Talk to the people leading AI inside a company and a surprising frustration comes up again and again. It isn't the models. It isn't the budget. It's that the senior leaders and investors funding the work can't quite follow what's being built — and it's hard to get good decisions out of people who are nodding along without a clear picture.
These are smart, accomplished people. They know ChatGPT and Claude exist. But the old mental model — software gets specified, built, tested, deployed — doesn't map cleanly onto how AI works, and most haven't been given a new model to replace it.
The confidence-competence gap
The data on this is uncomfortable, and worth showing leaders directly — partly because they're often in it.
94%
of senior leaders rate their AI knowledge as intermediate or better
MIT Sloan, via Fast Company, 2025
8%
actually have a substantial, conceptual grasp of it
MIT Sloan, 2025
44%
of CIOs are seen as 'AI-savvy' by their own CEO
Gartner, 2025
That space between 94 and 8 percent is where expensive mistakes get made — projects greenlit for the wrong reasons, risks waved through because they weren't understood, good ideas killed because they couldn't be explained. Closing it isn't about making everyone technical. It's about giving them a working mental model.
Why 'powered by AI' isn't enough
When a vendor says a product is "powered by AI," a leader without a mental model has no way to evaluate it. Is that a meaningful capability or a marketing sticker? Does it create a new risk? They can't tell, so they default to either rejecting everything or approving everything — and both are bad strategies dressed up as caution or vision.
The two-story method
The fix isn't another slide deck full of definitions. Drop the jargon entirely and use two stories, both pulled from the leader's own business. One shows the risk, one shows the win. Concrete beats comprehensive every time.
Here's what it exposed
"One of our people built a genuinely useful tool over a weekend. It also quietly sent a batch of customer records to a free service that trains on whatever you give it." Now the risk isn't abstract. It has a face and a consequence.
Here's what it saved
"This reconciliation took one person a full day every month. We rebuilt it with AI and now it runs in minutes, and the numbers are more accurate." Now the value isn't a buzzword. It's hours and dollars they recognize.
Two stories, five minutes, no acronyms. A leader who hears those walks away understanding more about AI in their business than they would from an hour of architecture diagrams. They don't need to know how the model works. They need to see where it creates value and where it creates exposure.
Make it hands-on
The strongest version of this isn't a presentation at all. It's sitting down together and running one real example — their data, their workflow, live. BCG went as far as advising that senior leaders personally run an AI session for their own board rather than delegating it. There's a reason: you understand a thing differently once you've done it with your own hands.
Next time you need to bring a leader along, skip the overview. Pick one real task from their world, sit down, and do it together. Ten minutes of doing beats an hour of explaining.
AI literacy at the top isn't optional anymore, but it also isn't as hard to build as people assume. Make it concrete, make it theirs, and make it hands-on. The understanding follows the experience.
Key Takeaways
- The hardest part of AI is often explaining it to the leaders and investors funding it.
- There's a wide gap between how much leaders think they understand AI and how much they actually do.
- Skip the jargon and use two concrete stories from their own business — one risk, one win.
- Leaders don't need to know how the model works, just where it creates value and exposure.
- The strongest format is hands-on: run one real example together rather than presenting slides.