Taming software licensing sprawl at Microsoft with an AI-driven solution

It’s a common challenge at any large enterprise—important, related data scattered across the organization, residing in disconnected silos. If only there was an efficient way to pull them together into a single system to aid transparency and business decision making.

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.”