{"id":84901,"date":"2026-04-30T09:52:10","date_gmt":"2026-04-30T13:52:10","guid":{"rendered":"https:\/\/isarta.com\/news\/?p=84901"},"modified":"2026-05-04T10:07:31","modified_gmt":"2026-05-04T14:07:31","slug":"brain-fry-the-hidden-downside-of-the-ai-revolution-at-work","status":"publish","type":"post","link":"https:\/\/isarta.com\/news\/brain-fry-the-hidden-downside-of-the-ai-revolution-at-work\/","title":{"rendered":"“Brain Fry”: The Hidden Downside of the AI Revolution at Work"},"content":{"rendered":"\n

AI has barely begun to make its way into the workplace, and it’s already raising concerns among employees who point to the cognitive fatigue it causes. A symptom dubbed “brain fry” by a new article in Harvard Business Review. Here’s what’s going on.<\/strong><\/p>\n\n\n\n

AI was supposed to simplify work \u2014 instead, it’s only intensifying it. That’s the conclusion reached by Julie Bedard, a partner at Boston Consulting Group, and members of her team in an article published by HBR<\/a>. It follows another piece<\/a> released in the same review just days apart, authored by researchers at UC Berkeley, who arrive at the same conclusions.<\/p>\n\n\n\n

What is “brain fry”?<\/h2>\n\n\n\n

Julie Bedard has named this new phenomenon “brain fry” \u2014 which can be understood as “mental fatigue resulting from excessive use of AI tools.” To illustrate it, she shares this testimony from an experienced engineer:<\/p>\n\n\n\n

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I had one tool to help me arbitrate technical decisions, another that produced drafts and summaries, and I kept switching back and forth between them, double-checking everything. But instead of going faster, my brain started to feel cluttered. Not physically tired, just\u2026 overloaded. It was like having a dozen tabs open in my head, all competing for my attention. My thinking wasn’t broken, just noisy \u2014 like mental static. What finally pulled me out of it was realizing that I was working harder to manage the tools than to solve the problem itself.”<\/p>\n<\/blockquote>\n\n\n\n

According to the study, 14% of the 1,488 American employees surveyed reported experiencing this kind of cognitive fatigue. With a notable difference across roles: 6% of people working in legal functions reported it, compared to\u2026 26% in marketing functions!<\/p>\n\n\n\n

And the consequences are concrete: more errors, decision fatigue, and\u2026 a stronger intention to quit one’s job, among those who reported the phenomenon.<\/p>\n\n\n\n

AI doesn’t lighten work \u2014 it accelerates it<\/h2>\n\n\n\n

Where is the problem coming from? From the rise in tasks involving the supervision of swarms of AI agents at speeds the human brain can’t keep up with.<\/p>\n\n\n\n

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“People who use these AI tools certainly accomplish much more work, but they also feel like they’re hitting the limits of their brainpower, as if there were too many decisions to make,” Julie Bedard explains.<\/p>\n<\/blockquote>\n\n\n\n

The stakes are even higher because some companies are pushing their teams in this direction. Take Meta, cited in the article, which treats AI tool consumption as a performance metric and, for instance, measures the number of lines of code generated by AI among its criteria for evaluating engineers.<\/p>\n\n\n\n

On LinkedIn<\/a>, Francesco Bonacci, founder of an AI startup, talks about the productivity trap in a post whose hook reads: “The ‘Vibe Coding’ paralysis: when infinite productivity breaks your brain.”<\/em><\/p>\n\n\n\n

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I end every day exhausted \u2014 not by the work itself, but by managing it. With the growing feeling that I’m completely losing the thread,” he writes.<\/p>\n<\/blockquote>\n\n\n\n

The surprising rule of 3 tools<\/h2>\n\n\n\n

The most mentally draining form of engagement? Supervision, according to the study. Employees who report doing a lot of AI supervision expend 14% more mental effort in their work and experience 19% more information overload.<\/p>\n\n\n\n

But the most intriguing finding concerns the relationship between the number of AI tools used simultaneously and perceived productivity gains. Going from one to two tools, employees report a significant rise in productivity. Adding a third tool produces another increase, though smaller. Beyond three tools, productivity scores drop!<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
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How Many AI Tools Is Too Many? This line chart shows the self-reported productivity of workers who were asked whether their overall productivity at work increased because of AI tools, depending on how many of those tools were being used at the same time. On a scale of 1 (strongly disagree) to 5 (strongly agree), productivity increases from 3.3 with one tool, to 3.8 with two tools. It peaks at 4.1 with three tools, then falls to 3.7 with four or more tools. Source: Boston Consulting Group survey of 1,488 full-time U.S. workers, January 2026.<\/em><\/p>\n<\/blockquote>\n\n\n\n

The difference between “Brain Fry” and “Burnout”<\/h2>\n\n\n\n

The authors do, however, add a nuance: AI use doesn’t appear to predict an increase in burnout. On the contrary, the replacement of repetitive tasks seems to reduce that state of chronic professional stress that builds up over time. In other words, “brain fry” seems to be just an acute, unpleasant, but temporary experience.<\/p>\n\n\n\n

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“When they take a break, it goes away,” reveals Gabriella Rosen Kellerman, one of the study’s authors.<\/p>\n<\/blockquote>\n\n\n\n

The solution? Not to eliminate AI from work\u2026 but to think critically about how it’s implemented. Training on the proper use of these tools, grouping AI-related activities into a specific time block during the workday, or carving out protected moments for stepping back \u2014 particularly before a demanding decision or task\u2026 These are all paths to avoid crashing and burning with AI.<\/p>\n\n\n\n

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AI has barely begun to make its way into the workplace, and it’s already raising concerns among employees who point to the cognitive fatigue it causes. A symptom dubbed “brain fry” by a new article in Harvard Business Review. Here’s what’s going on.<\/p>\n","protected":false},"author":88,"featured_media":84905,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3,7],"tags":[],"_links":{"self":[{"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/posts\/84901"}],"collection":[{"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/users\/88"}],"replies":[{"embeddable":true,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/comments?post=84901"}],"version-history":[{"count":1,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/posts\/84901\/revisions"}],"predecessor-version":[{"id":84907,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/posts\/84901\/revisions\/84907"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/media\/84905"}],"wp:attachment":[{"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/media?parent=84901"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/categories?post=84901"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/isarta.com\/news\/wp-json\/wp\/v2\/tags?post=84901"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}