Lessons From Microsoft’s Enterprise Change Capability Journey in the AI Era

AI adoption is keeping change practitioners up at night. It's the challenge most organizations are wrestling with right now—not whether to adopt AI, but how to get people to actually use it.

In a recent webinar discussion between Prosci COO Michelle Haggerty and Microsoft's Director of Business Programs Steve Green, a central point emerged: organizations that achieve success with AI adoption do so not by relying solely on advanced technology, but by building robust human capability to drive and sustain implementation.

Microsoft has been committed to advancing its change management practices for more than a decade. This sustained effort has resulted in a 450% increase in customer adoption rates and the development of a global network exceeding 10,000 certified change practitioners. To gain first-hand insights from this journey, watch the full webinar recording below or continue reading for a detailed recap.

The Numbers That Tell the Story

Microsoft's Director of Business Programs Steve Green has spent the past decade building something that most enterprise leaders only dream about:

• 450% increase in customer adoption rates
• 80% feedback response rate on change programs—voluntary and anonymous
• Scaled from an initial target of 600 practitioners to enterprise-wide capability
• From 25-person change consulting team to 10,000+ certified change practitioners globally

But what makes these numbers meaningful is that they represent a fundamental shift in how Microsoft measures success. Microsoft stopped measuring success by whether they deployed technology on time and started measuring whether people actually used it.

Redefining Success From Features to Outcomes

Green asked practitioners to reflect on their own technology rollouts. "Was the success that you deployed 'it' and you've gone live," he asked, "or is it about the actual usage and that the outcomes are being realized?"

This simple question exposes the gap most organizations face. We deploy technology on schedule, check the box, and move to the next project—without ever measuring whether people actually adopted the change or if it delivered business value.

Michelle jumped in with something that resonated with listeners: "I think oftentimes our customers or our partners struggle with what is that value that change management returns. What does that look like? How do we make it tangible?"

That's the real challenge. Everyone knows change management matters in theory. But when leadership asks for proof, most practitioners can't point to concrete metrics beyond "we deployed on time" or "we completed training sessions."

Microsoft figured out how to make the value tangible. They shifted their success metrics entirely—away from implementation schedules and feature rollouts to the people side. Usage rates. Proficiency levels. Actual business outcomes. That's what drove the 450% increase in customer adoption.

So how do you actually make this shift in your organization?

Three Non-Negotiables for Transformation Success

When asked what organizations facing AI adoption challenges should prioritize, Green was emphatic about three things:

1. Define the outcome first

"It's great to say, 'the outcome is that we'll have Copilot on everybody's desk.' Great. But is that gonna drive value?" Green emphasized that practitioners must identify the real business outcome before any technology rollout.

What are the signals that will confirm you're moving in the right direction? What does success actually look like beyond deployment dates?

2. Secure active sponsorship

Leadership sponsorship isn't about executives showing up to kick-off meetings. It's about equipping sponsors to communicate the vision and business reasons for change. Green noted that practitioners often need to "script almost what their role is going to be"—coaching leaders on how to be effective sponsors.

3. Establish measurement systems

"How will we measure that we're achieving that outcome?" This question must be answered upfront, not as an afterthought. Microsoft uses both anonymous feedback (achieving 80%+ response rates) and telemetry data to spot challenges early and adapt quickly.

Why Humans Matter More Than Ever In The Age of AI

One of the most compelling moments in the conversation addressed a question Green receives almost daily: Why keep investing in training humans when AI can generate change management plans?

"While I could ask an AI engine, 'Help me drive adoption of Copilot—can you pull together a change management plan for me?' it will give you a plan," Green explained. "But that doesn't mean it will execute, and it doesn't mean that plan is appropriate for your organization."

His philosophy is clear: "We are using AI internally to complement, not to replace."

Green explained that while AI can draft communications or create initial plans, it cannot:

• Build the trust necessary for change
• Understand local context (culture, location, organizational dynamics)
• Challenge assumptions or stress-test logic
• Execute change—it only produces artifacts

AI helps accelerate time to outcomes and deliver more consistent change management plans, but humans must remain in the loop for all decisions.

"Would automated communications from a generic mailbox energize and excite you as a human?" Green asked. The answer is obvious—and it's why Microsoft maintains its massive investment in human capability even as they lead in AI innovation.

Building Capability That Scales

Microsoft's approach to scaling change capability offers a practical blueprint:

• Create a foundational baseline: Everyone involved in delivering change can access e-learning, research, and self-study materials. Instructor-led programs provide coaching and facilitation.
• Develop a common language: When a change manager talks to another change manager anywhere in Microsoft globally, they speak the same vocabulary.
• Make it practical and action-oriented: Programs aren't about sending people to multi-day training. They're about putting methodology into practice using language appropriate for each audience. As Green noted, "The answer isn't change management. What are you looking to achieve?"
• Share resources publicly: Microsoft publishes change management resources at adoption.microsoft.com, including success kits, scenario libraries organized by function, and adoption score metrics that go beyond basic usage tracking.

The Culture of Continuous Learning

Perhaps the most underrated aspect of Microsoft's success is their "learn it all" culture. Green described how the 80%+ voluntary feedback rate on change programs enables continuous adaptation:

"I get that feedback, which allows me to then make adaptations for future programs and future deliveries. Because we are using those signals from individuals coupled with telemetry data, we can usually spot when there is a challenge or a dip and react accordingly."

This iterative approach—measuring as you go, being curious about what's not working, and pivoting quickly—transforms change management from a one-time project activity into an organizational competency.

What This Means for Your Organization

The Microsoft story offers clear direction for change practitioners navigating AI adoption and digital transformation:

• Start with outcomes, not features. Redefine success metrics around usage, proficiency, and business value—not deployment schedules.
• Invest in human capability at scale. Build common language and foundational competency across everyone involved in change, not just dedicated practitioners.
• Use AI as complement, not replacement. Leverage AI to accelerate planning and increase consistency, but keep humans central to building trust, understanding context, and driving adoption.
• Create feedback loops. Build measurement systems that surface challenges early so you can adapt quickly rather than waiting for post-implementation reviews.
• Make change management accessible. Scale beyond the PMO or change management office to embed capability throughout the organization.

The partnership between Microsoft and Prosci over the past 11 years demonstrates what's possible when organizations treat change management as a strategic capability rather than a project checklist.

As Green concluded, "Change sticks through people, not through features." In the AI era, that truth matters more than ever.

Want to explore how to build enterprise change capability at your organization? Connect with our team to discuss scalable solutions tailored to your transformation goals.