When a team starts using AI, the first sign of life looks great. People are in the tools. Everyone has a trick. Something is happening.
Then you look closer. One person built a way to prep for client meetings. So did three others, each from scratch, each a little different. Nobody knows the others exist. Five people solved the same problem five times, and not one of those solutions is written down.
That's not adoption. That's waste that happens to look like progress.
The issue isn't effort. Your people are doing exactly what you'd want, finding what AI can do for their own work. The issue is that none of it compounds. Every build dies on the laptop it was made on. The next person starts from zero. The team gets smarter one person at a time, which is the slowest way to get smarter.
The move is to treat a good workflow as shared infrastructure, not a personal habit. When someone builds the meeting prep that works, that becomes the team's meeting prep. You capture it, you name it, and the next person runs it instead of rebuilding it.
This is the difference between a team where AI is a hobby and a team where it's a capability. In the first, value is trapped in individuals. In the second, one person's build raises everyone's floor.
So the question for a leader isn't how many people are using AI. It's whether what they build in week one is still working for the team in week ten, or whether someone's quietly building it again.
Find the workflow that's been built five times. Pick the best version. Make it the one everyone uses.