Workers who excessively use AI agents and tools at work are at increased risk of mental fatigue, CNET reported, citing a Harvard Business Review study. The study, “When Using AI Leads to ‘Brain Fry’,” was published on 5 March 2026 by Boston Consulting Group researchers and surveyed 1,488 US workers. According to the report, “in certain industries, more than 25% of hired professionals report increased mental strain due to their role in AI oversight.” The same professionals generally experienced less burnout than peers who do not use AI.

The researchers describe AI brain fry as a “‘buzzing’ feeling or a mental fog.” Participants linked it to headaches and to trouble focusing and making decisions. They said the causes were large amounts of information and frequent task switching. The researchers say acute mental fatigue “is caused by marshalling attention, working memory and executive control beyond the limited capacity of these systems.” They also report a business cost: “Workers in [the] study who endorsed AI brain fry experience 33% more decision fatigue than those who did not.”

A second HBR study found that employees using AI tools “worked at a faster pace, took on a broader scope of tasks and extended work into more hours of the day.” It warned that “workload creep can in turn lead to cognitive fatigue, burnout and weakened decision-making.”

What happens in the brain?

A new paper in PNAS (Proceedings of the National Academy of Sciences), “A causal account of the neural origins of mental fatigue,” examines the biology behind this kind of exhaustion. The authors are Hongmei Xia, Gizem Vural, Antonia Susnjar, Helge J. Zöllner, Rebekka S. Mattes and Alexander Soutschek, led from Ludwig-Maximilians-Universität München. The paper was accepted on 1 October 2026. The study did not examine AI use; it studied mental effort in general.

The researchers “tested the hypothesis that sustained activation in the dorsolateral prefrontal cortex (DLPFC)—a neural substrate of cognitive control—causally induces motivational fatigue via the accumulation of prefrontal glutamate metabolites.” To do this, they combined brain stimulation (tDCS) with magnetic resonance spectroscopy while participants performed a demanding working-memory task.

Their findings, in the authors’ words:

• “We found that stimulating the DLPFC during mental effort exertion improved mental performance at the cost of increased posteffort motivational fatigue.”
• “On the neural level, DLPFC activation during effortful cognition also increased prefrontal concentrations of glutamate, which statistically explained the fatigue-induced lower motivation for mental effort.”

The authors also address the popular “the brain runs out of fuel” idea. “Earlier biological theories, most notably the glucose depletion hypothesis, proposed that effort costs reflect the exhaustion of metabolic resources, but the glucose hypothesis was rejected based on empirical data,” they write. Their conclusion is that “mental fatigue—and the costly nature of cognition—might rely at least partially on neural rather than only psychological constraints.”

Leadership lens (MAX ENERGY commentary):

Read together, the two studies suggest an uncomfortable trade-off. The brain’s control center can be pushed to perform better, but the bill arrives afterward as less willingness to keep making effort. This is our interpretation; neither study tested it directly. AI can amplify this pattern because it multiplies the outputs a person must check, compare and decide on. In MAX ENERGY terms, a leader who answers that load by pushing harder is running on Survivor Energy: performance rises today and decision quality falls tomorrow. The Life Energy response is to design work around the brain’s limits. That means fewer parallel tools, fewer task switches, real recovery windows, and protecting the hours when the most important decisions are made.

Sources: CNET, “Harvard Business Review Study Finds ‘AI Brain Fry’ Is Leaving Workers Mentally Fatigued”; Bedard et al., “When Using AI Leads to ‘Brain Fry’,” Harvard Business Review, March 2026 (https://hbr.org/2026/03/when-using-ai-leads-to-brain-fry); Harvard Business Review, “AI Doesn’t Reduce Work—It Intensifies It,” February 2026 (https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it); Xia, Vural et al., “A causal account of the neural origins of mental fatigue,” PNAS, 2026.