When it Comes to AI: Awe Sells, Risk Scales

The biggest fans of AI aren’t the experts, they’re the ones who don’t understand it. But should business strategy really be built on mystery and awe?

New research shows a paradox: the less people know about AI, the more likely they are to use it. Across multiple studies, including one where students had to write history papers and love poems, those with low AI literacy embraced AI tools far faster than those who understood the mechanics. Replication across 27 countries held.

Why? Because to them, AI feels magical. It writes, codes, and “thinks” in ways that seem beyond explanation. That wonder breeds adoption.

But here’s the catch: awe without understanding is a liability. The study warns against leaving users in the dark. The right goal is “calibrated literacy,” just enough knowledge to use AI safely, without stripping away the curiosity that drives exploration.

For leaders, this is a balancing act. In my new book Now What? How to Ride the Tsunami of Change, I argue that thriving in exponential times requires curiosity and discipline in equal measure. Awe sparks experimentation, but evidence must shape deployment. That means:

• Teach teams what AI can’t do, not just what it can.
• Run small, safe pilots before scaling use.
• Keep delight alive, but check outputs relentlessly.

Treat delight as a door, not a blindfold. We don’t need louder promises; we need proof under pressure.

If ignorance drives adoption and knowledge drives caution, how will you find the balance inside your organization? The future of AI use may hinge not on its power, but on how we teach people to see it. How do you keep curiosity alive in your teams without letting it cloud judgment?

Read the full article on Wall Street Journal.

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