Post ContentThe findings of the study come at a time when AI adoption by enterprises is being pushed aggressively. (Image: Unsplash)
Artificial intelligence (AI) is often promoted as powerful technology that can boost productivity and efficiency. However, a new study has found that workers are experiencing increased cognitive exhaustion from the excessive use and oversight of AI tools, as part of an emerging form of mental fatigue called ‘AI brain fry’.
The study was conducted by researchers from Boston Consulting Group and University of California, Riverside. It surveyed over 1,488 full-time US-based workers at various roles in large companies across industries. Over 14 per cent of participants ‘endorsed’ experiencing AI brain fry, with some of them describing a “buzzing” feeling or a mental fog with difficulty focusing, slower decision-making, and headaches.
Among those who use AI on the job, participants experiencing AI brain fry are 11 per cent more likely to make minor errors and 39 per cent more likely to make major mistakes than those who have not undergone the mental fatigue state. Additionally, 34 per cent of workers who had experienced AI brain fry showed active intent to quit their jobs as opposed to 25 per cent of workers who did not report AI brain fry.
The study further found that the extent of AI brain fry varies widely with people’s roles. For instance, six per cent of legal professionals reported experiencing it compared to 26 per cent of professionals in marketing. Functions in people operations, operations, engineering, finance, and IT also saw high prevalence of AI brain fry, as per the study.
The findings of the study come at a time when AI adoption by enterprises is being pushed aggressively, often through a top down approach.
Nvidia CEO Jensen Huang has told employees in the past to “use AI for every task.” Many companies are also incentivising employees to use AI on the job by measuring and rewarding token consumption as a proxy for performance. Recently, Meta reportedly introduced the number of lines of AI-generated code as a performance metric for engineers. Of course, the push for broader AI adoption by large companies has been accompanied by employee fears of job loss.
“Our findings are both a guide and a warning. Used thoughtfully, this data can help design AI-driven workflows to diminish burnout. They also point toward specific manager, team, and organizational practices to avoid mental fatigue even as AI work intensifies,” the researchers wrote in an article published in Harvard Business Review on March 5.
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Key findings of the study
Oversight of AI tools: Since the use of AI tools for work requires a high degree of oversight, the study said that workers had to expend 14 per cent more mental effort on the job. It also led to 12 per cent more mental fatigue and 19 per cent greater information overload among respondents, as per the study.
Number of AI tools: The study found that using more AI tools slowed productivity increases. Workers who use more than three AI tools reported declining productivity levels, it said.
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Mental fatigue versus burnout: Interestingly, the study points out that while using AI at work led to increased mental fatigue, the use of AI to replace repetitive tasks predicted a decrease in burnout. It defined burnout as “physical and emotional dimensions of distress”, different from AI brain fry, which is a more acute, cognitive strain caused by intensive AI use.
Business costs of AI brain fry
In an attempt to quantify the consequences of AI brain fry, the study said that the cognitive strain created by intensive AI use carries several critically significant business costs such as the inability to make high-quality decisions.
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The study’s participants who reported AI brain fry said they also experienced 33 per cent more decision fatigue than those who did not experience AI brain fry.
Citing a 2018 study, it said that the estimated cost of suboptimal decision making for a $5 billion revenue company is $150 million per year. Therefore, a 33 per cent increase in decision fatigue could increase that cost by millions of dollars per year, the researchers said.
