AI Change Management: Why People, Not Models, Are the Problem

The AI race is fierce. The translation gap is worse. What this week's news means for leaders managing people through change.

Hi there,

Not everyone cares about technology. And that is fine.

I spend most of my day connected to a screen, actively trying to keep up with what is happening in AI, and I still miss things constantly. If that is true for me, you should not feel bad about it. You have a business to run, you have people to manage, you have a life to lead. Nobody should be expected to stay across all the technical detail, and honestly I think the expectation that you should is part of the problem.

What I have come to believe, after leaving corporate life and spending a frankly unreasonable amount of time and money going deep on this subject, is that AI adoption is a change management problem before it is a technology problem. If you want real transformation, you have to start with people. Not with models, not with tooling, not with benchmarks. People.

Once you accept that framing, the resistance you are seeing starts to make sense. The pushback, the scepticism, the blank stares in meetings, the quiet foot-dragging. Most of it comes from fear, and the fear is rational, because nobody in any position of authority is offering a clear and honest story about what this means for ordinary workers and households. How they benefit. How abundance actually reaches them. How their lives get better rather than more precarious. There is no believable transition story on the table. No positive vision being articulated by anyone. None.

That absence is the backdrop to everything I am about to describe. The race between labs, the geopolitical competition, the capital flooding in. All of it is happening at pace, and almost none of it is being translated into language that helps real people understand where they stand. So every piece of news below, I want to filter through a single question: what does this mean for how you lead your people through what is coming?

Leaders who engage now will outpace those who wait

I keep coming back to a simple observation: too many leaders are still treating AI as something to monitor rather than something to use. They read about it, they attend the conference sessions, they nod along in board meetings. But they are not using the tools themselves, and it shows.