspects of the process.”

Senthil Selveraj, principal group product manager, Microsoft Digital

Our approach is to apply AI where it makes sense, using continuous improvement principles to guide us. We also look to our AI councils to make sure that we’re following best practices.

This ensures that when we at Microsoft Digital tackle something like software licensing, we’re going to achieve a transformational result that will pay big dividends across the company.

“We want to make the biggest difference for the company—that’s the ultimate goal,” says Senthil Selveraj, a principal group product manager in Microsoft Digital. “At the end of the day, we want to make sure there is plenty of cost savings produced. Beyond that, we want to apply as much intelligence as possible to the problem, so that AI is impacting all aspects of the process. That’s where we’ll see the largest, most impactful benefits.”

The post Taming software licensing sprawl at Microsoft with an AI-driven solution appeared first on Inside Track Blog.

At that scale, Python dependencies have emerged as a significant source of risk for us—representing the third-largest vulnerability surface across the company.

The good news is that we have strong visibility into these vulnerabilities, with tools that continuously detect and surface risks across our codebases. The bad news is that turning those insights into action required a complex remediation process.

Updating a single code package often caused changes across multiple interdependent libraries. This required coordinated updates, validation, and testing to maintain system stability.

“When AI arrived, I saw it as a great opportunity to finally fix a very complex problem we had: The level of entanglement involved in Python code dependencies. A simple script wasn’t going to resolve it—you needed the power of AI.”

Humberto Arias, senior product manager, Microsoft Digital

Multiply this by thousands of projects throughout our enterprise, and vulnerabilities accumulated much faster than we could resolve them. To address this challenge, we turned to AI.

Microsoft Digital—the company’s IT organization—has developed an AI-powered solution called Python Dependency Remediation. Designed to work directly within the developer workflow, this solution analyzes dependency chains, applies required updates, and automatically adjusts the code. This enables our engineers to remediate vulnerabilities quickly and consistently at enterprise scale.

“I’ve worked for years in the vulnerability management space at Microsoft,” says Humberto Arias, a senior product manager in Microsoft Digital. “When AI arrived, I saw it as a great opportunity to finally fix a very complex problem we had: The level of entanglement involved in Python code dependencies. A simple script wasn’t going to resolve it—you needed the power of AI.”

The tool has shown so much promise that we have begun releasing it externally, so that millions of Python developers around the world can take advantage of it.

“I used to have this problem all the time. I upgrade one library, and then I’ve got to upgrade 17 other things, and something else breaks, and now my code is completely different.”

Rich Chiodo, principal software engineer, Python and Tools for AI

Get started

Try using the Python Dependency Remediation tool

Flexibility leads to dependencies and risk

Python is a very flexible language, which is why it’s so popular among software developers. But that same flexible nature—it can be used across a wide range of scenarios—also means it forms deeply interconnected dependency chains. When one code library is updated, it can trigger changes across many others.

“I used to have this problem all the time,” says Rich Chiodo, a principal software engineer on the team responsible for Python Tools and AI. “I upgrade one library, and then I’ve got to upgrade 17 other things, and something else breaks, and now my code is completely different.”

“Developers avoid the upgrades because the dependency web is so complex. This means the vulnerabilities accumulate over time and can become a real security risk.”

Chintan Sheth, principal engineering manager, Viva Glint

Because the code is so interdependent and remediation is time-consuming, many developers skip updating their code packages, which can lead to security vulnerabilities.

Security compliance was often seen as a burden because it slows people down.

“Developers avoid the upgrades because the dependency web is so complex,” says Chintan Sheth, a principal engineering manager on the Viva Glint product team. “This means the vulnerabilities accumulate over time and can become a real security risk.”

“After my manager mentioned it, I reviewed the idea on the hackathon page, and it looked really interesting to me. So I jumped in, and we created a prototype and a demo video with a quick solution. That’s how it started.”

Shiva Krishna Gollapelly, senior software engineer, Microsoft Digital

Hacking our way to a solution

Like some of the best internally developed tools and processes, Python Dependency Remediation came out of a Microsoft hackathon project. These grassroots events allow our engineers to tackle interesting technical challenges in a collaborative, creative way.

“After my manager mentioned it, I reviewed the idea on the hackathon page, and it looked really interesting to me,” says Shiva Krishna Gollapelly, a senior software engineer in Microsoft Digital and the lead developer on the project. “So I jumped in, and we created a prototype and a demo video with a quick solution. That’s how it started.”

The fact that this solution came from a hackathon highlights the ideas-driven culture that we promote at the company.

“This really speaks to our special culture of innovation,” says Snigdha Bora, a principal group engineering manager for Employee Experience. “After this emerged from the hackathon, our developers realized it could solve a problem at scale—that it was worth taking through the full development cycle so we can release it for all of Microsoft, and maybe beyond.”

Solving the issue with one click (and AI)

Because the challenge was not detecting vulnerabilities but fixing them, we had to rethink how we addressed Python dependencies.

“The extension automatically finds the right updates and then fixes the vulnerabilities, so developers don’t need to do the research, the manual upgrades and fixes, run test cases, debugging—all those things that used to take so much time. With our solution, it’s just one button click and it does all of that automatically.”

Shiva Krishna Gollapelly, senior software engineer, Microsoft Digital

In the past, when engineers received a vulnerability notification, they would have to step outside their development workflow and address the issue. What was needed was a solution that could be enacted within their normal workflow—integrating remediation directly into the tools they were already using.

So, we created the Python Dependency Remediation extension for Visual Studio Code, a common Python development environment. Once installed, engineers can address vulnerabilities in the flow of their work.

“The extension automatically finds the right updates and then fixes the vulnerabilities, so developers don’t need to do the research, the manual upgrades and fixes, run test cases, debugging—all those things that used to take so much time,” Gollapelly says. “With our solution, it’s just one button click and it does all of that automatically, with the help of AI.”

The extension uses the APIs built into Visual Studio Code to connect with any AI model the user has access to. (If there is no AI model available, Gollapelly explains, the extension will still make the package updates but won’t do the remediation fixes to the code.) It also produces a report of the changes for the developer to review in case there’s a snag that needs troubleshooting.

“This tool removes a significant burden from our developers,” Bora says. “We are shifting the entire remediation process left, embedding it early in the development workflow. Developers can review the changes and move forward immediately, making the whole process more efficient.”

“We’ve upgraded the library with new methods, calls, and structures. Now, let’s make sure everything works, check for errors in the code, etc. That’s the gap we’re bridging with AI.”

Angel Saldivia, software engineer, SharePoint

The result is that fixes and upgrades that used to take multiple hours of developer time now take minutes, and the code is much more reliable.

What the agent does in this solution is help close that loop, something that the engineer used to have to do.

“We’ve upgraded the library with new methods, calls, and structures,” says Angel Saldivia, a software engineer on the SharePoint product team. “Now, let’s make sure everything works, check for errors in the code, etc. That’s the gap we’re bridging with AI.”

From Customer Zero to global impact

One of the powerful things about working at Microsoft is that you get to help develop technology tools that can change the world. This is the case with Python Dependency Remediation as well.

“We realized this technology had much broader value. There are hundreds of millions of Python users worldwide, so the impact could be massive.”

Snigdha Bora, principal group engineering manager, Employee Experience

As Bora explains, while the solution was being developed it was presented to Guido van Rossum, the creator of Python (and a Microsoft employee). He immediately saw the incredible potential of the concept.

“He suggested that we could take this solution to the world, not just to Microsoft,” Bora says. “We realized this technology had much broader value. There are millions of Python users, so the impact could be massive.”

To help make this happen, Microsoft Digital approached Graham Wheeler, a principal group engineering manager on the Python and Tools for AI team. Wheeler’s team is responsible for shipping Pylance, a development extension for Visual Studio Code used by more than 180 million developers worldwide.

“One of the things we could do was provide a jumping-off point for this extension, so that when users installed Pylance they’d be prompted to also download Python Dependency Remediation. It can help raise awareness, because many users don’t actually do the dependency scanning and updating that they should.”

Graham Wheeler, principal group engineering manager, Python and Tools for AI

Wheeler and his team are in the process of incorporating the Python Dependency Remediation extension as an option during Pylance installation. This will open up a convenient vector for getting the tool in front of a huge audience, potentially revolutionizing Python development.

“One of the things we could do was provide a jumping-off point for this extension, so that when users installed Pylance they’d be prompted to also download Python Dependency Remediation,” Wheeler says. “It can help raise awareness, because so many users don’t actually do the dependency scanning and updates that they should. So, we’re helping with that challenge.”

Beyond Python, the AI-powered technology behind this extension might be applied to other dependency challenges as well. What started as a simple hackathon project could have huge ramifications for the future of software development.

“This solution can easily be adapted to other libraries, other programming languages,” Gollapelly says. “Whether you’re talking about C#, Angular, React, or another language, the concept is the same. The implications are vast.”

The post Taming our Python dependencies at Microsoft with AI appeared first on Inside Track Blog.

Today, the company has grown into a global organization with more than 200,000 employees. They all rely on Microsoft Digital—the company’s IT organization—to provide the tools, technologies, and solutions that empower them to accomplish more every day.

The need for digital transformation

The history of information technology is one of constant evolution, and the pace of change has never felt greater than it does right now. The AI capabilities and other groundbreaking innovations unveiled in the last few years show the potential to radically transform our world and change the way we think about and operate all IT services.

When the world pivoted to remote online work and collaboration because of the COVID-19 pandemic, it was just one example of how digital transformation doesn’t always happen in a straight line or on a predictable schedule. Our company’s history of shaping and adapting its IT organization to the latest challenges faced by employees and partners is no different; marked by big bets and strategic shifts that reflect our ever-changing world.

Mapping our IT journey

Today, Microsoft Digital is the team that powers, protects, and transforms the digital employee experience across all devices, applications, and hybrid infrastructure at the company. Using our deep knowledge and experience in enterprise IT, we’re pivoting to help lead the company’s AI transformation while also sharing our journey with customers so they can take advantage of this generational opportunity to reshape their businesses and IT operations.

To understand where we’re going, it helps to take a look at where we’ve been. This article explores the details of the major eras of our IT history and then shifts to examine the trendlines and technological innovations that are shaping Microsoft now.

On-Premises IT (founding to 2009)

It’s useful to break the history of our IT operations into different eras. For the first three decades or so from its founding in 1975, Microsoft operated with on-premises IT systems. This era was characterized by the setup, operation, and maintenance of onsite physical technology—servers, datacenters, and other hardware infrastructure.

During this time, IT roles were narrowly defined. IT team members functioned primarily as “order-takers,” with limited influence over strategic decisions.

Because funding was inconsistent, our IT organization had limited growth opportunities and relied on vendors for development work. Gaps were filled in with “shadow IT,” where internal teams would sometimes procure their own hardware or software without formal IT approval or standards.

We established security as an early priority for the company. Cofounder Bill Gates launched the Trustworthy Computing initiative more than two decades ago, an effort emphasizing the importance of security, privacy, and reliability across Microsoft products and services both internally and externally.

Our On-Premises IT era established the foundation that would become crucial to the company’s future digital transformation.

All in on the cloud: The Cloud and Culture era (2010-2018)

Cloud computing marked the next significant shift in the history of IT at Microsoft. It began in 2010 under the leadership of CEO Steve Ballmer, signaling a major break with the previous era of physical IT infrastructure and an important step toward today’s distributed-computing world.

The launch of the cloud computing platform then known as Windows Azure heralded this new era, as we transitioned away from an IT philosophy focused on the Windows desktop client toward a more platform-agnostic view. Cloud computing offered extensive advantages for customers and for our own IT environment, in terms of cost, performance, security, and scalability.

We started our journey by moving productivity workloads (Exchange and SharePoint) to the cloud. Then, we shifted new development to Azure and optimized modern applications to run in the cloud. We also moved existing applications targeted for migration to virtual machines. Today, more than 98% of our IT workloads run on Azure.

Cultural transformation

Another important shift during this era was the profound cultural transformation at Microsoft sparked by new CEO Satya Nadella, who rose to the top job at the company in 2014. Nadella had previously run the Microsoft cloud computing and enterprise group, so he was already steeped in the idea of transformational change at the company.

“Achieving our mission requires us to evolve our culture. It all starts with a growth mindset—a passion to learn and bring our best every day to make a bigger difference in the world.”

Satya Nadella, CEO, Microsoft

Before Nadella’s ascension, Microsoft had long been known for its extremely competitive, “know-it-all” culture. Employees succeeded by showcasing their own individual achievements and how their accomplishments exceeded their peers.

Nadella changed this ethos by championing a growth mindset, encouraging employees to be “learn-it-alls” rather than “know-it-alls.” The shift included placing new importance on how employees contributed to the success of others, a value that was incorporated into individual performance reviews. Nadella made this transformation his personal mission and directed leadership to propagate the new philosophy at all levels across the organization.

“Achieving our mission requires us to evolve our culture,” Nadella says. “It all starts with a growth mindset—a passion to learn and bring our best every day to make a bigger difference in the world.”

The combination of the shift to cloud computing infrastructure and overhauling the company culture helped set the stage for the major technological innovations to come.

A new vision: The Modern Engineering era (2018-2023)

For years, IT at Microsoft had been order takers, doing what the business requested with limited ability to impact strategic priorities. That changed as we shifted to become a modern engineering organization. With support from our executive leadership, IT was elevated to become a peer engineering function at Microsoft.

Rather than simply taking orders, the team was empowered to lead with a strong vision for the future. In fact, leading with vision is the primary hallmark of our Modern Engineering era. As we moved into this era, we needed a clearly articulated view of our goals as an IT organization aligned to the needs of our business partners, as well as the resources needed to achieve them.

Role transformation

Transitioning to become a modern engineering organization required Microsoft Digital to adapt our legacy approach to IT.

Operating an engineering organization in a cloud environment meant new roles, new skills, and a new mindset. With no need to manage physical hardware, our modern IT professionals were freed to work more closely with business partners, requiring greater strategic acumen. The team was now focused on DevOps, Agile program management, and user-centric design principles.

User-centric, coherent design

Our design philosophy puts the user—an employee or guest—at the heart of every decision we make at Microsoft Digital.

The goal of this approach is to make tasks that might have previously caused friction to become simpler. Instead of dealing with disconnected systems, user-centric design introduces consistent and logical flow between services. This makes it easier for people to access services, learn how to use them, and then put them to good use.

Microsoft also embraces coherent design across all our products. A familiar look and feel, along with consistent usage patterns, accelerates employee usage and adoption. 

Embracing work-from-anywhere capability

During the pandemic, when our workforce was still fully remote, our organization was already starting to think about what the new hybrid workplace would look like when people started returning to the office. We identified three key dimensions of the employee experience:

• Physical spaces: We partner with Global Workplace Services to plan and deploy meeting spaces with amazing digital capabilities that support an inclusive approach to hybrid productivity.
• Digital capabilities: We keep employees productive and their digital environment safe and secure, no matter where they’re located or how they connect.
• Culture: A strong partnership with HR ensures that digital experiences support our company culture.

Managing shadow IT with a culture of trust

Shadow IT is the unknown and unmanaged set of applications, services, and infrastructure that are developed and managed outside standard IT policies. Shadow IT typically crops up when engineering teams are unable to support the needs of non-engineering partners, a situation that could arise from a lack of available capacity or the need for specialized domain solutions. 

While earlier eras of our IT history focused on trying to prevent shadow IT, we are now concentrating on managing it. We use Azure best practices to optimize shadow IT and Microsoft 365 governance policies to ensure that our corporate security, privacy, and accessibility standards are met. We empower our employees to create whatever they need within our tenant, including PowerApps, SharePoint sites, Teams channels, or agents, mitigating the need for “shadow” solutions while also providing visibility into how our employees are using our own technology.

Learn how optimizing our Microsoft Azure usage is helping us manage our Shadow IT.

The Era of AI (2023 to present)

The latest chapter in the history of our organization’s digital transformation is defined by the integration of AI and agents into IT operations. AI is revolutionizing how Microsoft does IT at enterprise scale, driving efficiency and innovation across the board. From the apps, workflows, and services that power our employee experience to the network, infrastructure, and devices that enable employee productivity, our AI-focused investments provide a solid foundation for the innovations that we are constantly implementing. As we look at the future of Microsoft Digital, we’re focused on four key priorities: security, service fundamentals, acting as Customer Zero, and AI-powered innovation. We’re working to excel in all four domains with the help of our industry-leading AI capabilities.  

“Our mission is to power and protect Microsoft, and that starts with an unwavering commitment to the Secure Future Initiative.”

Brian Fielder, vice president, Microsoft Digital

Securing our future

Security is our highest priority. The Microsoft Secure Future Initiative aligns every team with a shared approach, common priorities, and consistent milestones to harden our security posture across all products and services.  

“Prioritizing security above all else is critical to our company’s future,” Nadella says. “Every task we take on—from a line of code to a customer or partner process—is an opportunity to help bolster our own security and that of our entire ecosystem. If you’re faced with a tradeoff between security and another priority, your answer is clear: Do security.”

The Secure Future Initiative is built on three core principles: Secure by design, secure by default, and secure operations. As the company’s IT organization, we work relentlessly to fulfill the key pillars of the Secure Future initiative across all our systems, including:

• Safeguarding identities and secrets
• Protecting tenants and isolating production systems
• Securing networks and engineering systems
• Enhancing threat detection
• Expediting response and remediation

“Our mission is to power and protect Microsoft, and that starts with an unwavering commitment to the Secure Future Initiative,” says Brian Fielder, vice president of Microsoft Digital.

Secure Future Initiative | Microsoft

Foundations: Service fundamentals

The second pillar is to maintain the highest standards of service fundamentals. These are the essential capabilities and practices that enable us to deliver reliable, secure, and compliant services companywide. Adhering to the highest standards of service fundamentals ensures that our organization continues to play a critical role in running the company’s business and enabling innovation, agility, and resilience in a fast-changing and competitive environment.

Customer Zero

The third pillar is acting as Customer Zero for Microsoft’s most important products and services, like Copilot Studio, Microsoft Teams, and Agent 365. In Microsoft Digital, we take pride in being the first customer for a wide variety of Microsoft products and services, relentlessly focusing on our own employee experience to create products that enable every person on the planet to achieve more.

Being Customer Zero means forging a deep partnership between our IT organization and product engineering groups to envision the right experiences, co-develop innovative solutions, and then listen to and act on insights gathered from our employees. We work together to stay grounded in the way our employees use our products every day, so your employees can benefit from our insights prior to external product launches.

Read about how we’re improving our employee experience through our Customer Zero focus.

AI-powered innovation

The final pillar of this era is innovating with AI to transform the digital experience at Microsoft. By doing all the fundamental work detailed above—security, foundations, and Customer Zero—extremely well, we gain the confidence and earn the trust necessary to embed AI across our full portfolio of services. We do this over three key dimensions: core IT services, employee experiences, and corporate functions.

Core IT services: Transforming and securing our network and infrastructure

We’re focused on using AI to infuse data-driven intelligence into every part of our infrastructure and network operations. This allows us to optimize operations and increase security while simultaneously improving outcomes.

Examples include:

• Network observability and governance: Ensuring data accuracy, eliminating non-compliant hardware and software, and real-time updates
• Securing endpoints: Device management, asset management, and patching
• Zero Trust networking: Isolating device classes and limiting attacker’s movements across the network
• Network access: Azure VPN, identity management, and Secure Access Workstation (SAW) infrastructure security

Learn how we’re transforming our enterprise IT operations at Microsoft.

Core IT services: Tenant management

We manage one of the most complex tenants anywhere. Governance today is a somewhat fragmented experience, with no clear mechanism for IT to safely enable self-service asset creation for sites, Teams, groups, Power Apps, and so on. These unmanaged assets increase the risk of over-sharing sensitive data and compromise the health and security of our IT environment.

In the world of AI, security through obscurity is no longer a viable option. This means data hygiene, permission management, and data protection are essential to providing trustworthy AI tools that don’t overexpose sensitive content, while still providing quality responses.

Read about one way we’re improving security by protecting elevated-privilege accounts at Microsoft.

Core IT services: Support

We’re using generative AI to transform the way our employees interact with our support services. IT issues will be either auto-remediated or resolved remotely and instantly through conversational, personalized, and contextualized solutions, often without a human agent’s intervention.

We’ll accomplish this with a focus on the following:

• User experience: Our employees are using the AI-powered Employee Self-Service Agent to access personalized, accurate, and cost-effective issue resolution. Future goals include implementing a seamless transition to a human agent while the user stays within the agentic Copilot experience.
• Human agent experience: Operational efficiency and automation are being integrated into the Service Operations Workspace. The service includes chat and incident summarization that recommends best next actions and drafts contextual answers to queries.

Find out how we’re transforming IT support at Microsoft with AI and the Employee Self-Service Agent.

Defragmenting the employee experience

The second dimension where we’re implementing our AI vision to make a difference is our employee experience. Our vision is to deliver a unified, connected, and personalized experience where users can access employee data, tools, and insights from one place.

“We see AI as the key to unlocking the full potential of our employees, delivering personalized experiences that empower us to work smarter, faster, and happier—unleashing the innovation and collaboration necessary for our success.”

Vijaya Alaparthi, principal group product manager, Microsoft Digital

One of the key ways we’re doing this is with Microsoft 365 Copilot, which functions as a “UI for AI” across our employee tools and services. An example is our Employee Self-Service Agent, an AI-driven tool based on Copilot that helps employees more efficiently find context-specific answers to their questions using natural language queries.

“We see AI as the key to unlocking the full potential of our employees, delivering personalized experiences that empower us to work smarter, faster, and happier—unleashing the innovation and collaboration necessary for our success,” says Vijaya Alaparthi, a principal group product manager in Microsoft Digital.

To achieve our vision, we’re building a workplace where AI defragments the employee experience by:

• Providing contextual support in the flow of work
• Reducing the number of sites and apps an employee must remember
• Using Microsoft 365 Copilot as the “UI for AI,” making it simple for employees to find information, take action, and even fully automate certain repeatable tasks

Corporate functions growth

Our third major priority in Microsoft Digital is to improve how we support the company’s corporate functions organizations, including legal and real estate and facilities.

“With AI, we have so many new ways to innovate. From optimizing building occupancy, to streamlining commute services, to automating contract and document management, we have incredible potential to make our corporate functions more efficient and impactful.”

Becky West, principal group product manager, Microsoft Digital

This is a particular challenge, as these teams are being asked to do more with less today; Microsoft can no longer afford to grow operational costs at the same rate as in the past.

AI is playing a fundamental role in transforming the business workflows of our corporate functions partners while improving operational efficiency, user productivity, regulatory and corporate compliance, and data-driven decision making. It’s revolutionizing the way they operate by automating repetitive and time-consuming operational tasks.

“With AI, we have so many new ways to innovate,” says Becky West, a principal group product manager in Microsoft Digital. “From optimizing building occupancy, to streamlining commute services, to automating contract and document management, we have incredible potential to make our corporate functions more efficient and impactful.”

Some of the corporate functions taking advantage of AI capabilities and related increased efficiencies include:

• Real estate and facilities: In supporting the technology needs for more than 500 company buildings worldwide, we are poised to use AI and related innovations to implement cost savings in the areas of workspace systems, facilities management, and space management.

Find out how we’re transforming facility operations at Microsoft with AI maps.

• Travel and expense: Our plan is to work for near-elimination of the traditional expense reporting process through AI-based and touchless experiences, driving simplification and productivity gains.

Check out how OneExpense transformed our employee expense reporting.

• Legal: Our vision for integrating AI into Corporate, External, and Legal Affairs (CELA) includes more discoverable legal findings, better corporate document management with the Docufy platform, enhanced engagement with Microsoft Philanthropies, and accelerated support for business-critical functions such as immigration, contracting, and insider trading compliance.

Read how AI is revolutionizing the way we support corporate functions at Microsoft.

Agentic AI: Becoming a Frontier Firm

This era of AI in IT has quickly morphed into a world in which agents are having major impacts across the enterprise. Microsoft Digital plays a central role in helping the company embrace this change and transform into a Frontier Firm: an organization that has deeply embedded AI and agents into its operations, products, and culture

As a Frontier Firm, we go beyond simply adopting AI as a discrete tool or additional technology. We’re actively integrating intelligent systems, rich data platforms, and human knowledge into a unified operating model, where automation, decision making, and innovation combine to spark acceleration at scale. Agentic AI is a core enterprise capability for us, powering everything from employee productivity to customer experiences and strategic decisions.

As Microsoft progresses into this agentic AI future—where autonomous or semi-autonomous AI agents understand context, take actions, and collaborate alongside humans—Microsoft Digital has played a lead role in deploying these capabilities internally. We’ve led the early adoption of tools like Microsoft 365 Copilot, Azure AI services, and custom-built agents that help us automate repetitive tasks, surface insights, and orchestrate workflows across systems while enforcing strict governance policies. Examples include AI-powered agents that assist in IT service management, network monitoring, and enterprise knowledge retrieval, which allow employees to focus on higher-value work and maximize their individual impact.

As AI agents continue to grow in power and functionality and become more deeply integrated into the daily workflows of knowledge professionals, Microsoft IT will maintain our leadership role and operate at the bleeding edge of this technological revolution. 

A catalyst for change and growth

Microsoft’s digital transformation is a story of evolutionary change, resilience, and adaptation across multiple eras of information technology. From our origins as a traditional IT organization to becoming a modern engineering organization focused on driving AI-powered innovation, we in Microsoft Digital remain a catalyst for change within the company and our industry.

With our insights born from customer and employee obsession, we’re committed to streamlining IT operations while prioritizing security, revolutionizing user services, and facilitating corporate functions growth and development. All with the overarching goal of making Microsoft employees everywhere more productive while showing our customers and partners what’s possible as we move forward together into the future of IT.

The post Digitally transforming Microsoft: Our IT journey appeared first on Inside Track Blog.

“The legacy system was highly fragmented, with more than 50 device options, localized processes, data scattered across different systems, manual touchpoints, and limited visibility into order status. This created a lot of friction across the company, as well as higher costs.”

Aniruddha Das, principal PM manager, Microsoft Digital

But as our organization scaled globally, this system became increasingly complex and inefficient.

Across more than 200,000 employees in over 100 countries and regions, our device procurement and inventory management devolved into a patchwork of systems and practices. There was no top-level management, no consistent lifecycle model, and no standardized experience for employees needing to order a new device.

“The legacy system was highly fragmented, with more than 50 device options, localized processes, data scattered across different systems, manual touchpoints, and limited visibility into order status,” says Aniruddha Das, a principal PM manager in Microsoft Digital, the company’s IT organization. “This created a lot of friction across the company, as well as higher costs.”

Working in partnership with Procurement, we built myDevice—a companywide program that centralizes primary-device procurement and lifecycle workflows within a single managed platform. myDevice brought together previously distributed data and processes, giving us reliable visibility into each employee’s primary device and enabling predictable, data-driven refresh planning at scale—along with the operational insights needed to run the end-to-end experience.

“We’ve moved from a fragmented device procurement experience with many touchpoints to one conversation with one agent. Basically, we can tell our employees that their next device is just a conversation away.”

Mukul Singhal, partner engineering manager, Microsoft Digital

Beyond solving some of these basic data challenges, we also needed to address harder, at‑scale problems in the broader procurement experience: helping employees confidently pick the right device without getting overwhelmed by options, aligning eligibility and catalog choices to an employee’s role and location, and more.

With the new Employee Device Information (EDI) agent—affectionately referred to as “Eddie”—our employees will soon be able to use an AI chat interface to quickly explore recommended device options based on their job role and work needs, compare different models, and order a new device with a single click. This streamlined approach will reduce frustration, save time, and cut our costs as we automate a formerly manual process.

“We’ve moved from a fragmented device procurement experience with many touchpoints to one conversation with one agent,” says Mukul Singhal, a partner engineering manager in Microsoft Digital. “Basically, we can tell our employees that their next device is just a conversation away.”

Creating a unified approach with myDevice

The transformation began about three years ago, when our Procurement partners brought their vision for myDevice to us in Microsoft Digital. The stated goal was to standardize employee device procurement, inventory, and lifecycle management across the company.

“Our decentralized process was an industry outlier, and we realized we needed to pivot toward a standardized global process. We wanted to give our employees a single entry point, with consistent guidance across the enterprise.”

Angela Pearson, senior procurement program manager, Microsoft Procurement

Built on top of our internal ServiceNow platform, myDevice brought together previously disconnected workflows into a single consistent experience for employees. It introduced a common catalog of devices, standardized refresh cycles, and centralized ordering and fulfillment processes.

It was evident that such a system was badly needed.

“Our decentralized process was an industry outlier, and we realized we needed to pivot toward a standardized global process,” says Angela Pearson, a senior procurement program manager in Microsoft Procurement. “We wanted to give our employees a single-entry point, with consistent guidance across the enterprise. That was the first big win.”

Purchasing devices for a global workforce the size of Microsoft is not an insignificant budget item. And our fragmented system meant higher costs for the organization.

“The decentralized procurement model allowed teams to move fast, but it also led to inefficiencies,” Das says. “Devices were often purchased at the end of the fiscal cycle, because there was budget, but they didn’t always match real requirements and would sometimes go unused.”

This list maps out the evolution of our device procurement program here at Microsoft:

Legacy state

• Distributed experience: Inconsistent, inefficient processes across countries and business groups
• Zero visibility: Lack of proper asset tracking, accounting, or device management
• High friction and high cost: Significant manual effort required across multiple touchpoints

Foundation: myDevice 1.0

• Unified global experience: One consistent process across all geographies and divisions
• Persona-based: Guided buy for productivity needs based on job role
• Streamlined workflows: Optimized automated processes reducing manual touchpoints
• Enhanced visibility: Improved data management and asset tracking entering the company

Future vision: myDevice 2.0

• Next-gen interface: AI-driven, seamless employee interaction
• Supply chain resiliency: Built to weather disruption
• AI-assisted workflows: Intelligent automation across backend systems and processes

Creating a solution at the scale required for myDevice was a challenge. Relevant data was spread across systems, refresh cycles were inconsistent, and key processes, such as determining which devices should be refreshed, were often manual and time-intensive.

“The data was distributed across multiple systems, and each group was doing their own cycle,” says Amit Raghuwanshi, a principal software engineering manager in Microsoft Digital. “Bringing all the relevant data together was a huge task and big part of the solution.”

Three scenarios for device procurement

Our employees interact with three different workflows that involve obtaining a new primary work device:

• New hire provisioning
• Device refresh (for aging machines)
• Replacement for damaged devices

Each of these core scenarios now follows a standardized process, replacing the ad hoc methods that previously varied by team and geography.

“If a new hire’s device arrives a week after they join the company, that’s not a good experience. We want them to have it on day one.”

Ashok Bagade, principal product manager, Microsoft Digital

Establishing a clear device lifecycle was a big step. For example, Microsoft employees are eligible for a new PC (called a refresh) every four years. Now, with myDevice, roughly 20,000 employees each quarter automatically get a refresh invite, presuming available budget. This takes the burden off IT, admins, and other support staff who were previously tasked with managing this process manually.

The myDevice system is also improving the process for new hire device procurement. The goal has always been for each new Microsoft employee to have a computer waiting for them on their first day, but the gaps in the previous system often made meeting this standard difficult.

“If a new hire’s device arrives a week after they join the company, that’s not a good experience,” says Ashok Bagade, a principal product manager in Microsoft Digital. “We want them to have it on day one. Today, we are only able to do that around 70% of the time. We want to take that rate up to 98%.”

To make that happen, we’re in the process of shifting from a build-to-order device model to an inventory-based model. This means that our suppliers will have a stockpile of our most frequently requested PCs on hand, based on data we have compiled. This approach is designed to reduce the device procurement time from four to six weeks down to less than two weeks, Bagade says.

By centralizing and standardizing device management, myDevice created the foundation for the next phase of transforming this process: intelligence.

Adding AI for a seamless procurement experience

The second part of reimagining our employee device procurement at Microsoft was on the front end, which is the digital interface our people experience when they need to choose their new device.

Even with a unified platform in place, the experience of selecting and ordering the device could be time consuming and disjointed. Employees could browse a list of available computers, but choosing the right one still required research and consultation with colleagues and led to cognitive overwhelm.

“The challenge we saw is that people take a long time to complete their purchase because they don’t know which device to select,” Bagade says. “They get a bunch of options, and they’re not sure which one is right for them.”

So we built EDI (or “Eddie”), an AI-powered agent created with Microsoft Copilot Studio, that makes the process much more efficient. Eddie is transforming a static workflow into a conversational experience.

With Eddie, employees get a guided, conversational buying experience instead of a form-led journey. The agent validates the employee’s eligibility, captures the required inputs, and then offers role-aligned device choices directly in the chat—complete with comparison details and a clear selection path. Once confirmed, the employee submits the request and receives a trackable ServiceNow reference, which reduces follow-ups and helps employees stay informed on the process end-to-end.

“Eddie not only gives a consistent purchasing experience—it also guides you,” Bagade says. “You can ask questions and, through that conversation, narrow down your options.”

The agent is underpinned by a multi-agent architecture where specialized components handle different aspects of the process—catalog browsing, comparison, recommendations, and ordering—coordinated by an orchestration layer.

“With Eddie, the agent validates the information and, in many cases, executes the change. It can literally happen in minutes.”

Aniruddha Das, principal product manager, Microsoft Digital

Reducing complexity and increasing visibility

EDI also addresses operational pain points that extend beyond purchasing. One early challenge focused on correcting primary device records, which is an essential but previously manual process.

“Before we developed this solution, something as simple as correcting an employee’s primary device required multiple tickets and human validation,” Das says. “It could take weeks—and in some cases months—to resolve. With Eddie, the agent validates the information and, in many cases, executes the change. It can literally happen in minutes.”

Another critical improvement is visibility. Previously, once a device request was submitted, it effectively disappeared into a system that offered limited transparency.

“After placing a request, employees had no way to check on the status—it went into a black hole,” Das says. “Now, Eddie can look at the same data that Procurement has and provide answers immediately.”

Looking ahead: From systems to conversations

With myDevice and EDI in place, we’re now focused on the next phase: transforming device management into a fully conversational, intelligent experience. The vision is to move beyond portals entirely and toward an agent-first model where employees interact with systems through natural language.

“Our view for the future is that you won’t need to visit a UI or a system to accomplish a task, you’ll just start talking to an AI agent.”

Amit Raghuwanshi, principal software engineering manager, Microsoft Digital

This includes expanding capabilities such as predictive refresh cycles, deeper personalization, and tighter integration with supply chain and inventory systems. Efforts are also underway to reduce fulfillment times through innovations like centralized inventory management and forecasting.

At the same time, the experience will continue to evolve toward greater simplicity.

“Our view for the future is that you won’t need to visit a UI or a system to accomplish a task, you’ll just start talking to an AI agent,” Raghuwanshi says.

For employees, that shift means less friction, faster decisions, and a more intuitive experience.

“We know how busy our employees are, and we don’t want them spending time on lower-priority tasks. When it’s time to acquire a new device, the experience should be seamless from start to finish, without added complexity or cognitive burden. We’re making steady progress toward that reality.”

Anna Adams, director of hardware programs and operations, Microsoft Procurement

For our organization, it represents a broader transformation—one where AI not only improves existing processes but fundamentally reshapes our workflows and the way that work gets done across all functions.

This means that our employees have one less process that they have to puzzle through and figure out, which allows them to focus on their higher-value work.

“We know how busy our employees are, and we don’t want them spending time on lower-priority tasks,” says Anna Adams, director of hardware programs and operations in Microsoft Procurement. “When it’s time to acquire a new device, the experience should be seamless from start to finish, without added complexity or cognitive burden. We’re making steady progress toward that reality.”

The post Meet ‘Eddie,’ our agent for putting new PCs in the hands of our employees appeared first on Inside Track Blog.

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

Work IQ isn’t a product.

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

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

Aisha Hasan, principal product manager, Microsoft Digital

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

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

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

How Work IQ impacts everyday work

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

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

Dodd Willingham, principal product manager, Microsoft Digital

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

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

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

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

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

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

Making Outlook better

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

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

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

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

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

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

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

Applying persistent memory

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

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

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

From answers to action: Work IQ and AI agents

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

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

Naveen Jangir, principal architect, Microsoft Digital

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

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

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

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

Intelligence without bypassing governance

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

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

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

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

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

Work IQ, Fabric IQ, and Foundry IQ

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

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

The three layers serve distinct but connected purposes:

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

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

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

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

Key takeaways

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

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

Try it out

Get a closer look at Work IQ.

Related links

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

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

Humans can usually spot the signs of outdated information and exclude it when answering a question or addressing a work topic. But what happens when there’s no human in the loop?

At Microsoft, we’ve embraced the power and speed of agentic solutions across the enterprise. This means we’re at the forefront of developing and implementing innovative tools like the Employee Self-Service Agent, a chat-based solution that uses AI to address thousands of IT support issues and human resources (HR) queries every month—queries that used to be handled by humans. Early results from the tool show great promise for increased efficiency and time savings.

In developing tools like this agent, we were confronted with a challenge: How do we make sure all the unstructured data the tool was trained on is relevant and reliable?

Many organizations are facing this daunting task in the age of AI. Unlike structured data, which is well organized and more easily ingested by AI tools, the sprawling and unverified nature of unstructured data poses some tricky problems for agentic tool development. Tackling this challenge is often referred to as data conditioning.

Read on to see how we at Microsoft Digital—the company’s IT organization—are handling data conditioning across the company, and how you can follow our lead in your own organization.

Read our guide

Learn how to deploy an Employee Self-Service Agent based on our experience here at Microsoft.

How AI has changed the game

We already fundamentally understand that the power of AI and large language models has changed the game for many work tasks. The way employee support functions is no exception to this sweeping change.

“A tool like the Employee Self-Service Agent doesn’t know if something is true or false—it only sees information it can use and present. That’s why stale or outdated information is such a risk, unless you manage it up front.”

David Finney, director of IT Service Management, Microsoft Digital

Instead of relying on human agents to answer employee questions or resolve issues, we now have AI agents trained on vast corpora of data that can find the answer to a complex question in seconds.

But in our drive to give these tools access to everything they might need, they sometimes end up consuming information that isn’t helpful.

“A tool like the Employee Self-Service Agent doesn’t know if something is true or false—it only sees information it can use and present,” says David Finney, director of IT Service Management. “That’s why stale or outdated information is such a risk, unless you manage it up front.”

Before AI, support teams didn’t need to worry as much about the buried issues with unstructured content because a human could generally spot it or filter it out manually. After we turned these tools loose, they began reading everything, including:

• Older or hidden SharePoint content that humans would never find—but AI can
• Large knowledge base articles with buried incorrect information
• Region-specific content that’s not properly labeled

“For example, humans never saw the old, decommissioned SharePoint sites because they were automatically redirected,” says Kevin Verdeck, a senior IT service operations engineer. “But AI definitely could find them, and it surfaced ancient information that we didn’t even know was still out there.”

Data governance is the key

A major part of the solution to this problem is better governance. We had to get a handle on our data.

“We needed to determine the owners of the sites and then establish processes for reviewing content, updating it, and defining how it should be structured. I would highly encourage that our customers think about governance first when they are launching their own AI tools, because everything flows from it.”

Olivier Cherel, senior business process manager, Microsoft Digital

The first step was a massive cleanup effort, including removing decommissioned SharePoint sites and deleting references to retired programs and policies. The next step was making sure all content had ownership assigned to establish who would be maintaining it. This was followed by setting up schedules for regular content updates (lifecycle management).

Governance was the first priority for IT content, according to Olivier Cherel, a senior business process manager in Microsoft Digital.

“We had no governance in place for all the SharePoint sites, which were managed by the various IT teams,” Cherel says. “We needed to determine the owners of the sites and then establish processes for reviewing content, updating it, and defining how it should be structured. I would highly encourage that our customers think about governance first when they are launching their own AI tools, because everything flows from it.”

Content governance was also a huge challenge for other support areas, such as human resources. A coordinated approach was needed.

“HR content is vast, distributed across multiple SharePoint sites, and not everything has a clear owner,” says Shipra Gupta, an engineering PM lead in Human Resources who worked on the Employee Self-Service Agent project. “So, we collaborated with our content and People Operations teams to create a true content strategy: one source of truth, no duplication, with clear ownership and lifecycle management.”

Cherel observes that this process forces teams to think about their support content in a totally different way.

“People realize they need a new function on their team: content management,” he says. “You can’t simply rely on the knowledge found in the technicians’ heads anymore.”

Adding structure to the unstructured data

The simple truth is that part of what makes unstructured data so difficult for agentic AI tools to deal with is that it’s disorganized.

“Our HR Web content already had tagging for many policy documents, which helped us get started. But it wasn’t consistent across all content, so improved tagging became a big part of our governance effort.”

Shipra Gupta, engineering PM lead, Human Resources

AI works best with content that has as many of the following characteristics as possible:

• Document structure, including:
  • Clear headers and sections
  • Page-level summaries
  • Ordered steps and lists
  • Explicit labels for processes
  • HTML tags (which AI can see, but humans can’t)
• Structured metadata, including:
  • Region codes (e.g., US-only policies)
  • Device-specific tags
  • Secure device classification
  • Country-based hardware procurement policies and HR rules

This kind of formatting and metadata allows the AI tool to more clearly parse and sort the information, meaning its answers are going to have a much higher accuracy level (even if it might be a little slower to return them).

“A good example here is tagging,” Gupta says. “Our HR Web content already had tagging for many policy documents, which helped us get started. But it wasn’t consistent across all content, so improved tagging became a big part of our governance effort.”

Be sure that as part of your content review, you’re setting aside the time and resources to add this kind of structure to your unstructured data. The investment will pay off in the long run.

Using AI to help condition data for use

As AI tools grow more sophisticated, we’re using them to directly work on AI-related challenges. This includes using AI on the challenge of unstructured data itself.

“Right now, these efforts are primarily human-led, but we are applying AI to, for example, help write knowledge base articles,” Cherel says. “Also, we’re starting to use AI to determine where we have content gaps, and to analyze the feedback we’re getting on the tool itself. If we just rely on humans, it’s not going to scale. We need to leverage AI to stay on top of things and keep improving the tools.”

Essentially, the future of such technology is all about using AI to improve itself.

“We’re looking at building an agent to help validate content,” Finney says. “We can use it to check for outdated references, old processes, or abandoned terms that are no longer used. Essentially, we’ll have AI do a readiness check on the content that it is consuming.”

Ultimately, the better the data is conditioned, the more accurate and relevant the agent’s responses will be. And that will make the end user—the truly important human in the loop—much happier with the final outcome.

Key takeaways

We’ve highlighted some insights to keep in mind as you consider how to condition your own organization’s data for ingestion by AI tools:

• Unstructured data becomes a business risk when AI is in the loop. AI agents consume everything they can access, including outdated, hidden, or conflicting content, making data conditioning a critical prerequisite for agentic solutions.
• AI highlights content issues that were previously invisible. Decommissioned SharePoint sites, outdated policies, and region-specific content without proper labels all became visible after AI agents began scanning across systems.
• Governance is a vital part of the conditioning process. Assigning clear content ownership and establishing lifecycle management are essential steps in ensuring the content being fed to AI tools is of high quality and is well managed.
• Adding structure to data dramatically improves AI accuracy. Clear document formatting, consistent tagging, and rich metadata help AI agents return more relevant, reliable answers.
• AI will increasingly be used to condition and validate the data it consumes. Microsoft is already exploring using AI to identify content gaps, analyze feedback, and flag outdated information, creating a continuous improvement loop that can scale faster than human review alone.

Try it out

Learn how your organization can take advantage of the power of the Employee Self-Service Agent.

Related links

• Read how we’re accelerating employee services at Microsoft with the Employee Self-Service Agent.
• Learn how we keep our content fresh and well-governed with AI-powered SharePoint.
• Check out how we’re using good governance to ride the wave of agents washing over Microsoft.
• Discover how we’re becoming an AI-first Frontier Firm at Microsoft.
• See how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.

The post Conditioning our unstructured data for AI at Microsoft appeared first on Inside Track Blog.

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

The case for AI in employee assistance

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

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

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

Bringing AI to employee assistance

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

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

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

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

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

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

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

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

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

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

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

Before you start: Developing your plan

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

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

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

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

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

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

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

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

4. Articulate your vision

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

5. Define your governance

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

6. Implement your agent

This phase involves configuration and integration, followed by testing.

7. Roll out the agent while driving adoption and measurement

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

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

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

Chapter 1: Governance means getting your data right

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

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

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

Prerna Ajmera, general manager, HR digital strategy and innovation

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

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

Major considerations for governance

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

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

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

Architecture essentials

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

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

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

Assessing and preparing your content

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

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

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

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

Be aware of tone and conversational flow

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

Make sure you incorporate:

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

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

Addressing common scenarios with “golden” content

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

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

Our golden prompts are a curated set of scenarios that:

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

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

Including “zero prompt” content

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

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

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

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

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

Data security and compliance

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

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

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

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

Responsible AI

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

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

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

Key takeaways

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

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

Learn more

How we did it at Microsoft

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

Further guidance for you

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

Chapter 2: Implementation with intention

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

Determine category parameters

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

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

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

Understanding your deployment steps

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

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

Customization

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

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

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

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

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

Rollout: A phased approach

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

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

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

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

Key takeaways

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

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

Learn more

How we did it at Microsoft

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

Further guidance for you

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

Chapter 3: Driving adoption by breaking old habits

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

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

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

Adoption across verticals

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

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

Leadership is key

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

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

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

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

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

Defining your messaging

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

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

Listening to feedback

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

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

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

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

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

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

Calibrating your usage goals

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

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

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

Making the agent your front door for employee assistance

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

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

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

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

There are three key steps in this process:

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

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

Strategic outreach to employees

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

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

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

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

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

We used this channel for various kinds of messaging:

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

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

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

Prerna Ajmera, general manager, HR digital strategy and innovation

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

Managing expectations

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

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

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

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

How we measured success

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

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

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

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

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

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

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

Key takeaways

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

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

Learn more

How we did it at Microsoft

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

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

Further guidance for you

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

Begin your journey with the Employee Self-Service Agent

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

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

Brian Fielder, vice president, Microsoft Digital

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

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

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

Key takeaways

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

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

Learn more

How we did it at Microsoft

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

Try it out

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

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

In parts of Europe and elsewhere, relationships with our employees are governed by works councils. These councils play a major role in vetting and approving any new technology that might impact our workers and their jobs.

At Microsoft Digital, the company’s IT organization, we have gained a ton of insight by working closely with our works councils, especially as we all embrace the rise of generative AI and new tools like Microsoft 365 Copilot.  

“With the speed of AI innovation today, we can’t sit and wait. We need our internal users, including our works council members, to be forward-thinking early adopters and help us drive AI transformation.”

Irina Chemerys, regional experience lead, Microsoft Digital

This experience means we are able to help guide customers who are dealing with their own works councils—many of which also have questions and concerns about the agentic workplace of the future, which is coming fast.

As we continue on our journey to becoming an AI-first Frontier Firm, we are collaborating closely with our works councils to make sure that we address their concerns and follow all applicable regulations. This process also helps us make better products that meet the evolving needs of our customers, wherever they are.

“With the speed of AI innovation today, we can’t sit and wait,” says Chemerys, a regional experience lead who oversees works council engagements within Microsoft Digital. “We need our internal users, including our works council members, to be forward-thinking early adopters and help us drive AI transformation.”

How works councils work

Our works councils serve as the voice of our employees in some geographies (especially in Europe), advocating for their rights and interests within the workplace. Typically, they have purview over topics like workplace health and safety, pay and benefits, hiring, business reorganizations, training, and more.

 As AI technology becomes increasingly commonplace across many industries, our works councils—along with all of our employees—are at the forefront of the complex discussions regarding the implications of AI for the modern workforce.

While our relationship with Microsoft works councils has always been cooperative and collaborative, how we engage with them for product reviews has evolved over time. What used to be somewhat impromptu or inconsistent engagements have changed to become more strategic and programmatic opportunities for feedback, which can end up greatly improving our products.

Chemerys helped lead the Microsoft Digital effort to streamline the approval process for new technology across works council countries. She drove the development of a global solution that uses a single request form and platform for our works councils worldwide, helping them communicate with Microsoft Digital, product groups, legal, HR, and others at the company.

This simplified communication across the board, and facilitated collaboration among all works councils, allowing smaller countries to take advantage of resources from larger ones and creating a more cohesive community. The unified approach significantly improved coordination, collaboration, and, importantly, trust among works councils.

“Trust is more essential than anything else in terms of collaborating with works councils effectively, especially in the context of AI,” Chemerys says. “To build that trust, you need transparency. And the way you build transparency is by having a well-documented and effective request process.”

Approving Copilot: The tolerance phase

Trust and good communication were linchpins of the process we used to gain works council approval for Microsoft 365 Copilot. Considering how new generative AI tools are, and the widely promoted fears surrounding their potential impact on the workforce, there were understandable concerns raised by some of our works councils about Copilot.

Germany was one country where our works councils were particularly wary of AI. They raised questions about the ways that Copilot could be used to evaluate individual employee performance or make impermissible inferences about individual employees without the data to support them. For example, Copilot might be asked to generate a ranking of employee performance during a meeting, something that fell outside the boundaries of our Microsoft responsible AI principles.

“The earliest versions of these generative AI tools lacked guardrails,” says Carsten Schleicher, chairman of the Microsoft works council in Germany. “You could ask them anything and get an answer back—even questions about religion, race, gender, ethnicity, etc. There were also concerns about AI tools generating false information—so-called ‘hallucinations.’”

“AI is in the world; if you deny your employees access to it, you’ll fall behind. It was absolutely necessary to find a constructive way to deal with AI, and to use it in a fair and transparent way in our company.”

Carsten Schleicher, chairman, Microsoft German Works Council

Faced with these concerns, but also wanting to get as much feedback on Copilot from our European employees as possible, we decided to introduce a tolerance phase.

Countries such as Germany, France, and the Netherlands were included in this approach, which allowed for controlled deployment of the tool while still enabling employees to try it out.

“As a works council, it’s your goal to protect the employees, but you also want the company to be successful,” Schleicher says. “AI is in the world; if you deny your employees access to it, you’ll fall behind. It was absolutely necessary to find a constructive way to deal with AI, and to use it in a fair and transparent way in our company.”

Some members of our works councils were part of the first Copilot deployment wave, and their feedback was then channeled back to the product engineering team. This early access helped the councils quickly reach an agreement that deployment of Copilot could continue, while also leading to product improvements that benefited all our customers.

The tolerance phased ended in the spring of 2025, and Copilot is now approved for use by Microsoft employees worldwide.

Getting ready for the agentic future

After Copilot was approved, the next challenge for our works councils was the world of AI agents. As a Frontier Firm, Microsoft is gearing up for a workplace where employees are routinely aided in their work by digital agents. Eventually, agents may become our “digital colleagues” or even run entire business processes independently.

“For the Employee Self-Service Agent, it was an easy and straightforward process. We made a presentation to people from Microsoft HR in France, which went well. So, when we went to the works council, there were not a lot of concerns. We got the green light very quickly.”

Isabela Cardoso, regional experience lead for France and Ireland, Microsoft Digital

One example of a digital agent that we’ve launched across the entire company (as well as externally to our customers) is the Employee Self-Service Agent. This AI-driven tool offers a “one-stop shop” that our employees can turn to for help with IT support, HR questions, and facilities requests.

Because the tool can access potentially sensitive personal information about employees, we were careful to make sure that our works councils were consulted during the internal deployment of this agent. Their experience reviewing Copilot—and the simplified process that Chemerys spearheaded—were key to winning rapid approval of the Employee Self-Service Agent.

“For the Employee Self-Service Agent, it was an easy and straightforward process,” says Isabela Cardoso, a regional experience lead for France and Ireland within Microsoft Digital. “We made a presentation to people from Microsoft HR in France, which went well. So, when we went to the works council, there were not a lot of concerns. We got the green light very quickly.”

Edith Dubuisson, a senior business program manager in Microsoft Digital who manages our relationship with the Microsoft works council in France, agreed.

“AI is a massive change, so getting the councils engaged early helps to deal with the fear and questions. We see the works councils as a true partner in this transformation of the company with AI.”

Edith Dubuisson, senior business program manager, Microsoft Digital

She stressed how important the concept of partnership is in making sure works council reviews go as smoothly as possible, especially with AI-related technologies.

“We make a point of including the works council in early discussions, telling them that we need them as a partner,” Dubuisson says. “AI is a massive change, so getting the councils engaged early helps to deal with the fear and questions. We see the works councils as a true partner in this transformation of the company with AI.”   

Chemerys notes that as employee-created agents proliferate across the company, the review process will typically take place at the platform level, not the agent level. In this way, agents created with Microsoft 365 Copilot Studio will be treated much like tools created with something like the Microsoft Power Platform are handled.

“When it comes to low-code/no-code agents, you can compare the process to something like Power BI,” she says. “We’ve approved that platform to build reports, and then employees can create reports using it. In some countries, if an employee creates an AI agent using Copilot Studio that could impact the workplace in a sensitive way, then it’s their responsibility to get the proper approvals from our works councils. They can submit it through our standard process, which is why having that is so helpful.”

Embracing the future with our works councils

If there’s one true thing about technology in the age of AI, it’s that things continue to evolve at lightning speed. New tools and features are constantly being created, tested, and launched across Microsoft and many other cutting-edge, innovative companies.

Amidst all this rapid change, we continue to keep our works councils in the loop as these new technologies emerge. It’s a challenge that Microsoft is ready for, Chemerys says.

“There’s an avalanche of new solutions emerging all the time—so many different types of agents and other AI tools,” she says. “And the level is complexity is very high. But we have a great platform for works council reviews, so we can give them an early heads-up, which helps us maintain trust. They hate surprises, so we strive to stay ahead of things and make sure they stay informed.”

In the end, our works councils continue to be a source of invaluable feedback in this new fast-moving AI era. They play a role that transcends mere oversight and embraces proactive engagement, which makes for better products and happier employees—and customers.

Key takeaways

Here are some things to remember as you engage your own works councils with product reviews and discussions in the age of agentic AI:

• Engage your works councils early and often. Bringing them into conversations at the start—well before deployment—reduces uncertainty, surfaces valid concerns, and ensures smoother adoption of new AI tools like Copilot and employee-facing agents.
• Build trust through transparency and structure. A clear, well-documented approval process helps works councils understand new AI technologies and establishes the trust needed for productive, long-term collaboration.
• Simplify and unify communication channels. A single global request platform (like the one we use at Microsoft) improves coordination across works councils of different sizes, enabling smaller countries to benefit from shared expertise and creating a more consistent review experience.
• Balance innovation with worker protections. Structured tolerance phases, like those used for Microsoft 365 Copilot, allow employees to test new AI tools under controlled conditions while ensuring compliance with responsible AI principles and local regulations.
• Treat works councils as strategic partners in the agentic future. Their early feedback on digital agents—like our Employee Self-Service Agent—helps improve product design, accelerate approvals, and reduce fear or misconceptions about AI in the workplace.
• Design governance that scales with low-code and agentic tools. With AI agents proliferating, platform-level approvals—similar to the Power Platform model at Microsoft—ensure innovation can move quickly while still requiring review for individual high-impact scenarios.
• Stay ahead of rapid AI change with proactive communication. Works councils “hate surprises,” so providing early visibility into emerging tools helps maintain trust, reduces friction, and enables Microsoft to build better products for employees and customers alike.

Try it out

Try out Microsoft 365 Copilot at your company.

Related links

• Learn how we’re deploying Microsoft Places with the help of our works councils.
• Find out how we’re becoming an AI-first Frontier Firm at Microsoft.
• Read the full guide on how we managed the internal deployment of Microsoft 365 Copilot at our company.
• See how we’re embracing the agentic future with our Customer Zero approach in Microsoft Digital.

The post Transforming into an AI-first Frontier Firm in partnership with our works councils appeared first on Inside Track Blog.

That’s where the promise of AI transformation comes in.

We at Microsoft Digital, the company’s IT organization, have developed and implemented a diverse portfolio of agentic, AI-driven capabilities that are now embedded directly in our day-to-day IT operations. These agentic systems—AI solutions that can reason across data, recommend actions, and, in some cases, execute workflows with human oversight—turn telemetry and insights into action, making our IT infrastructure and processes more resilient, auditable, and proactive.

“We’ve crossed an important threshold in the evolution of AI for IT. We’re now using the capabilities these technologies provide to transform all our core IT services, making everything we do on that side more efficient and secure.”

Brian Fielder, vice president, Microsoft Digital

While your organization’s IT infrastructure may not match our size or complexity, we believe any company can benefit from the AI-driven innovations that we’ve implemented in recent years.

We focus our AI investments across three core areas:

• Network management and infrastructure
• Tenant and device management
• Employee and engineering productivity

We’re also using AI across our IT systems to increase security, both as a standalone initiative and an integrated priority. This principle is baked into all our compliance, vulnerability response, and governance scenarios.

“We’ve crossed an important threshold in the evolution of AI for IT,” says Brian Fielder, vice president of Microsoft Digital. “We’re now using the capabilities these technologies provide to transform all our core IT services, making everything we do on that side more efficient and secure.”

Pillar One: AI in network management and infrastructure

We have applied AI throughout our global network and IT infrastructure, enabling us to keep up with the ever-increasing demands for capacity and services while reducing disruptions and incidents.

The different innovations we’ve made that fall under this pillar demonstrate the breadth of the opportunity to reimagine IT services with AI.

Supporting enterprise IT at Microsoft: Our three pillars

Network management with AI

• AIOps
• Network infrastructure Copilot (NiC)
• Vuln.AI
• Managed Cloud Labs AI Assistant

Tenant and device management with AI

• Digital Asset Management Copilot
• Works councils and tenant trust review
• Enterprise vulnerability management
• IntelLicense
• myDevice AI Agent

Employee and engineering productivity with AI

• ADO Copilot
• ADO Work Item Assistant
• Automation Hub/Automation Catalog

The impact of AI technologies on enterprise IT operations at Microsoft can be divided into three main areas: network management, tenant and device management, and employee and engineering productivity.

AIOps: Transforming network management with operational excellence

AIOps, or Artificial Intelligence for IT Operations, involves the application of machine learning, big data analytics, and automation to streamline and improve IT operations processes. In Microsoft Digital, we use AIOps to help us to manage our complex global IT infrastructure.

Our AIOps solution leverages sophisticated data insights to detect and remediate network issues before they become impactful. We use our internally developed AIOps tools to turn raw signals and institutional know-how into guided actions that have led to major time and cost savings.

AIOps benefits include:

• Enhanced productivity: AIOps reduces cognitive load by automating routine tasks, allowing teams to focus on more strategic activities.
• Proactive issue resolution: AIOps executes automatic troubleshooting and remediation, minimizing downtime and reducing incident impact.
• Improved decision-making: AIOps leverages advanced analytics and machine learning to provide actionable insights, which enhances our decision-making capabilities.

The impact of our AIOps work is huge: thousands of hours of engineering time saved and a significant reduction in total disruption time for employees across the company’s global workforce.

Related products:

Microsoft 365 Copilot and Azure AI Services

NiC: A network engineer’s companion

Our Network Infrastructure Copilot (NiC) serves as an everyday companion for our network engineers and field IT professionals. With NiC, our IT pros can use natural-language queries to gain quick, accurate insights into network health, configuration states, documentation, troubleshooting resources, and live device data—all in one place.

Some of the typical use cases for NiC include:

• Summarizing syslogs for specific devices
• Recommending circuit upgrades
• Checking deployment status
• Listing devices missing required controls (such as AuditD)

In aggregate, NiC streamlines network device lifecycle management and operation, delivering significant time savings while improving the consistency of operational decisions.

Related products:

Microsoft 365 Copilot, Microsoft Foundry, Azure OpenAI, Azure Data Explorer

Vuln.AI: Proactively keeping our systems safe

Leaving just a single connected device unpatched could put our entire enterprise at risk. That’s why we developed Vuln.AI (Vulnerability Management Copilot), our intelligent agentic system that has transformed the way we identify, prioritize, and resolve these vulnerabilities across our enterprise network.

Vuln.AI coordinates two agents that enable our network engineers to gather, analyze, and respond to vulnerabilities proactively using AI insights. The research agent maps the vulnerability to the Microsoft infrastructure, significantly increasing accuracy and reducing manual effort and time involved. It then feeds this information to an interactive AI agent, which becomes a gateway for a security engineer or device owner to interface with the data, ask detailed questions, and gather the required information.

Thanks to Vuln.AI, we’ve been able to accelerate infrastructure compliance, reduce exposure windows, streamline security operations, improve endpoint hygiene, and lower operational risk. Our data show thousands of hours of engineering time saved and meaningful improvement in the accuracy of impacted-device identification.

Related products:

Microsoft 365 Copilot, Microsoft Foundry, Azure OpenAI, Azure Data Explorer

Managed Cloud Labs AI Assistant: Scaling support to meet demand

Engineering disciplines across Microsoft rely on production-like Azure lab environments for testing Windows updates, investigating incidents, and building customer demos. We created the Managed Cloud Labs AI Assistant to enable the rapid creation and management of these lab environments in the face of increasing user demands across our operations. This tool uses AI to help speed tasks such as the development and testing of Windows updates, investigating security incidents, and creating prototypes for customer demos.

Time is a critical component for all lab scenarios, whether it be resolving a customer support issue or testing a Windows Update ahead of a patch release. Our goal is to reduce “Customer Pain Time” (CPT), which measures the amount of time it takes to solve a customer’s problem. Every hour saved in the support process represents a multi-hour reduction in customer pain.

Our most recent data shows that Managed Cloud Labs AI Assistant reduced tickets submitted to our Tier 1 teams by 50% and saved 500 hours by leveraging support chats, configuration guides, and other artifacts In addition, new user onboarding training tickets were reduced by 90%, and individual support interaction time was reduced from an average of 20 minutes to 30 seconds.

Related products:

Azure OpenAI, Azure Cognitive Search, Azure Bot Framework, Azure Adaptive Cards

Pillar Two: Tenant and device management

One of the most complicated dimensions of managing IT services at Microsoft is our tenant. This refers to the internal instance of all our cloud services, including Teams channels, SharePoint sites, Power BI workspaces, apps, and email accounts, as well as the millions of devices used by our global workforce.

In Microsoft Digital, we’ve developed a number of AI-powered tools and solutions to help us manage this gigantic management challenge.

Digital asset management with AI: Governing the tenant

Microsoft empowers our employees to create assets—apps, groups, sites, Power Platform environments, Power BI workspaces—at self-service speed, and our governance must match that pace. Our Digital Asset Management Copilot is a multi-agent solution that surfaces risk and policy violations, recommends fixes, and enables self-service remediation.

Our employees can access a Copilot-like experience to self-manage their assets and ensure app compliance accountability. The agent surfaces insights and recommendations related to asset compliance like oversharing of sensitive documents, highlights tenant assets that pose a security risk, offers remediation mechanisms, and can execute compliance tasks with end-user or admin validation.

The benefits include a more secure enterprise tenant and an embedded culture of compliance: Simplify compliance responsibilities, making them intuitive and seamless for our employees. Success is gauged through end user NSAT scores from our compliance solutions.

The scope of this tool spans more than 1.5 million digital assets in the tenant. The benefits include a more secure enterprise tenant and an embedded culture of compliance. With the help of the Digital Asset Management Copilot, we aim to reach our overall goal of 90% compliance with policies covering ownership, labeling, oversharing, and periodic attestation across the tenant.

Related products:

Microsoft 365 Copilot, Dynamics 365 Copilot, Azure AI Service, Power BI Copilot

Works councils and tenant trust reviews: Optimizing tenant onboarding

In the past, fragmented and manual processes around works councils and tenant trust reviews consultations in the European Economic Area  could result in delays to our product launches by as much as four to six months. Our AI-driven optimization program streamlines the end-to-end process, improving submission quality and routing and providing other efficiency recommendations.

The result of these efforts is significant: We’ve managed to reduce the average works councils and tenant trust review cycle times from 133 days to 40—about a 70% improvement—while strengthening trust and transparency across roughly 17 European Economic Area countries.

Related products:

Microsoft 365 Copilot, Azure AI Service, Power BI

Enterprise Vulnerability Management: Reducing risk to our device fleet

Our extensive companywide Windows device fleet is exposed to vulnerabilities for extended periods after remediations (patches) are applied, increasing the risk of security breaches and operational inefficiencies. Relying on manual processes can lead to slow response times.

Enterprise Vulnerability Management (EVM) is a multi-phase strategy that uses AI technology in combination with Microsoft first-party vulnerability management solutions to proactively secure and maintain the fleet. While Vuln.AI helps us keep our enterprise infrastructure safe and secure, EVM does the same for our fleet of Windows devices.

EVM minimizes risk and reduces manual effort by integrating advanced detection, automated remediation, and compliance acceleration, minimizing risk and manual effort. This holistic approach ensures our devices stay secure and compliant with minimal IT intervention, delivering resilient, self-healing endpoints across the enterprise.

AI-driven EVM delivers measurable impact across our security, compliance, and IT efficiency. Our goal is to reach 95% compliance within a week of a major patching event while reducing operational overhead and enhancing enterprise resilience.

Related products:

Windows Autopatch, Intune, Windows Update

IntelLicense: Our AI-driven license optimization and audit readiness

Managing a software estate the size of ours—including 28 disconnected systems, 400,000 software assets, and more than 800 suppliers—requires license intelligence. IntelLicense is a set of advanced, AI-driven solutions we’ve developed to help us revolutionize our software discovery and acquisition processes.

These solutions optimize our software asset management throughout the enterprise software lifecycle, reducing fragmented data, lowering audit risk, and accelerating decision-making. These changes have delivered substantial cost savings and efficiency improvements. One standout example: Our external vendor audits that previously took an average of 154 days are targeted to drop to about 15 minutes, thanks to IntelLicense changes.

Related products:

Microsoft 365 Copilot, Microsoft Fabric, Power BI Copilot, Microsoft Foundry, Azure AI Service

myDevice AI: Transforming our IT asset management

Ensuring the security of our physical assets requires a unified and accurate inventory. Fragmented IT asset data leads to inconsistent policies and exposes vulnerabilities, making it difficult for security teams to quickly isolate threats and limit potential impact.

The myDevice AI Agent advances an AI-native approach to IT asset management across our IT tenant. The agent automates our high-volume employee requests, clarifies inventory, and streamlines our procurement. While this is occurring, the agent’s recommendation engine matches devices to our users’ needs to improve satisfaction and security.

Early results from myDevice AI include an approximately 50% reduction in time and costs in asset management (eliminating thousands of hours in manual processes annually), as well as improved security and a more personalized device-procurement experience for employees. In time, we will broaden this impact as agentic workflows expand to include labs, printers, conference rooms, and Internet of Things devices.

Related products:

Microsoft 365 Copilot, Azure AI Service

Pillar Three: Our employee and engineering productivity

Building the software and systems needed to power Information Technology at Microsoft is a time-intensive job. Our engineers have been hard at work building AI-powered solutions that make building and maintaining those systems more efficient and streamlined, answering the question, “How can we apply AI to make this more efficient?”

Here are a few of the solutions we’ve found to help cut down the time and effort involved in some of the routine, day-to-day IT procedures that help keep our systems running smoothly.

ADO Copilot: AI with Azure DevOps

ADO Copilot empowers all our developers and product managers by providing instant, AI-driven insights and automation within Azure DevOps (ADO). This AI-driven assistant seamlessly integrates into ADO and acts as a “trusted copilot” with natural-language capabilities that automate workflows; enhance productivity, compliance, and velocity; and amplify decision-making across the planning, building, and deployment phases.

This agentic solution reduces the time we spend searching for information, managing permissions, planning sprints, summarizing KPIs, and resolving engineering friction points. It enables our engineering teams to move from planning to execution faster and with greater quality and consistency.

The early results from our use of this tool show extensive time savings, which projected over a full year would mean 73,000 fewer hours of engineering time required for the same output.  We’ve also seen greater developer satisfaction and faster movement from planning to execution.

Related products:

Azure DevOps, Azure AI Service

ADO Work Item Assistant: Automating our ADO processes

Building consistent, high-quality ADO work items manually can be time-consuming and prone to errors. Our ADO Work Item Assistant is a generative AI-powered tool that streamlines the creation and understanding of Azure DevOps work items, including features, user stories, tasks, bugs, and custom item types.

The benefits of our assistant include:

• Greater efficiency: The potential to cut the amount of time it takes to craft an ADO feature or user story in half (50%).
• Project delivery enhancement: A streamlined approach mitigates errors and inconsistencies.

By leveraging the power of AI within Azure DevOps, we can significantly simplify and accelerate the work-item authoring process for our product management and engineering teams, improving quality and reducing workload.

Related products:

Azure DevOps, Copilot Studio, ES Chat

Automation hub and catalog: Solving task fragmentation

Large enterprises face major productivity challenges stemming from scattered information, fragmented systems, and reliance on numerous disconnected apps. This fragmentation leads to increased meetings, duplicative effort, and significant time spent on lower-level tasks.

Automation Hub/Automation Catalog is our customizable Teams app—built on Power Platform and Power Catalog—that addresses this challenge by applying AI-powered automation solutions that integrate seamlessly with your existing systems. Common automations include a daily consolidated task list, cancelled-meeting alerts, flags for important emails, and nudges on unanswered messages. The app streamlines workflows and jump-starts productivity gains, enabling you to enhance operational efficiency while maximizing your ROI.

Related products:

Microsoft 365 Copilot, Microsoft Teams, Power Platform

The future of AI in IT

As enthusiastic as we are about our progress so far, we’re even more excited about the great potential that AI agents show in terms of lowered costs, time saved, and boosted productivity across our IT operations.

“The advent of AI agents is the next big step in AI-powered innovation. We are actively working towards our vision of deploying, governing, and managing a fleet of agents across our IT organization, pushing Microsoft to the boundaries of the AI Frontier.”

Monika Gupta, partner group engineering manager, Microsoft Digital

We’re anticipating that these solutions will continue to scale up as we further optimize and standardize large language models and agent patterns in our engineering organizations. Multi-agent orchestration will make an impact on governance and vulnerability response, and autonomous actions will become more common in everyday IT workflows. Measurement rigor will continue to sharpen, ensuring that value is tracked and amplified as AI tools and technologies proliferate across the enterprise.

“As exciting as it’s been to see the many practical applications of AI across our IT portfolio the last two years, 2026 is shaping up to be even more exciting,” says Monika Gupta, partner group engineering manager in Microsoft Digital. “The advent of AI agents is the next big step in AI-powered innovation. We are actively working towards our vision of deploying, governing, and managing a fleet of agents across our IT organization, pushing Microsoft to the boundaries of the AI Frontier.”

Key takeaways

Here are some important factors to consider as you contemplate adding AI tools and innovations to your IT operations and workflows:

• Think holistically: Evaluate the major categories of your IT organization where AI can drive transformation—network management, tenant and device governance, and employee productivity.
• Leverage AIOps for resilience: Use AI-driven operational tools to automate troubleshooting, reduce downtime, and improve decision-making across your network infrastructure.
• Embed compliance into workflows: Implement AI-fueled governance solutions that make compliance intuitive and self-service, reducing risk while fostering a culture of accountability.
• Accelerate vulnerability response: Adopt multi-agent AI systems to proactively identify, prioritize, and remediate security vulnerabilities, minimizing exposure windows and operational risk.
• Boost productivity with AI assistants: Deploy AI Copilots and automation hubs to streamline engineering tasks, reduce cognitive load, and eliminate inefficiencies caused by fragmented systems.
• Plan for scale and autonomy: Prepare for the next wave of AI in IT—multi-agent orchestration, autonomous workflows, and rigorous measurement frameworks to amplify value across the enterprise.

Try it out

Learn more and sign up for a free trial of Microsoft Azure AI apps.

Related links

• Learn how we’re enhancing our network reliability with AIOps and Network Infrastructure Copilot.
• Find out more about our AI-powered leap into vulnerability management at Microsoft.
• Check out our playbook for becoming a Frontier Firm in the AI era.
• Explore our 5-step guide to enterprise AI maturity.
• Discover how we’re transforming the employee experience at Microsoft with AI.
• Read about how we’re using AI to reinvent our network security practices.

The post AI at scale: How we’re transforming our enterprise IT operations at Microsoft appeared first on Inside Track Blog.

We’re taking this challenge head-on today, working to build trust between leaders and employees using all the communications strategies at our disposal. One of the most effective tools we employ to meet this goal is Microsoft Viva Engage, a powerful platform that facilitates two-way communication on the front end and provides rich analytics and insights on the back end.

Viva Engage is integrated with Microsoft Teams, Outlook, and SharePoint, which allows us to better connect with our employees in the flow of their work.

Another key internal communications channel is Ask Me Anything (AMA) events, which give our senior leaders the opportunity to have an authentic dialogue with employees. These events take full advantage of the combined power of Viva Engage and Teams to produce outstanding results.

“When we look at our most effective channels for informing and connecting with Microsoft employees, Viva Engage and AMAs are among the top,” says John Cirone, senior director of global employee and executive communications. “Those channels didn’t really exist three years ago, so that’s a sign of how our internal comms practices continue to evolve as we lean more into a social-first, two-way dialogue approach to our communications.”

As the company embraces its role as an AI-first Frontier Firm, we are connecting with our employees more deeply than ever before, keeping them tightly engaged with our mission and overall goals.

“Trust has proven to be this magical, key ingredient in driving change and strengthening engagement between employees and leaders. Viva Engage and Ask Me Anything events are extremely valuable in helping us foster trust, encourage authenticity, and listen to our employees at scale.”

John Cirone, senior director of global employee and executive communications

Building trust to change our culture

When Satya Nadella took over as Microsoft CEO in 2014, he shifted our company culture from being siloed and internally competitive to more open, agile, and collaborative. This has led to a lot of change over the last decade, a shift that has been compounded by the AI revolution.

That’s why Cirone and other senior leaders have identified building trust and facilitating two-way communication at Microsoft as linchpin goals of our internal comms strategy.

“Trust has proven to be this magical, key ingredient in driving change and strengthening engagement between employees and leaders,” Cirone says. “This dynamic has only increased in recent years, as studies show that trust is declining across the board in society and within companies worldwide. Viva Engage and Ask Me Anything events are extremely valuable in helping us foster trust, encourage authenticity, and listen to our employees at scale.”

That’s why we’ve diversified our internal comms strategy, going from an approach centered on one-way communication channels (like email) to one that incorporates two-way tools like Viva Engage, a platform that allows employees to express themselves, connect with others, and build community across the company. It also enables our leaders to communicate at the scale of the enterprise with incredible reach.

Nadella himself uses Viva Engage to communicate regularly with the entire organization, posting about twice a month and covering everything from major company news and strategic shifts to more fun, practical content. A recent post by Nadella with ideas for prompts to use in Microsoft 365 Copilot generated more than 2,200 employee reactions. (Viva Engage also allows communicators to easily access detailed analytics, which make it simple to track messaging impact.)

Similarly, holding regular AMAs and Town Hall events with Microsoft leadership in recent years has been a big part of building trust and keeping the company informed and engaged.

“An AMA event is all about trying to address the questions that are most on our employees’ minds,” Cirone says. “It’s a chance for our leaders to demonstrate listening and responding at scale, by tackling key topics in a timely manner. I see it as part of our overall company belief in the importance of listening and commitment to two-way dialogue.”

“One of the most important shifts in our strategy for Viva Engage is the deep integration of the community experience into Teams. It’s not just a technical integration—it’s a fundamental change in how leaders and employees connect, collaborate, share knowledge, and build trust in the flow of work.”

Jason Mayans, vice president of product management and analytics, Viva Engage

Reaching employees in the flow of work

Another powerful aspect of Viva Engage is that it works seamlessly with Microsoft Outlook and Microsoft Teams, allowing communicators and admins to reach employees where they spend most of their time working.  

“One of the most important shifts in our strategy for Viva Engage is the deep integration of the community experience into Teams,” says Jason Mayans, vice president of product management and analytics for the Viva Engage product group. “It’s not just a technical integration—it’s a fundamental change in how leaders and employees connect, collaborate, share knowledge, and build trust in the flow of work.”

Evolving communication with Viva Engage

This is a huge step, because so many of our employees use Teams as their main communications hub. Viva Engage community content and conversations can now be brought directly into their daily work experience, side by side with their other chats and channels.

For communicators, this means they can create one announcement and send it out across Outlook, Teams, and Viva Engage (or whichever subset of channels they prefer). Then, they can use the AI-powered analytics provided by the software to monitor engagement at different levels.

“In the analytics tool you can see the types of engagements that your people are having, and through what interface—Viva Engage for the web, Teams, and Outlook,” Mayans says. “You can see how they’re interacting. You can monitor sentiment and theming to give you deeper insight into what people are talking about. You can see a summary view, or you can drill down to see analytics on individual conversations. It’s incredibly powerful.”

Engaging employees through major campaigns

This year marked Microsoft’s 50^th anniversary, and our internal communications team wanted to honor the occasion by building both awareness and engagement across the company. So, they developed a “50 Change-Making Moments” countdown campaign to highlight major company milestones over the years.

Viva Engage was an integral part of this effort, providing a central platform for storytelling across the company, allowing both leaders and employees to share their reflections.

The results spoke for themselves.

“Over the course of several months, the campaign ended up reaching almost the entire company and had an 89% net positivity rating,” Cirone says. “The leaders’ posts sparked employees to share their own memories, which generated super-strong engagement and a great lead-up to the all-company anniversary celebration.”

Another major campaign we do every year at Microsoft centers around our Employee Giving Program, which began more than four decades ago and has been a long, sustained success story. Over the history of the program, Microsoft and its employees have contributed more than $3.4 billion to support charitable causes.

“We leveraged Viva Engage to help promote the Giving Campaign across the company, which produced a ton of enthusiasm. Leaders and employees could post about their favorite nonprofit causes, and we were able to highlight some great stories about how the campaign is making a difference in the world.”

Amy Morris, director of global employee and executive communications and employer brand

As part of this campaign, Microsoft matches every dollar our employees give to eligible nonprofits. When employees volunteer their time for an approved cause, the company also donates $25 per volunteer hour to the nonprofit.

Since giving is such a significant part of our company culture, we’ve used Viva Engage extensively for the past two years to help employees rally around the annual campaign.

“We leveraged Viva Engage to help promote the Giving Campaign across the company, which produced a ton of enthusiasm,” says Amy Morris, director of global employee and executive communications and employer brand. “Leaders and employees could post about their favorite nonprofit causes, and we were able to highlight some great stories about how the campaign is making a difference in the world.”

Balancing dialogue with respect and accountability

The growth of two-way internal employee communications in Viva Engage has built trust and increased engagement, but it’s also driven the need for more robust communications governance. We’ve had to implement comprehensive safeguards that ensure digital safety, respect, and accountability on Viva Engage.

Our employees have strong opinions on topics ranging from cafeteria menus to the latest political news. Our goal is to ensure that sensitive conversations stay in places where those who wish to participate can opt into them, rather than spilling out into the company at large.

“You have to balance the risks and rewards of creating this open, transparent space for employees to communicate,” Morris says. “We’ve learned quite a bit in the last couple years, and we’ve developed systems for monitoring employee sentiment on different hot-button issues and moderating content on Viva Engage.”

Making sure the right governance protocols are in place allows us to listen to our employees while protecting their colleagues and the company as a whole.

“We want a corporate communication space that is vibrant, yet remains respectful and safe. The goal is balance. That’s why we’ve partnered across IT and other teams at Microsoft to establish the right protocols and tools that help us maintain digital safety companywide.” 

Ife Kolawole, senior product manager, Microsoft Digital

Ife Kolawole is a senior product manager for Microsoft Digital, the company’s IT organization. One aspect of his work centers around driving the development and improvement of content moderation tools for Viva Engage, which are a crucial part of creating a safe and supportive environment at Microsoft.

“We want a corporate communication space that is vibrant, yet remains respectful and safe,” Kolawole says. “The goal is balance. That’s why we’ve partnered across IT and other teams at Microsoft to establish the right protocols and tools that help us maintain digital safety companywide.” 

With nearly 5,000 different Viva Engage communities across the company, moderators need help identifying sensitive posts in a timely way. Kolawole, who also serves as a moderator for the platform, appreciates the power of AI in helping him do that work proactively at scale.

“Viva Engage features an AI-powered moderation tool that intelligently detects sensitive themes and keywords before a potentially problematic post can gain traction,” he says. “It helps us preserve respectful, productive dialogue at scale and fosters a trusted collaboration and communication space.”

Communicating for meaningful change

Internal communications is a huge part of what we do at Microsoft—and it’s not something masterminded by just a few people at our corporate headquarters. That’s why Cirone and Morris lead Global Employee & Executive Communications (GEEC), a community of more than 1,000 communications professionals scattered throughout our global operations.

The GEEC organization works collaboratively to align messaging, elevate executive voices, and build trust across the company. Its members are constantly deploying new tools—like Viva Engage and Microsoft 365 Copilot—and strategies that increase engagement and strengthen Microsoft’s company culture through communications.

“Our goal is never to just adopt a new IT tool—our goal is to change the company,” Cirone says. “We don’t do internal comms for the heck of it. We do it to create dialogue, to listen, to inform, and to drive cultural change for the entire organization, so that our employees can to do their best work.”

Key takeaways

Here are a few principles to be aware of as you consider your own internal communications strategy:

• Prioritize building trust between company leaders and employees, which can pay big dividends in the long run. We’ve made this the cornerstone of our internal comms philosophy.
• Two-way communication channels are becoming the best way to connect with employees internally. Tools like Viva Engage and Ask Me Anything events promote dialogue, encourage authenticity, and help employees feel heard.
• Measure your internal comms impact. Viva Engage allows you to capture detailed analytics around reach, engagement, and sentiment so you can understand what topics and types of content are resonating with your employees.
• Leverage integrated tools to communicate across multiple channels. We use the Viva Engage integration with Teams and Outlook to reach employees in the flow of their work, so they don’t have to launch a dedicated outreach tool to stay informed.
• Companywide campaigns are great opportunities to build engagement. Having leaders share their thoughts about company milestones and community-focused initiatives are feel-good moments that encourage employees to share their own experiences.
• Balance openness with safety and respect. Take advantage of built-in moderation tools—including AI-driven features—to flag potentially sensitive posts and limit negative fallout on your comms platforms.

Try it out

• Check out how your organization can benefit from Viva Engage.
• Read our guide for deploying and driving adoption of Viva Engage.

Related links

• Learn more about our Global Employee & Executive Communications (GEEC) community at Microsoft.
• Find out how we’re accelerating a cultural transformation at Microsoft through Viva and AI.
• Discover how we’re deploying Microsoft 365 Copilot in Viva Engage.
• Read about how Microsoft Viva became a business transformation engine at Microsoft.
• See how we’re driving Microsoft 365 Copilot adoption with help from Viva Engage.

The post Supercharging our internal communications at Microsoft with Viva Engage appeared first on Inside Track Blog.

They dubbed it the “Scream Test.”

“We didn’t have a great server inventory and tracking system, and we didn’t always know who owned a server,” says Brent Burtness, a principal software engineer in Commerce Financial Platforms, who was one of the leaders for the effort in his group. “So, we essentially just turned them off. If someone screamed—‘Hey, why’d you turn off my server?’—then we’d know it was still being used.”

Today, the basic idea behind the Scream Test is being used across the company, but in a more holistic way. Importantly, it’s been incorporated into the overall lifecycle management of our computing infrastructure. And, through the automation tools provided by Microsoft Azure, we have a much more efficient process for making sure that we’re saving time and money by reducing the number of underused machines we operate, monitor, and maintain.

“We thought we were going to get rid of a small number of machines that weren’t being used. But we found the actual share was about 15% of all machines, which saved us a lot of effort of moving those unused machines to the cloud. In other words, we downsized on the way to the cloud, rather than after the fact.”

Pete Apple, cloud network engineering architect, Microsoft Digital

Uncovering more than expected

The Scream Test was part of the huge effort to evaluate our on-premises compute resources before we began moving to the Azure cloud. After all, why spend resources moving something that isn’t needed?

Pete Apple, who helped develop the concept of the Scream Test, is a cloud network engineering architect in Microsoft Digital, the company’s IT organization. Looking back, he remembers the surprising results that emerged when they began shutting down specific servers to see who noticed.

“We thought we were going to get rid of a small number of machines that weren’t being used,” Apple says. “But we found the actual share was about 15% of all machines, which saved us a lot of effort of moving those unused machines to the cloud. In other words, we downsized on the way to the cloud, rather than after the fact.”

As part of this process, Apple explains, our engineers looked at two related factors to reduce inefficiencies in our usage of computing resources.

The first was to identify systems that were used infrequently, at a very low level of CPU (sometimes called “cold” servers). From that, we could determine which systems in our on-premises environments were oversized—meaning someone had purchased physical machines according to what they thought the load would be, but either that estimate was incorrect or the load diminished over time. We took this data and created a set of recommended Microsoft Azure Virtual Machine (VM) sizes for every on-premises system to be migrated.

“We learned that there’s a lot of orphaned, or underutilized, resources out there,” Burtness says. “These were cases where the workload was so small on a server—like under 5% CPU—that it didn’t make sense to host it on its own machine. We could then move the task or application and get it down to just one or two CPUs on a virtual machine.”

At the time, we did much of this work manually, because we were early adopters. The company now has a number of products available to assist with this review of your on-premises environment, led by Azure Migrate.

Another part of the process was determining which systems were being used for only a few days a month or at certain busy times of the year. These development machines, test/QA machines, and user acceptance testing machines (reserved for final verification before moving code to production) were running continuously in the datacenter but were really only needed during limited windows. For these situations, we applied the tools available in Azure Resource Manager Templates and Azure Automation to ensure the machines would only run when needed.

Automating with Azure

Today, we don’t have to rely on anything as crude as the Scream Test to find unused and underused computing resources. With 98% of our IT resources operating in the Azure cloud, we have much greater insight into how efficient our network is, so much of the process can be automated.

“We’ve found this effort much easier to manage in the cloud, because all our computing resources are integrated with the Azure portal,” Apple says. “They have an API system and offer various tools within Azure Update Manager and Azure Advisor to help with cost efficiency. It’s kind of like a modern version of Clippy—’Hey, it looks like your VM isn’t being used much. Do you want to downsize that or turn it off?'”

(For the uninitiated, Clippy was the Microsoft Office animated paperclip assistant introduced in the late 1990s. It offered tips and help with tasks, like writing and formatting documents. Clippy became iconic for its quirky suggestions, including recommending that you remove things from your desktop that you weren’t using.)

“With everything being in the Azure portal or in Azure Resource Graph, it’s much more streamlined, and makes it easier to get that data out to the teams. They can then go into the portal and clean up the resource.”

Brent Burtness, principal software engineer, Commerce Financial Platforms

And simply taking the step of turning off stuff that we weren’t using turned out to be very effective. Thanks, Clippy!

Today, we approach this challenge in a more efficient and sophisticated way, taking advantage of Azure tools like Update Manager and Advisor.

“With everything being in the Azure portal or in Azure Resource Graph, it’s much more streamlined, and makes it easier to get that data out to the teams,” Burtness says. “We can run automated queries with Azure Resource Graph. Then we bring that information into our internal Service 360 tool, which we use to give action items to our developers. Each item gives them a link to Azure portal, and they can then go into the portal and clean up the resource.”

Managing for the lifecycle

One of the most important things we learned by using the Scream Test to identify inefficiencies and moving our systems from on-premises servers to the cloud was that it’s an ongoing process, not a fixed-end project.

“We had this idea that it was going to be a one-time event, that we’ll move to the cloud and then we’ll be done,” Apple says. “A better understanding is that it’s a lifecycle. We have integrated this concept of continual evaluation into our processes around everything that’s still on-premises, because we still have labs, we still have physical infrastructure.”

We continue to do this evaluation on a regular basis with both physical and virtual computing resources, because needs and usage are constantly changing.

Cutting our cloud costs

“Now we have a basic process around a six-month cycle,” Apple says. “So, every six months we ask, does this still need to be on-premises or should we start moving it to the cloud? And we do the same thing with our cloud resources. Who’s still using these VMs? And we still go through the same review process to see if it’s needed, or if we can shut it down or move it.”

This has resulted in significant cost savings for the company. “We’re up to about 15% to 20% less compute cost, depending on the organization, because of this much better understanding of our business needs,” Apple says.

Better governance, increased security

Another major benefit of this process was establishing much stronger governance of compute resources across the entire organization.

“When we first did the Scream Test, we weren’t always really sure who owned what, in some cases,” Apple says. “We’ve fixed that as part of this process. This governance aspect is a key part of being more efficient with our resources.”

Burtness explains why this is so important.

“It’s critical to know exactly who to contact when there’s something wrong with the server,” Burtness says. “Now, with clearer ownership, clearer accountability, and better inventory, it’s a much better experience.”

Better governance also means tighter security, according to both Apple and Burtness.

“This is really important when it comes to threat-actor response,” Apple says. “Unused servers can often be an entry point for hackers. Or, say we discover that a machine or server is getting hacked; you need to talk to who owns it. If you don’t know, it takes you longer to track them down and combat the hack. That’s not great. Improving our governance has definitely made securing our environment easier.”

Key takeaways

Here are some things to keep in mind when managing your own enterprise compute resources for greater efficiency:

• It’s not a one-time exercise. For the best results, you should be evaluating your computing resources on a regular schedule to identify ”cold” servers and unused infrastructure.
• Adjust for variable usage patterns. It’s not just about unused servers. Some machines may only be needed for a business function during certain busy times of the year. Consider turning the machines on just to handle the load during those periods and turning them off the rest of the year.
• Use Azure tools for greater insight. If you’re operating your infrastructure in the Azure cloud, you can much more easily monitor and address orphaned resources using automated tools such as Azure Advisor, Azure Resource Graph, and the Azure portal.
• Apply your savings to other priorities. “The more efficient you are, the more savings can be applied to other projects or given back to your manager—who is going to be very happy with you,” Apple says.
• Saving money is not the only benefit. You’ll not only save operating costs, you’ll have a reduced maintenance and monitoring load, better governance, and fewer security vulnerabilities.

Try it out

• Get started on your own cloud journey with the Cloud Adoption Framework for Microsoft Azure.
• Learn about Azure process automation and sign up for a free trial.

Related links

• Read about our IT journey to becoming a cloud-first organization with Microsoft Azure.
• Discover the five principles that guided our move from on-premises infrastructure to the cloud at Microsoft.
• Explore the benefits of Azure Advisor.
• Get more details about the Azure portal.

The post Moving from a ‘Scream Test’ to holistic lifecycle management: How we manage our Azure services at Microsoft appeared first on Inside Track Blog.

In the past, Julie might have interacted with different apps and websites to get help with each of those tasks. Today, thanks to the power of agentic AI and Microsoft Copilot Studio, Julie can turn to a single portal to handle all of it: the Employee Self-Service Agent.

This agentic tool, which will soon be released publicly as a free add-on for the Microsoft 365 Copilot license, has already made a big impact on the lives of our employees, saving them time, effort, and frustration. We call it the “one-stop shop” experience of employee self-service.

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

“Our employees rely on AI tools like Copilot to help get their work done. And the same is now true for resolving an issue related to facilities.”

Becky West, principal group product manager, Microsoft Digital

Of course, employees like Julie also need assistance with other common job-related tasks, like getting their human resources (HR) questions answered or fixing a technical issue with their device.

Those are also important categories included in the Employee Self-Service Agent, something the flexibility and extensibility of Copilot Studio makes possible.

“Our employees rely on AI tools like Copilot to help get their work done,” West says. “And the same is now true for resolving an issue related to facilities, HR, or IT support. We live in an AI-powered world, and this agent meets the moment for our people.”

In this story we share how we’re using the Employee Self-Service Agent in the real estate and facilities space, but it does much more than that. Our employees also use it to get help with IT problems and answers to their HR queries, and we expect to add other key areas soon, such as finance and legal. Available to all Microsoft employees worldwide, the full agent is already delivering a significant boost in productivity, cost savings, and user satisfaction across the company.

Everyday use cases for agentic assistance

Julie might not need IT support or help with an HR issue every day. But she’s always on the hunt for her favorite foods for lunch.

In our existing dining app, employees could look up that day’s menu for a specific building cafeteria, but they couldn’t just ask, “Hey, where can I get some good teriyaki on campus today?”

With the Employee Self-Service Agent, now they can.

“Searching on type of cuisine or dish is one of the top requests we were getting,” says Balaji Radhakrishnan, principal software engineering manager for the dining team. “It was an important feature missing from our existing apps, and we solved that with the employee-assistance agent.”

Employee Self-Service Agent screenshot

Not only can the agent help Julie locate the perfect lunch, it also connects her to the tool where she can order and pay for it. This streamlines the process for her—she doesn’t have to remember which website or app to call up to procure her teriyaki treat. (In the future, we plan to extend the functionality so the agent remembers your previous food choices, and you can order right from the agent.)

Dining is just one of the facilities-related experiences we targeted when developing the Employee Self-Service Agent. Other tasks include:  

• Lobby and visitor services – registering a campus guest
• Parking – registering a car to park on campus
• Maps – navigating around a building or a campus
• Facilities tickets – getting help with office furniture, lighting, HVAC, or other building issue
• Transportation – calling a shuttle for a ride between buildings or finding commuting help
• Finding a space – locating a place to relax, work, or connect with colleagues

“We started out by looking at the services we already offered,” West says. “We thought about what tasks would be in highest demand, where that information or transaction lived now, and how best to surface it. The more we explored the power of the agent, the wider the variety of experiences we were able to incorporate.”

Saving time and reducing frustration

Resolving employee pain points and saving time are two of the key advantages inherent to this area of agentic employee assistance. Consider the common employee task of registering a business-related campus guest (such as an interview candidate or a prospective customer).

“If we can handle 50%—600,000—of these business-related visitor registrations through the Employee Self-Service Agent, that adds up to 50,000 hours of employee time each year.”

Bhavani Paruchuri, senior product manager, Microsoft Digital

According to Bhavani Paruchuri, a senior product manager in Microsoft Digital, in 2024 Microsoft saw more than 2 million registered visitors at our buildings worldwide. Roughly 1.2 million of these were business-related guests.

Previously, employees had to email or talk to lobby hosts (front-desk staff) when they wanted to register a guest; the host would then enter visitor details into the Guest Management System. Now, the Employee Self-Service Agent provides a simple form within the chat, asking for details like guest name, email, purpose, building number, and date. Once the form is submitted, the system confirms it and sends a QR code directly to the guest via email.

“We calculated that this new process could save at least five minutes for each guest registration,” Bhavani says. “If we can handle 50%—600,000—of these business-related visitor registrations through the Employee Self-Service Agent, that adds up to 50,000 hours of employee time each year. So, just in this one area alone, the agent can have a big impact on overall productivity.”

Those savings add up, and quickly.

“Once you start using the agent for dining, you use it daily. As we added in cuisine and price filtering and other functionality that wasn’t available before, you could see it was a big differentiator from what the previous tools could do.”

Erik Downing, principal product manager, Microsoft Digital

One of the reasons we decided to include facilities-related help early on in the development of the Employee Self-Service Agent is that these common tasks would help increase usage of the new portal—building a habit with our workers that would have long-term benefits.

We have already seen employees used to finding a meal with the agent also using it to solve other challenges, including in the HR and Support spaces.

“Once you start using the agent for dining, you use it daily,” says Erik Downing, a principal product manager with Microsoft Digital. “As we added in cuisine and price filtering and other functionality that wasn’t available before, you could see it was a big differentiator from what the previous tools could do.”

West explains how this can have an outsized effect on promoting product adoption.

“If people get in the daily habit of using the agent for these routine tasks, they’ll be more comfortable going to it for other things,” West says. “Then you can really start to scale the agent up and see the larger impact across more areas.”

Filing a service request with the help of AI

Julie gets to work one morning and is dismayed to discover that her adjustable desk will no longer rise to a standing position. She needs to open a facilities ticket for help.

“The AI automatically picks out the problem class and the problem type; presents a form with the details; asks for confirmation; then kicks off the ticket right from there. It’s all in one place, AI-driven, and truly agentic in terms of task completion—and it will only get better.”

Sonaly Choudary, senior product manager, Microsoft Digital

In the past, this would have required Julie to send Facilities an email with a description of the problem, or she would have had to track down the right app or web form for the same purpose.

Now, she can simply snap a photo of the broken desk and upload it to the Employee Self-Service Agent.

The agent will open a form and use information from the photo to create the help ticket right there. This image-based technology, like natural-language chat, is something that our previous apps couldn’t do, which reflects the power of AI. 

“Whether you upload a photo or just describe your issue using natural language, we’ve really pushed this tool to be as agentic as possible,” says Sonaly Choudary, a senior product manager who works on facilities technology products for Microsoft Digital. “The AI automatically picks out the problem class and the problem type; presents a form with the details; asks for confirmation; then kicks off the ticket right from there. And then you can query the agent to get status updates on it. It’s all in one place, AI-driven, and truly agentic in terms of task completion—and it will only get better.”

How Customer Zero makes our products better

Because Microsoft employees are the first ones to use our newest products and features, we have the opportunity to roll them out gradually and test them under actual enterprise-work conditions, which enables us to gather valuable feedback and telemetry. This data is then fed back into the product development process to make key improvements. We call this our Customer Zero philosophy.

“We were pioneers as Customer Zero in showing the need for these services in an employee-assistance portal, and the product group saw that need.”

Michelle Schaefer, principal product manager in Microsoft Digital

In the case of the Employee Self-Service Agent, we began product development by tackling HR and IT support, which were key areas to capture cost savings.

But how could we get even wider usage of the product? We turned to our real estate and facilities functions.

“The facilities and real estate aspect of Microsoft Digital is unique, in that it focuses on the employee experience at the company, literally in the buildings,” says Michelle Schaefer, a principal product manager in Microsoft Digital. “All those tasks—getting lunch, parking, filing a facilities ticket, moving around the campus, inviting a guest—are universal for all our employees. We were pioneers as Customer Zero in showing the need for these services in an employee-assistance portal, and the product group saw that need. And we’re constantly gathering telemetry to learn how our workers can more easily discover the agent and have a better experience with it each time.”

Adding the facilities and real estate category to the Employee Self-Service Agent also helped our engineers learn more about building an agent that presents a “single pane of glass” to the user on the front end but incorporates so many different functions on the back end.

“Our strategy with this new natural-language agent is to augment our existing tools, which brings AI to the experience and gets the user to the right place.”

Thomas Po, senior product manager, Microsoft Digital

Each team has its own tools that compete for our employees’ attention.

“The challenge was to turn all those into a common experience for the user,” says Erik Orum Hansen, a principal engineering manager for Microsoft Digital. “That’s been a learning journey for us, as the organization pivoted to developing a single agent incorporating all these different functions.”

This single-portal approach makes it so much easier for users to explore their options and figure out the best way to accomplish the task, even as the underlying tools are still available.

We still have as many as 15 different tools that employees use today for campus related tasks, but we’re managing them more effectively—now our employees only need to use them when their use case is more challenging or detailed in nature.

“Our strategy with this new natural-language agent is to augment our existing tools, which brings AI to the experience and gets the user to the right place,” says Thomas Po, a senior product manager for Microsoft Digital. “The user may not have the specific facilities app they need on their phone, but everyone has Copilot, right? It’s about giving our employees access to information in more places and connecting them to the right tool or function.”

Employee Self-Service Agent screenshot

The Employee Self-Service Agent can also see when an employee took prior action, recognize that they might want to take the same action again, and suggest that action—for example, suggesting that they may want to reserve a shuttle ride to the same location they’ve visited previously.

“This allows users to have a more contextual, conversational experience,” says Ram Kuppaswamy, a principal software engineering manager in Microsoft Digital. “For example, for transportation needs they can just type, ‘Help me book a campus shuttle,’ and the agent can suggest options based on their previous ride history. Then it can call up a form to help complete the booking. Users really love it.”

Built on the power of Copilot Studio

We built the Employee Self-Service Agent with Microsoft Copilot Studio, a powerful platform that allows you to create and extend AI agents. The agent is designed so that our customers can customize it to fit their own business needs and integrate it with their existing technologies.

“We didn’t want a custom connector; we wanted to go with an out-of-the-box connector that worked with Dynamics,” he says. “There were some product iterations to deal with while we made sure it met Microsoft’s data-compliance standards, but ultimately it made it easier to show customers how simple it is to implement the agent—it’s a very low-code/no-code solution.”

Erik Orum Hansen, principal engineering manager, Microsoft Digital

When we built the part of the Employee Self-Service Agent that handled HR and IT Support needs, we were able to create connectors for major third-party service providers in those areas, such as Workday, SAP, and ServiceNow. (These connectors are now “out-of-the-box capabilities” that are included in the product.)

In the facilities and real estate space, we have numerous vendors that we work with to provide various campus services. Since we already used various existing internal applications to connect employee requests with these vendors, we were able to create connectors for the agent easily using Copilot Studio. More importantly, we were also able to use the out-of-the-box Dataverse connector that worked with our Dynamics 365 data, which cut down on development time.

“The agent functions as a single entry point, which then connects with the Microsoft Dynamics data,” Schaefer says. “We have numerous different facilities vendors in different parts of the world, but we didn’t have to build multiple connectors to those vendors because of the common Dynamics back end.”

Orum Hansen says this caused a small delay in the internal deployment of the product, but that it was worth it in the end.

“We didn’t want a custom connector; we wanted to go with an out-of-the-box connector that worked with Dynamics,” he says. “There were some product iterations to deal with while we made sure it met Microsoft’s data-compliance standards, but ultimately it made it easier to show customers how simple it is to implement the agent—it’s a very low-code/no-code solution.”

“We’re also previewing more multi-agent capabilities that are coming from Copilot Studio, which our customers will be able to incorporate into their own solutions. The product is just going to get richer and richer over time, as it extends into other lines of business.”

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

The future of workplace AI

In many ways, we’re still in the early stages of the revolution that AI agents are going to bring to the workplace.

But the Employee Self-Service Agent is a significant early marker on that path.

“The first step is to develop this agent that’s optimized for the HR, IT, and facilities verticals,” says Kirk Gregersen, corporate vice president of product for Microsoft Viva and Microsoft 365 Copilot Experiences. “We’re also previewing more multi-agent capabilities that are coming from Copilot Studio, which our customers will be able to incorporate into their own solutions. The product is just going to get richer and richer over time as it extends into other lines of business.”

As employees like Julie are already finding out, this new era of agentic AI is going to be a major improvement over what came before.

“Most companies already have some kind of employee-assistance portal solution,” Orum Hansen says. “With this new agent, there’s an opportunity to really reimagine the entire experience—to shed some of the old baggage and figure out how to do things differently. It’s going to lead to a more efficient workplace, along with more satisfied employees.”

Key takeaways

Here are a few factors to remember when implementing an AI-powered employee-assistance solution at your company:

• Pick high-value targets. Consider employee needs and the most commonly used assistance functions (using data where available), then develop a solution that addresses those areas. This will drive adoption and daily use of the agent.
• Customize the solution. Take advantage of the extensibility of Copilot Studio to develop an agent that fits your organization’s specific needs.
• Augment existing tools. Your employee-assistance agent can be the front door through which users find the tool they need. Over time, you can retire legacy tools and portals as the agent is able to complete the same functions on its own.
• Go beyond information retrieval. Employees want to be able to carry out tasks right from the agent, so incorporate forms and other technologies that allow them to accomplish their goal as quickly and easily as possible.
• Think outside the box. The image-driven feature we developed for filing a facilities ticket is a great example of applying the revolutionary abilities of AI to solve problems in new and innovative ways.    

Try it out

Learn more about the Employee Self-Service Agent.

Related links

• Read about the full scope of the impact the Employee Self-Service Agent is having on our organization.
• Learn about our strategic approach to agentic AI internally at Microsoft. 
• Explore how the Employee Self-Service Agent is helping Puget Sound-based Microsoft employees with their transportation needs.
• Explore how Microsoft HR is using Viva and Copilot to empower our employees.

The post Reimagining campus support at Microsoft with the Employee Self-Service Agent appeared first on Inside Track Blog.