A new study reported an increase in mental fatigue tied to heavy AI use. Marketing workers were hit hardest at 26%.
A Harvard Business Review article by researchers from Boston Consulting Group and the University of California, Riverside reports that 14% of 1,488 full-time U.S.-based workers surveyed experienced what the authors call “brain fry.”
They define it as mental fatigue from excessive use of, interaction with, or oversight of AI tools beyond a person’s cognitive capacity.
What The Study Found
The study identified AI oversight as the most mentally taxing form of AI engagement. Workers who reported that their AI tools required a high degree of direct monitoring expended more mental effort and reported more mental fatigue than those with lower oversight demands. High oversight was also associated with a 19% greater information overload.
A second key predictor was whether AI had increased a worker’s overall workload. Oversight and workload expansion together widen what the authors call a worker’s “sphere of accountability,” requiring attention to more outcomes across more tools in the same amount of time.
There also appears to be a ceiling on how many AI tools one person can use effectively. Perceived productivity increased as workers went from one AI tool to two, and again from two to three, though at a lower rate. After three tools, productivity scores dipped.
The study notes that many of the workers using AI most intensively are “today’s superstars, talent whom the company must retain.” The people hitting the cognitive ceiling aren’t casual users. They’re early adopters and high performers.
Marketing Leads The Pack
Marketing workers reported the highest brain fry rate at 25%. HR/people operations followed at 19%, operations at 17%, and engineering/software development at 17%. Finance/accounting (16%) and IT (16%) were close behind. Legal/compliance was lowest at 5%.
Workers described a “buzzing” feeling, mental fog, and slower decision-making. Many said they had to physically step away from their computers to reset.
One 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.”
The Business Cost
Workers who reported brain fry scored 33% higher on decision fatigue than those who didn’t. They also reported making mistakes more often, scoring 11% higher on minor errors and 39% higher on major errors.
Brain fry also correlated with intent to leave. Among workers without brain fry, 25% showed active intent to quit. Among those with brain fry, that number rose to 34%, a 39% increase.
AI Can Also Reduce Burnout
The study draws a line between burnout and brain fry. Burnout measures focus on emotional exhaustion. Brain fry is acute cognitive strain from pushing attention and working memory beyond their limits.
When workers used AI to replace routine or repetitive tasks, their burnout scores were 15% lower. But that same use didn’t reduce mental fatigue.
The researchers argue this makes sense. Offloading dull work frees time for more engaging tasks, which helps emotionally. Intensive AI oversight taxes a different system entirely.
Manager and organizational practices also mattered. Workers whose managers took time to answer their AI questions had 15% lower mental fatigue scores. Workers who felt their organization expected them to accomplish more because of AI had 12% higher scores. And employees who felt their organization valued work-life balance had 28% lower mental fatigue scores.
Why This Matters
The findings contribute to the debate on AI’s real impact on the workforce.
A Yale study published last year found no evidence that AI had displaced workers in exposed occupations after 33 months. And a PwC survey of 4,000+ CEOs earlier this year found that 56% hadn’t seen revenue or cost benefits from AI.
This research adds a different angle. AI may not be eliminating marketing jobs, but the data suggests it may be burning out the people who hold them, especially those managing multiple tools at once.
For marketing teams and agencies juggling AI across content, analytics, and ad platforms, the three-tool productivity ceiling and the 25% brain fry rate are both worth factoring into how work gets organized.
Methodology Notes
The survey covered 1,488 full-time U.S.-based workers (48% male, 51% female; 58% individual contributors, 41% leaders) at large companies across industries, roles, and levels. The survey was conducted in January 2026. Full details are in the Harvard Business Review article.
Looking Ahead
In an interview with CBS News, Julie Bedard, a managing director and partner at BCG and an author of the study, called the findings an early warning, not a reason to stop using AI.
She said:
“The AI can run out far ahead of us, but we’re still here with the same brain we had yesterday.”
As companies push AI adoption and expect more from the same teams, this research warns that the cognitive costs of expansion should be considered alongside productivity gains.
The authors recommend limiting the number of AI agents a worker oversees and resisting adding more work since AI speeds some tasks.
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