What happens when AI gets the answer right so often that we slowly lose the ability to recognize when it’s wrong?

This isn’t a hypothetical question. Another industry has already lived through it.

Aviation.

In 2013, an expert panel commissioned by the FAA raised concerns about something troubling. Highly trained, experienced commercial airline pilots were becoming overly dependent on automation, and some of their fundamental manual flying skills were deteriorating.

The technology wasn’t necessarily failing. In fact, its reliability was part of the problem.

Pilots were spending less time actually flying the aircraft manually. And when automation encountered a situation it couldn’t handle, control returned to a human who might not have exercised those critical skills in quite some time.

Think about that.

The technology worked so well that the people responsible for stepping in when it didn’t were becoming less prepared to do so.

Now consider what we’re doing in collision repair, insurance claims, estimating, and business operations.

We’re introducing AI systems that summarize information, interpret documents, recommend decisions, write estimates, and increasingly perform work that once required a human to evaluate evidence and exercise professional judgment.

We celebrate the time saved. We measure productivity gains. We talk about efficiency.

But who’s measuring what happens to the skills we no longer practice?

In my book, The Judgment Gap: What Collision and Claims Are Quietly Losing as AI Takes Over the Answers, I examine what I believe is one of the most overlooked risks of our industry’s rapid adoption of artificial intelligence.

It’s not simply whether AI can produce an accurate answer.

It’s what happens to the human who becomes increasingly dependent on receiving that answer.

Research into cognitive offloading, automation bias, and human attention reveals some uncomfortable realities.

Experienced professionals aren’t immune. Years of knowledge don’t necessarily protect a skill that is no longer being exercised.

And humans are particularly poor at performing one task that many companies are now assigning them: passively monitoring a highly reliable automated system for the occasional mistake.

The more reliable the technology becomes, the easier it is to stop questioning it.

That’s a serious consideration when the decisions involve vehicle safety, insurance coverage, repair methodology, financial outcomes, and potential liability.

Let me be clear. This isn’t an argument against AI. I use AI, and I see its enormous potential.

But there’s a difference between using technology to strengthen human judgment and designing an operation where technology gradually replaces the need to exercise it.

And that difference is a leadership decision.

In Episode 6 of The Judgment Gap Podcast — “The AI Crutch and the Human: When the Tool Starts Training the Worker” — I explore what aviation learned about automation dependency, what decades of human-factors research tell us, and why collision repair and insurance claims leaders should be paying attention.

Because the real test of your AI strategy may not be how efficiently your team performs when the technology works.

It may be what your people are still capable of doing when it doesn’t.