What Foot Locker’s Copilot Adoption Journey Teaches Us About Making AI Work in Organizations
During our recent Team Copilot session, Alex from Foot Locker joined us to share how they approached Copilot adoption inside a global organization. What made this conversation so valuable was not that everything was already figured out. Quite the opposite. It was an honest story about learning along the way, about experimenting, and about discovering what actually helps people change the way they work.
That honesty is important, because many organizations are currently in the same place. AI is available everywhere, expectations are high, but the question remains the same. How do you move from having AI tools to actually seeing people use them in their daily work?
One of the first things Alex emphasized was that Copilot adoption was never treated as a technical rollout. It was approached as a guided journey. The team understood early on that you cannot simply deploy a tool and expect employees to know how to use it. People need context. They need examples. And most importantly, they need to understand what is in it for them. Instead of focusing on features, the focus was on helping employees work better and feel more confident using AI in their day-to-day activities.
This mindset shaped the entire approach. Rather than immediately pushing full Microsoft 365 Copilot licenses, Foot Locker started with Copilot Chat. The goal was not immediate ROI, but familiarity. Employees learned how AI responds, how prompting works, and how AI can support tasks like summarizing information, organizing thoughts, or preparing presentations. By lowering the barrier to entry, adoption started to grow naturally. Within a few months, they reached more than twenty percent adoption globally, a number that surprised even their Microsoft counterparts, especially considering the program was driven internally without external change management support.
What became clear during the conversation is that adoption is strongly influenced by energy. The program succeeded because it was carried by people who were genuinely enthusiastic about the possibilities of AI. Training sessions were not positioned as mandatory learning moments, but as conversations. Employees were shown practical examples. Live demonstrations made the impact visible. Once people saw how a meeting transcript could be summarized in seconds or how a presentation could be structured faster, the value became tangible. The moment people experience the benefit themselves, resistance starts to disappear.
Another important element was consistency. Many organizations launch AI initiatives with excitement, only to see interest fade after a few weeks. At Foot Locker, the opposite happened. The team kept showing up. They created a central Copilot hub in SharePoint where employees could find learning materials, videos, prompt examples, and documentation. Corporate communications continued to refer employees back to this hub, making it a living environment instead of a static knowledge base. Over time, it became the place employees returned to whenever they wanted to learn something new.
Equally important was the creation of an internal community through Viva Engage. Alex described this as almost a social platform for Copilot learning. Employees shared questions, struggles, and successes. One of the biggest barriers to AI adoption is the fear of asking “basic” questions. By openly communicating that everyone, including the experts, was still learning, that barrier disappeared. Adoption accelerated the moment people felt safe to explore without judgment.
The conversation also touched on a topic many organizations struggle with today: measuring ROI. The reality is that productivity gains are not always easy to quantify. While dashboards and usage metrics provide insight, they do not tell the full story. The discussion shifted toward a more human perspective. How do employees feel working with AI? Do they experience less friction? Are they able to spend more time on meaningful work instead of repetitive preparation tasks? In many cases, AI does not simply save time. It gives time back. Time that can be used for thinking, creativity, and decision-making. That shift is harder to measure, but often where the real value lies.
Looking ahead, another interesting insight was how AI is changing skills inside organizations. Rather than creating one group of AI specialists, Alex described a future where people become AI experts within their own domain. HR professionals learning how AI supports learning and development, product managers using AI to streamline roadmaps, or marketing teams integrating AI into campaign development. The advantage will not come from knowing everything about AI, but from knowing how to apply it deeply within your own field.
At the same time, the session made clear that successful scaling requires preparation behind the scenes. Data governance, security, and proper information classification remain essential. Several organizations have learned the hard way that turning on AI without understanding data access can create risks. Collaboration between AI teams, cybersecurity, and governance functions is therefore not optional, but foundational.
What stayed with many people after the session was how human the entire story felt. The success was not driven by technology alone, but by curiosity, openness, and the willingness to learn together. AI adoption, in the end, is less about tools and more about behavior. When people feel invited into the change instead of pushed toward it, adoption follows naturally.
That is exactly why we host these Team Copilot sessions. Not to present perfect answers, but to share real journeys. Because hearing how others navigate this transition often provides more value than any framework or slide deck ever could.
A big thank you to Alex for openly sharing the Foot Locker experience with the Team Copilot community. Stories like these help organizations move from experimenting with AI to truly transforming how work gets done.
