Companies that rushed to deploy AI without a plan to protect employee skills are now facing a measurable decline in critical thinking and judgment, researchers warn. The cognitive erosion is real, and most HR functions are unprepared for the talent consequences that follow.
Mohammad Hossein Jarrahi, a professor at the University of North Carolina at Chapel Hill, calls this buildup cognitive debt - the capability that disappears every time an employee lets AI handle a decision that once required human judgment. "You are gaining something in the short term that might result in losses in the long term," he said.
Most organizations treat AI the same way they've treated every efficiency drive before it, Jarrahi said. The focus is on what can be automated, not on what capability vanishes when it is.
The two types of friction AI removes
Jarrahi draws a distinction that most AI deployment strategies overlook. There are two kinds of workplace friction, he argues, and only one of them should go. The first is toil: paperwork, redundant processes, tasks with no learning value. The second is the friction of difficult decisions, competing options, and moments that require genuine judgment.
"These are decision-making moments. These are difficult work moments. You need to examine different options. You need to go closely and decide what the outcomes and consequences are," Jarrahi said. When AI absorbs that second category of friction, employees stop doing the reps. Cognitive muscles weaken without use, just like physical ones.
Adam Green, a professor of neuroscience and director of the Laboratory for Relational Cognition at Georgetown University, has studied what happens in the brain when skills go unpracticed. Disuse causes real, measurable deterioration. "If you stop thinking in certain ways, your brain will continue to change, and those changes will make it less capable of those sorts of things that you're not practicing," Green said. He points to GPS as a proven precedent: two decades of navigation offloading has measurably altered spatial cognition. AI is now doing the same across a much wider range of cognitive skills.
The 2026 International AI Safety Report, compiled by researchers across 30 countries, found emerging evidence that routine delegation of cognitive tasks to AI may negatively affect critical thinking and memory. One study cited in the report showed that clinicians' ability to detect tumors without AI assistance dropped by 6% within three months of AI support being introduced.
Why routine work is the problem
Jarrahi points to a structural flaw in how most organizations deploy AI. The standard model gives AI the routine cases and leaves humans to handle the exceptions. In practice, that means the most cognitively demanding work gets handed to employees whose judgment has had fewer opportunities to develop, because AI has been handling the decisions that used to build it.
"You are giving the most difficult cases to someone who hasn't even solved the simpler cases," Jarrahi said. "You are giving a very heavy load to someone who hasn't really developed the mastery." Workers who once built judgment through thousands of routine decisions are now skipping that foundation entirely. When a situation arises that AI can't handle, there's no depth to draw on. And once those skills are gone, Jarrahi believes they may not come back.
Progressive HR teams are already building frameworks to prevent this, a shift covered in detail by AI for Human Resources training on the topic.
The creativity convergence
Green's research adds another dimension to the concern. His lab has been tracking what happens to original thought when workers lean on AI for idea generation. "AI is breaking the link between words and ideas," he said. "It's making words more diverse. And at the same time, the ideas that those words are conveying are becoming more similar to each other."
In other words, the outputs look more diverse but the thinking behind them is converging. That's a direct problem for any organization that depends on genuine innovation. Green also referenced research by Sandra Matz of Columbia Business School showing that AI is homogenizing the options people consider, meaning fewer alternatives get evaluated and fewer solutions get explored.
If critical thinking atrophies widely across a workforce, Green argues, AI stops being a tool and becomes a dependency. "If you lose that ability, and especially for younger people who have never had the opportunity to develop those thinking skills before AI, it can really become a true dependency where you're not capable of functioning without it," he said.
How to preserve cognitive skills
Neither researcher views AI as the problem. The way most organizations are adopting it is the problem - chasing output with no thought for what's being lost. Green's recommendation is to start with your own ideas and let AI help develop and sharpen them, rather than letting AI generate the ideas first. Use AI for the work that doesn't require original thinking, he says, so there's more bandwidth left for the work that does.
"What we need to do is measure and quantify and reward thinking for yourself with AI. Because that will be the value add of humans," Green said. "Everybody's got access to the same AI systems. What will make a person valuable is not their ability to use those systems, but their ability to add value when they use those systems."
Jarrahi pushes the solution into workflow design itself. He recommends building parallel processes that require employees to make independent decisions and challenge AI-driven outputs, rather than simply reviewing and approving them. He also introduces a framework HR should actively protect: cooperative skills (the critical literacy to evaluate and challenge AI) and competitive skills (judgment, contextual reasoning, relational intelligence), the uniquely human capabilities that employees need to preserve.
"You design a parallel process where you demand your employees to make decisions and challenge the decision-making of the AI system," he said. "Sometimes you need to go against the precedent if you are in unprecedented times."
Some skill loss is inevitable. Jarrahi uses GPS as an example of a skill people have largely handed over to technology without much consequence. But the skills that underpin judgment, consequence-sensing, and contextual reasoning are in a different category. Those are what organizations will need most precisely when AI falls short.
Why this matters for HR
The fundamental building block of organizational performance is changing. "The unit of competition is not humans anymore. It's human-AI hybrids," Jarrahi said. For HR leaders, the shift from efficiency-focused AI adoption toward long-term workforce resilience is a strategic imperative. A AI Learning Path for CHROs offers guidance on aligning AI deployment with deliberate skill preservation, so the workforce doesn't lose the judgment it will need most when AI can't handle the exception.
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