A recent study published by Harvard Business Review has identified a new kind of mental exhaustion affecting workers who constantly use and monitor AI tools. The phenomenon, dubbed "AI brain fry," is characterized by symptoms including mental fog, difficulty concentrating, slower decision-making, and headaches. The study, conducted by researchers from Boston Consulting Group and other institutions, surveyed 1,488 full-time workers in the United States. The findings suggest that certain patterns of AI use can contribute to cognitive fatigue.
According to the researchers, AI brain fry occurs when people use or oversee AI tools beyond what their cognitive capacity can comfortably handle. The problem is not necessarily asking an AI tool to draft an email, summarize a document, or generate ideas. Instead, much of the strain comes from overseeing AI output, checking whether it is accurate, correcting mistakes, monitoring multiple streams of information, and deciding what can be trusted. This can create a significant mental burden, similar to reading a report written by a colleague versus one that requires fact-checking sentence by sentence.
The numbers behind AI fatigue are alarming. About 14% of US knowledge workers already report experiencing this fog-like fatigue. In marketing departments specifically, that number jumps to 26 percent, likely due to the need to juggle multiple AI tools at once. Workers affected reported more mistakes at work, slower decision-making, and a noticeably higher urge to quit their jobs entirely. One researcher, Julie Bedard of BCG, noted that while AI can move quickly, people are still working with the same brain they had yesterday.
The study found that productivity actually peaks when someone uses just one to three AI tools regularly. Once a person is juggling four or more tools at once, the mental cost of switching between them starts to outweigh whatever time those tools were supposed to save. Every extra tool adds another interface to learn, another output to double-check, and another place attention has to jump to. This lines up with a broader pattern researchers have noticed elsewhere, where the average length of time someone can stay genuinely focused on one task has been shrinking for years.
Workers studied described experiences including a "buzzing" sensation, mental fog, difficulty concentrating, slower decision-making, and headaches. The symptoms may not look like an obvious workplace crisis. Instead, a worker may simply finish a normal day feeling mentally exhausted, struggle to concentrate on routine tasks, or find it harder to make decisions. Over time, that cognitive fatigue can affect how people perform their jobs and how they feel about their work.
To reduce AI fatigue, researchers suggest redesigning the way AI is incorporated into daily work. This can include limiting the number of AI tools employees are expected to manage and avoiding workflows that require workers to constantly monitor multiple streams of AI-generated output. Workers can also benefit from grouping AI-related tasks into specific periods instead of repeatedly switching between AI tools throughout the day. Creating periods for human-only work can also give workers time to think, make decisions, and complete tasks without constantly evaluating AI output.
Employers also have a role to play in reducing AI-related fatigue. Managers can help by clarifying which AI tools workers are expected to use, providing guidance on how to evaluate AI output, and avoiding unnecessary duplication of tools. The researchers also point to the importance of workplace culture and managerial support in reducing the effects of AI-related fatigue. As AI becomes increasingly embedded in everyday work, the challenge may no longer be simply getting employees to use the technology, but learning how to use AI without overwhelming the people expected to supervise it.
Key points
- AI brain fry is a new kind of mental exhaustion affecting workers who excessively use and monitor AI tools.
- Productivity peaks when using one to three AI tools regularly, and declines with four or more tools.
- Employers can help reduce AI-related fatigue by clarifying AI tool usage, providing guidance on evaluating AI output, and avoiding unnecessary duplication of tools.
