From GPS to autocomplete to AI, we’re outsourcing more and more of our thinking to technology. Researchers are now seeing the cost: The less we practice problem-solving ourselves, the weaker that skill gets. We asked Deanna Dannels, dean of NC State’s College of Humanities and Social Sciences, what that means for leaders in hiring, on their teams and day to day.

“Critical thinking is a muscle you have to work. If I don’t get out there and train for a marathon, it’s a disaster.”

Use It or Lose It

Dannels has hired about 80% of her leadership team over the past five years and points to something she knows firsthand as a runner and biker. 

“Critical thinking is a muscle you have to work,” she said. “If I don’t get out there and train for a marathon, it’s a disaster.”

If you skip the training on AI literacy, she warned, you’ll be less ready for the moments you need to think something through yourself — such as when an AI tool is wrong, is unavailable or simply not built for the problem in front of you.

What Dannels Looks For

In interviews, which she always does in person, Dannels presents candidates with a real case and observes how they reason through it, not whether they land on the right answer. She also pays close attention to the questions people ask her, since that often reveals more than a polished response.

On existing teams, she watches for the same signals in reverse. “Early warning signs may be if team members stop asking, ‘help me understand,’ or stop asking why. If discussions become more shallow and if fewer people are challenging assumptions.”

Her fix isn’t restricting AI. It’s treating it like any other tool, with honest team conversation about where it helps and where it should do the thinking for you. 

Building the Critical Thinking Muscle Back Up

If your team’s critical thinking muscle seems to be weakening, “Help them work the muscle. Build the culture into your everyday meetings. Have a section on critical questions,” Dannels recommended.

Here are a few ways to put that into practice:

• Put real scenarios in front of candidates. Ask them to reason out loud, not submit a polished answer.
• Listen to the questions, not just the answers. Curiosity is often the clearest signal of real thinking.
• Name where AI helps and where it shouldn’t. Make it an explicit team conversation, not an assumption.
• Add “critical questions” to your meeting agenda. Give the muscle a regular place to work.

The Bottom Line

AI can generate options and speed up routine work, but it can’t decide which problem is worth solving or read a room. That is still a uniquely human skill, and like any muscle, it only stays strong if we keep using it.