C-suite: Your AI strategy is going to cost you your job

One of the hardest things to understand about AI is not how to use it effectively to be more productive and, in the process, build pretty ROI graphs that will make most everyone happy.

To build these graphs, most companies now have AI strategies. With all the hype, you would have to be crazy not to, or at least not to have a pretty deck somewhere with big words on the headline pages stating “roadmap”, “executive mandate”, and of course, the world-shattering press release announcing a transformation that no one will read, not even your employees.

No one will read it because they are getting it fundamentally wrong. While every company has an AI strategy. Almost none have an AI operating model.

There’s a difference. And it’s costing them.

The operating model is what actually changes. Who decides what. Which inputs get trusted. Where a human still needs to be in the loop. What happens when the AI recommendation contradicts the established process.

MIT’s NANDA initiative put a number on it last year: 95% of enterprise AI pilots fail to reach production with measurable impact on the P&L. It is not because the models are bad, and to be honest, this is an easy fix; it is because the organization around the model was never redesigned.

You can’t bolt intelligence onto a structure built for a different century and call it transformation. I mean, you can, but it is a transformation in the wrong direction and will, in time, cost the CEO and the C-suite their jobs.

What I keep seeing, across sectors and geographies, is the same pattern: leadership buys the strategy. Middle management absorbs the tools. And the operating model — the real architecture of how decisions get made — stays exactly as it was. It is a design problem.

What it’s not: An AI operating model isn’t a governance document. It’s not a Center of Excellence with a quarterly meeting.

What it is: It’s a clear answer to four questions: What decisions are AI-assisted? What decisions are AI-led? Where does accountability sit when the system is wrong? And what does the organizational chart look like when those answers are honest?

Most companies haven’t answered any of them.

The ones that have? They’re not running AI pilots anymore. They’re running at a different speed entirely while daily demonstrating that the gap isn’t between companies with AI and those without. It’s between the ones who redesigned to think with it and the ones who still use it as a faster version of what they already had.