Here is a question worth examining carefully: If the technology we adopt to simplify work ends up making it harder, are we deploying the technology or is the technology deploying us?
A new study published in the Harvard Business Review suggests many organisations have got this equation backwards.Researchers from Boston Consulting Group and the University of California, Riverside surveyed nearly 1,500 full-time US workers and found that a significant proportion of employees who constantly use AI at work to push their productivity past their normal capacity are becoming fatigued.Participants described a "buzzing" feeling or mental fog with difficulty focusing, slower decision-making, and headaches.
In the survey of 1,488 full-time U.S.-based workers, 14 percent said they had experienced "mental fatigue that results from excessive use of, interaction with, and/or oversight of AI tools beyond one's cognitive capacity". The percentage matters less than the pattern.The condition was highest in marketing, software development, HR, finance, and IT roles - precisely where organisations have invested most aggressively in AI automation.
Strip away the talking points and what remains is clear: the fundamental problem is not that AI exists. It is how organisations are wielding it. Consider the mechanics.The most draining aspect of using AI to automate work is oversight, or the need to constantly supervise the AI tools, with some overseeing multiple AI agents at the same time. This creates a peculiar inversion. Workers no longer do the repetitive task; they monitor the machine doing it, which demands constant attention, decision-making, and error correction.
Workers who experienced brain fry experienced a 33 percent increase in decision fatigue, which for multibillion dollar firms could translate to millions of dollars lost to poor decision-making each year.Participants experiencing AI brain fry reported more minor mistakes that are easy to correct and more major mistakes with consequences for safety, outcomes, or significant decisions. The promised efficiency gains dissolve under the weight of cognitive overload.
The counter-argument deserves serious consideration: this is merely the friction of transition. Early adopters always struggle. Give organisations time to mature their AI practices and workers will adapt. The evidence, however, suggests something more structural.The technology is enabling workers to multitask at a speed and workload well past their regular limit, which seems to be part of the problem regarding its cognitive effects. It is not that the technology fails; it is that it succeeds too well at amplifying expectations.
There is a genuine paradox embedded in the findings.Workers who used AI to reduce time spent on routine and repetitive work reported lower burnout levels. Yetwhen workers had to constantly supervise multiple AI systems or juggle several tools at once, mental strain increased sharply, while by contrast, when workers used AI to actually offload repetitive tasks, their stress levels dropped.
The distinction matters. The problem is not AI. It is the absence of what researchers call intentional design.Leadership and training could play a critical role, with less brain fry seen among employees whose managers were intentional with their AI use.Guidance on how AI fits into daily work reduced cognitive pressure across teams.
If we accept that premise - and the evidence suggests we should - then what follows is uncomfortable for organisations. The solution requires more than buying better tools. It requires redesigning how work happens.Leaders must rethink workflows so they don't "just keep exactly what we did yesterday and put AI on the top of it".
The workers most at risk for brain fry are the early adopters and those most excited about the technology - the high performers organisations most depend on.Workers reporting AI brain fry were more likely to express intent to leave their jobs. This is not a marginal issue for HR departments. It is a retention crisis waiting to happen among precisely the talent pool companies cannot afford to lose.
Voters and workers deserve better than empty promises about productivity paradise. They deserve organisations that think seriously about the human cost of their technology choices before rolling out the next shiny automation tool. The research is clear: AI adoption without intentional leadership and workflow redesign creates new forms of exhaustion, not efficiency.