A new study warns that overusing artificial intelligence (AI) tools at work can lead to a condition researchers are calling "AI brain fry" — a form of mental fatigue caused by managing too many AI systems at once, beyond what the human brain can comfortably handle.

Published in the Harvard Business Review, the study was conducted by researchers from Boston Consulting Group and the University of California, Riverside. They surveyed 1,488 full-time U.S.-based workers about their AI use and its effects on their mental health and job performance.

Julie Bedard, Gabriella Rosen Kellerman, and their co-authors define AI brain fry as "mental fatigue from excessive use or oversight of AI tools beyond one's cognitive capacity." Workers who experienced it described a "buzzing" feeling, mental fog, difficulty focusing, slower decision-making, and headaches. Many said they had to physically step away from their computers to "reset."

Francesco Bonacci, an engineer and founder of Cua AI, captured the feeling in a widely shared post, writing: "I end each day exhausted — not from the work itself, but from the managing of the work. Six worktrees open, four half-written features, two 'quick fixes' that spawned rabbit holes, and a growing sense that I'm losing the plot entirely."

Who's Most at Risk

Fourteen percent of workers in the study reported experiencing AI brain fry. Marketing professionals had the highest rate at 26%, followed by human resources at 19.3%, operations at 17.9%, and engineering at 17.8%. Legal professionals had the lowest rate, at just 5.6%.

Workers who reported high levels of AI oversight expended 14% more mental effort and experienced 12% more mental fatigue than those with lower oversight demands. The study also found that using more than three AI tools at the same time actually caused productivity to drop — even though adding a second or third tool initially boosted output.

Real Costs for Businesses

The mental strain doesn't just affect workers — it hits employers' bottom lines, too. According to Axios, the researchers describe the costs as "significant." Workers experiencing AI brain fry reported 33% more decision fatigue than those who did not. They also made 11% more minor errors and 39% more major errors on average.

Perhaps most alarming for employers: workers with AI brain fry were 39% more likely to say they intended to quit their jobs.

A finance director quoted in the study described the experience this way: "I had been back and forth with AI, reframing ideas, synthesizing data, forming and organizing the flow of pillars and work…I couldn't even comprehend if what I had created even made sense…just couldn't do anything else and had to revisit the next day when I could think."

AI Brain Fry vs. Burnout

The researchers are careful to distinguish AI brain fry from traditional workplace burnout. As India Today reports, burnout is typically driven by emotional exhaustion and negative feelings about work, while AI brain fry stems from the cognitive load of monitoring and managing multiple AI systems simultaneously. That distinction matters because AI brain fry may go undetected in standard workplace burnout surveys.

Interestingly, the study found that AI can also reduce burnout — but only when used the right way. When workers used AI to eliminate repetitive or unenjoyable tasks, their burnout scores were 15% lower than those who didn't use AI that way. Those workers also reported better engagement, more motivation, and stronger social connections with colleagues.

The Role of Managers

How managers handle AI in the workplace makes a measurable difference. Workers whose managers took time to answer their AI-related questions reported 15% lower mental fatigue scores. By contrast, when managers left employees to figure out AI tools on their own, mental fatigue scores were 5% higher.

When teams felt pressure to use AI and lacked organized guidance, mental fatigue climbed. But when teams embedded AI into their workflows together — as a shared resource rather than an individual performance metric — cognitive strain dropped.

The researchers also noted that companies sending mixed messages about AI's impact on workloads were contributing to the problem. Employees who believed their organization valued work-life balance reported 28% lower mental fatigue scores than those who didn't.

The authors urge organizations to set clear limits on how many AI agents one worker can reasonably oversee, invest in upskilling employees to handle complex AI workflows, and resist the urge to pile on more work just because AI makes some tasks faster. "Just because a worker can keep iterating with AI," they write, "does not mean they should."

EJ