Driving seller adoption of Sales Agent through role-based change management at Microsoft

For Microsoft sellers, one challenge remains remarkably consistent: The more time they spend on administrative work, the less time they spend with customers and making sales.

Opportunity records need updates. Forecast comments require review. Investment programs and licensing options live in different places. Preparing for a meeting can mean searching across customer relationship management records, email, and meeting notes.

To tackle this challenge, we developed Sales Agent in Microsoft 365 Copilot. This AI-driven platform gives our sellers one conversational entry point, allowing them to pull all the data and context they needed for a deal into one space.

But information retrieval was just the first step. As agentic AI has gotten more powerful, we realized it had the potential to fundamentally change how our sellers completed their day-to-day work. That’s the promise of becoming an AI Frontier Firm.

We also knew that just creating an amazing new AI sales platform for our employees wasn’t enough. Sales Agent needed to connect with how our employees actually worked, or it would never change long-standing work habits. Rethinking work is difficult, and AI hesitancy is real.

“If you have a broken process, just laying AI on top of it is not going to fix it. We had to fundamentally redesign the process to drive the outcomes we wanted to get to. And that’s where Sales Agent comes in.”

Rene Vejlby, senior business program manager, Business Innovation and AI Transformation, Small Medium Enterprises and Channel

One of our biggest Customer Zero takeaways throughout this process is that connecting AI to the work that matters for each role makes a huge difference in adoption rates. If you show your employees exactly how the technology will benefit them in their work, they will navigate the transition to a new way of working and become evangelists for AI in the workplace.

Rethinking how sales work is done

Our internal research has shown that about 70 percent of a seller’s time was being spent on non-customer-facing activities—researching accounts, preparing for meetings, following up afterward, coordinating across the team, and sending proposals and quotes.

The reason for this could be traced back to sheer information sprawl. Our sellers were navigating at least 15 different CRM, tracking, and communication tools on a daily basis, with the data they needed scattered across all of them.

This was a perfect challenge for AI to address. But without changing the way our employees worked, just adding another piece of technology—AI or not—was not the answer, our experts realized.

“If you have a broken process, just laying AI on top of it is not going to fix it,” says Rene Vejlby, a senior business program manager in the Small Medium Enterprises and Channel (SME&C) group. “We had to fundamentally redesign the process to drive the outcomes we wanted to get to.”

That meant setting a clear destination first: a hub where a seller could pull in contextual details and complete common tasks without ever leaving the interface.

“The goal has always been to keep our sales force in their flow of productivity while also keeping our systems of record up to date. Sales Agent gives sellers a single place to work without hopping from system to system.”

Steve Cohen, senior director of digital specialists, SME&C

Getting there was painstaking. Vejlby and his peers took every single workflow that our sellers used and broke it down step by step, asking of each one what AI could take over, what could be eliminated entirely, and what sellers could be doing with that recovered time instead.

“The goal has always been to keep our salesforce in its flow of productivity while also keeping our systems of record up to date,” says Steve Cohen, a senior director of digital specialists in SME&C. “Sales Agent gives sellers a single place to work without hopping from system to system.”

The Sales Agent user experience builds on previous platforms we’ve developed, like Viva Sales and Microsoft 365 Copilot for Sales. Crucially, it adds a chat-based “front door” that can retrieve information, interpret context, and support seller actions through natural language.

But delivering on that ambition meant rebuilding what Sales Agent itself was designed to do.

From information retrieval to workflow completion

When an earlier incarnation of Sales Agent came out a bit more than two years ago, the focus was information retrieval—reflecting the abilities of Copilot at the time. Agentic AI use cases were just starting out, and it was considered a breakthrough simply to get a seller’s CRM data and our wider data estate into one chat experience.

That was no small thing, given the many different systems and hundreds of reports our sellers were otherwise navigating to piece the same picture together.

But eventually, information retrieval became table stakes. Microsoft Cowork and other Copilot agents could do the same work—and do it well, deeply integrated across Microsoft 365—which meant Sales Agent needed a different reason to exist.

“Our charter kind of evolved from focusing on pure information retrieval to become more about workflow and action completion. Today, Sales Agent’s unique value is as an entry point for sellers to complete end-to-end workflows that are aligned to their jobs to be done.”

Ajay Nair, principal group engineering manager, Commercial Engineering and AI

It found one in doing tasks rather than fetching information. Today, Sales Agent works across up to 25 different systems of record, making updates and running workflows, so a seller can create a CRM opportunity, submit an investment request, or build a deal book without ever leaving the conversation.

This was a big transition, according to Ajay Nair. He’s the engineering owner for Sales Agent at Microsoft, and his team is in charge of internal implementation of the product for our own sellers.

“Our charter kind of evolved from focusing on pure information retrieval to become more about workflow and action completion,” Nair says. “Today, Sales Agent’s unique value is as an entry point for sellers to complete end-to-end workflows that are aligned to their jobs to be done.”

Delivering that functionality meant tapping the capabilities of Copilot Studio. Nair’s team used technologies like Model Context Protocol (MCP) to make Sales Agent a single “front door” for agentic services that other Microsoft teams had already built. The routing is invisible: Sellers type a prompt, and Sales Agent works out which agent to invoke.

AI adoption is a mindset shift

When it comes to change management in the AI space, we couldn’t count on traditional approaches that we might have used in the past when rolling out a new tool.

Our sellers may already feel they’re being successful using their existing methods, so they ask, “Why should I change?” There is also a learning curve and a real insecurity about the larger impact of AI that must be addressed.

“Sellers need to think about what outcome they want from AI, and then they have to craft their prompt around that. We have to get people used to that shift in mindset.”

Susan Neece Robien, senior director, AI Transformation, Adoption, and Change

It’s not a simple case of, Look what this new platform can do. Instead, as adoption specialist Susan Neece Robien explains, it’s more of a shift in how our employees think about their work.

“As we like to say, you have to ‘think differently, feel differently, and do differently,’” says Neece Robien, a senior director of AI transformation in Microsoft Sales. “Sellers need to think about what outcome they want from AI, and then they have to craft their prompt around that. We have to get people used to that shift in mindset.”

Because of this, much of our work around Sales Agent adoption started with the people, not the technology.

“I talked to one hard-nosed seller about his experience with Sales Agent, and he said that because of it he was no longer having to work on presentations at two in the morning. This made him a better husband and father, a better person.”

Jacqueline Stein, senior director, Learning and Skilling, Worldwide Learning

An important thing to remember is that people typically do their best learning when they are motivated to do so, and that means understanding how they will benefit from the new knowledge. Once they grasp that, it unlocks the willingness to change and use AI in their everyday work.

“It’s about the human motivation,” says Jacqueline Stein, a senior director of learning and skilling for Microsoft Worldwide Learning. “I talked to one hard-nosed seller about his experience with Sales Agent, and he said that because of it he was no longer having to work on presentations at two in the morning. This made him a better husband and father, a better person. And he can relay that to his customers as his lived experience.”

Role-based adoption

Broad capability descriptions and generic prompt training could create awareness of Sales Agent, but they did not always answer the question a seller would ask first: “How will this help with my job?”

So the team created specific role pages and validated them with people doing the work. Neece Robien described developing content for about 20 field roles, a task that included checking sales guidance with account executives. These scenarios had to represent work that happened often enough, with a benefit large enough, to earn attention.

“What matters is the flow of work and the tools that support it,” Neece Robien says. “Leading with the workflow makes the change more meaningful.”

Our Frontier Accelerator adoption program is designed to use peer learning and role-based practices to cultivate enthusiasm for AI applications among our sales professionals. The benefits include these five outcomes:

The teams also moved beyond one-way demonstrations. In peer huddles, sellers now discuss how they approach account planning or another job responsibility, then examine where Sales Agent can help. Our champions add credibility, because they can test realistic scenarios with customer and opportunity data that our adoption professionals may not have.

Regional adoption leaders can also provide local context. They address familiar habits, explain why the change matters, and create space for sellers to learn from one another.

Stein, a regional adoption leader based in the United Kingdom, described how teams are moving toward more dynamic learning and experimentation in the flow of work.

“It’s not just adoption programs aimed at sellers,” Stein says. “It’s sellers learning together, and us creating a framework and a blueprint for them to do that.”

An evolution in AI measurement

Sales Agent is also a great example of our changing approach to AI measurement strategy.

Our early reporting focused on monthly, weekly, and daily use of Sales Agent. Those measures showed whether people opened the product, but they didn’t reveal whether a deal moved faster or a seller spent less time on customer updates as a result.

“The fact that someone uses the agent does not necessarily mean that they’re driving business impact. Now that we’ve got a decent level of adoption, we’re pivoting toward looking at the business outcomes that are actually being driven through the product, rather than mere usage.”

Ajay Nair, principal group engineering manager, Commercial Engineering and AI

Today, we’re shifting our measurement toward actual business outcomes, including deal velocity and reduced seller toil. That change requires teams to identify the process they aim to improve before agent deployment, then decide what evidence will indicate a meaningful difference has been made.

“The fact that someone uses the agent does not necessarily mean that they’re driving business impact,” Nair says. “Now that we’ve got a decent level of adoption, we’re pivoting toward looking at the business outcomes that are actually being driven through the product, rather than mere usage.”

Our larger experience points to a significant Customer Zero insight: A capable agent and a thoughtful adoption plan are parts of the same implementation. Great engineering of the agent gives sellers a useful path through their workflows. Role-based scenarios, peer learning, and results-driven measurement help ensure stickiness and change the way our sellers actually carry out their day-to-day work. And the result is better business outcomes.