Somebody in your organization had a great idea: "Let's identify AI champions in every department! They'll drive adoption from the ground up!"

It's the kind of idea that sounds brilliant in a strategy meeting. Grassroots! Bottom-up! Organic!

And it almost always fails.

Not because the champions aren't enthusiastic. They are. They're usually the most tech-forward, most excited people in the building. That's exactly the problem.

The Champion Paradox

AI champions are selected because they love AI. They volunteer. They're excited. They attend every webinar. They can't stop talking about the latest model release.

Your average employee sees them and thinks: "That person is nothing like me."

The champion is an enthusiast. The people they're supposed to influence are skeptics, pragmatists, and people who just want to do their job without learning a new tool every quarter.

Enthusiasts don't convert skeptics. They alienate them.

What Actually Drives Adoption

Adoption doesn't spread through enthusiasm. It spreads through demonstrated value in context.

That means someone who does the SAME JOB as the skeptic shows them — in their workflow, with their data, on their problems — that AI makes their specific work better.

Not a demo. Not a training session. A peer showing a peer: "Look, this thing that used to take me three hours now takes twenty minutes. Let me show you exactly how."

A Better Model

Instead of AI champions, build AI proof cases:

1. Pick one team. Not the most enthusiastic team. Pick a team with a visible, painful, repetitive problem.
2. Solve that problem with AI. Hands-on. In their workflow. With their data. Messy and real, not polished and theoretical.
3. Measure the result. Time saved. Errors reduced. Output quality improved. Hard numbers.
4. Let THEM tell the story. Not the innovation team. Not the CIO. The people who actually did the work tell their peers what changed.

That story — from a peer, with real numbers, in a real context — does more for adoption than a hundred champion presentations.

Try This Monday

Identify one team that complains the most about a repetitive task. Offer to spend one hour helping them test an AI solution. Don't make it a project. Don't make it a program. Just show up and solve a problem.

One hour. One problem. One team. That's how adoption actually starts.

This is the exact approach I outline in AI Transformation — building adoption through demonstrated value rather than declared enthusiasm, with the governance structure to scale it once it works.

Stop appointing champions. Start creating proof.

— Vance Sterling