A study 1,488 workers who use AI tools showed some interesting results

Partícipants saw increased mental fatigue especially after using 3+ AI tools and having to oversee multiple AI agents. However they saw reduced burnout thanks to automating repetitive tasks.

I’ve argued being a manager is the best preparation for being a worker in a world of supervising AI agents instead of doing the work by hand. Now backed up with research.

https://hbr.org/2026/03/when-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.

Harvard Business Review

@carnage4life

A study 1,488 workers

That's, uhhh, a peculiar number. Nobody looked at this and thought, "Fuck, we should find like at least 2 more people to include in this data set."

@Legit_Spaghetti @carnage4life
👆🏼👆🏼👆🏼 There is exactly zero chance that they studied exactly 1488 people as a random sample. Someone involved in this chose 1488.

@saraislet As much as I appreciate your concern about Nazi dog whistles, that's simply not true. Research on humans regularly has weirdly random-seeming numbers of research subjects simply because they started with a nice round number (say 1500), and a random number of subjects dropped out of the study or were disqualified (say 12). It could absolutely could have been entirely innocent accident.

It also could be Nazis! I'm just saying that's not an assumption we can confidently leap to, just a suspicion to investigate.
@Legit_Spaghetti @carnage4life

@siderea @Legit_Spaghetti @carnage4life
1. What's the probability of ending up at 1488 by random chance (as opposed to 1489 or 1487, etc)?

2. What's the probability that no one stopped and went "hold on, we need to change something here"?

This isn't the first study I've seen with that number. You cannot tell me that number happens more often than 1487 in research studies by random chance. Again, that probability is zero.