Human attention is a finite resource.
A lot of AI work _increases_ the amount of attention needed, just as it increases constant context switching (which, together with the myth of multitasking, we already know to be burn out catalysts).
Together with ill- (or un-)defined “productivity gains” and peer pressure induced FOMO, it’s no surprise that “Using AI leads to ‘Brain Fry’”.

When Using AI Leads to “Brain Fry”
As firms increasingly incentivize employees to build and oversee complex teams of agents—for example, by measuring and rewarding token consumption as a proxy for performance—people are finding themselves pushed to their cognitive limits. Participants in a recent study described a “buzzing” feeling or a mental fog with difficulty focusing, slower decision-making, and headaches. The authors call this phenomenon “AI brain fry,” defined as mental fatigue from excessive use or oversight of AI tools beyond one’s cognitive capacity. This AI-associated mental strain carries significant costs in the form of increased employee errors, decision fatigue, and intention to quit. The findings also show how AI-driven workflows can be designed to diminish burnout and point toward specific manager, team, and organizational practices to avoid mental fatigue even as AI work intensifies.