Modernizing Work: The People Side of Microsoft Copilot Adoption

When a large utilities company decided to roll out Microsoft Copilot, their goal wasn’t just to modernize their systems, it was to modernize how people work. They saw AI as an opportunity to free up employees from repetitive, low-value work and give them more time to focus on high-impact, strategic tasks.   

This wasn’t just an IT project. It was what Eleanor Roe, a seasoned change management consultant, likes to call “workplace modernization.” And for a company with 25,000 employees, that meant transforming mindsets as much as technology.  

Microsoft Copilot for Real People 

The specific use case was a Microsoft Copilot-powered chatbot that would help employees find answers to questions about buildings, offices, and facilities. Previously, employees dug through SharePoint, emailed managers, or opened help tickets to find basic information. 

With a Microsoft Copilot chatbot, the goal was to make that information available instantly, through self-service—like a digital colleague who always knew where to find the right answer in a minute, versus a day or even days. 

Leading with a Proven Change Framework (Prosci ADKAR) 

For this implementation, Roe leaned on the Prosci ADKAR framework and while every stage was important, two stood out as critical: Desire and Knowledge. 

Building Desire 

Desire is about getting buy-in, and with AI, that requires extra care. Employees needed to understand that Copilot wasn’t here to replace them; it was here to support them. 

Roe and team made sure Leadership visibility-built credibility and helped ease anxieties about AI. They created a Change Champion Network, a group of mid-level managers and early adopters who acted as the voice of their teams. These champions helped Roe get real-time feedback, shared what was working, and became the early storytellers who helped others see the value of Microsoft Copilot. 

Building Knowledge 

Knowledge is the “how” of the change—the concrete, role-specific know-how of how to use AI entailed making a couple of key pivots to ensure this new way or working got embedded: 

• Experimentation over training or enablement: Instead of traditional “how-to” sessions, we encouraged “experimentation” — letting employees try, fail, and share. This shifted the mindset from fear to exploration. 

• Micro learning over training: We focused on bite-sized simple and small tips and guidance that are quickly accessible but deliver value and guidance when needed to use the chatbot 

• Storytelling over instructions: Rather than talking about technical features, the communication strategy focused on storytelling. 

To make it real, Roe analyzed work-order and interaction data to identify the top use cases and issues employees faced day-to-day, then built these 25 real-world use cases into the chatbot. These examples became the foundation for communications, training, and demos. People could see themselves in the examples, which made adoption more relatable and meaningful.  

Instead of, “Copilot can retrieve facilities data,” we said things like: 

• “Find answers in seconds instead of hours or days.” 

• “Get back time to focus on the work that matters most.” 

The Biggest Lesson: Focus on Experimentation, Not Perfection 

One of the biggest takeaways was that AI adoption isn’t about training; it’s about experimenting. Instead of formal training sessions, Roe encouraged employees to try it out, share their experiences, and learn from each other. That created a sense of psychological safety; people felt free to explore without worrying about doing it wrong. 

Final Thoughts 

Implementing Microsoft Copilot was more than introducing a new chatbot. It was about helping people work smarter, not harder; and building confidence in using AI as a trusted coworker.  

Success came down to three things: 

• Strong leadership advocacy that set the tone. 

• Relatable storytelling that humanized the change with related use cases. 

• A learning culture that valued curiosity and experimentation over perfection. 

Contact ChangeStaffing for support with AI change readiness and adoption within your organization. 

Thank you to Eleanor Roe for her thought leadership and for collaborating with us on this blog. 

Written by Kylette Harrison.