Most AI rollouts in organizations follow the same script. Leadership gets excited. Someone gives a presentation full of big numbers about productivity gains. A policy gets drafted that's either so restrictive nobody uses anything or so vague nobody knows what's allowed. Then everyone goes back to their desks and keeps working the way they always have.
I see it as my personal responsibility to prepare my team for a new way of working. Not because AI is a revolution. Because it's a tool, and tools only work if people know how to use them. The difference between "we have AI" and "AI makes us better" is entirely about adoption, and adoption is a leadership problem, not a technology problem.
Here's what a thoughtful approach actually looks like. First, measure usage and effectiveness in a way that doesn't feel invasive. People clam up when they think they're being monitored. They open up when they feel supported. I share articles, host monthly lunch and learns, and keep the conversation going in a spirit of curiosity rather than compliance. The goal is to make experimentation feel safe.
Second, build trust across the organization so you can unlock the tools your team needs. Most companies have procurement processes that move at glacial speed. If your team doesn't trust you, and if the organization doesn't trust your team, getting access to the right tools becomes a political battle instead of a practical one. Trust is infrastructure.
Third, be specific about what AI is actually good for on your team. It's not good for everything. It's a strong thought partner. It handles the mundane so your people can focus on judgment calls. It accelerates research synthesis. It generates options fast so designers can evaluate instead of just creating from scratch. But it doesn't replace the twenty years of experience that tell you when something feels wrong. It doesn't replace talking to real users. It doesn't replace taste.
The organizations that get this right won't be the ones that moved fastest. They'll be the ones that moved most deliberately. They set clear boundaries, encouraged experimentation within those boundaries, and treated AI as something their people wield rather than something that replaces them.
Skip the hype deck. Build the practice.