12 Statements for Leaders Who Already Rolled Out AI
2 Sept 2026
Agree or disagree: we have put more money into AI tools than into the skills to use them.
Agree or disagree: we have put more money into AI tools than into the skills to use them.
That is one of twelve statements I wrote for leaders who have rolled out AI and cannot tell whether anything actually changed.
Two more:
→ In my team, everyone is figuring AI out on their own.
→ Most of the AI initiatives we start in my team fade after a few weeks.
Every one came from something I have heard in a room with a leadership team. That first one also shows up in the data. Gallup found 44 percent of leaders use AI frequently, against 23 percent of the people who work for them. That split sits inside your own team.
AI is doing the small jobs. Summarising an email. Cleaning up a paragraph. Nothing has changed in how you decide which project to kill.
So I turned the twelve into a free assessment. Five minutes. You see where your team stands across four areas, and a thirty day plan arrives in your inbox.
Which one would you agree with?
Why AI tool access and AI readiness are not the same thing
The Gallup split, 44 percent of leaders using AI frequently against 23 percent of their own people, is the number I keep coming back to in coaching conversations. It means the gap is not really about the tools. Everyone has access. It is about who has been given the time, the permission and the specific use case to build real fluency, and who has been left to figure it out alone at the edges of a busy day.
I see this pattern most clearly when a leadership team tells me proudly that AI adoption is high, and then cannot answer a much simpler question: which decision changed because of it. High usage and real readiness are two different things, and closing that gap is what senior leaders actually need from AI in 2026.
Three signs your team has tools but not yet readiness:
→ People use AI for small, low-stakes tasks only, never for anything that actually gets reviewed
→ Nobody has said out loud what AI use looks like when it goes well versus when it goes wrong
→ Initiatives launch with energy and quietly stop being mentioned within a month