【AI + Efficiency】 Using AI may not necessarily improve efficiency and could become more "brain-burning" — which top ten job positions are most prone to "AI Brain Fog"?

The world has entered the AI era, with industries and job roles utilizing AI to assist work and improve efficiency. However, widespread AI use has led to the phenomenon of “AI brain fog.” A study published in Harvard Business Review found that 14% of respondents who use AI in their work have experienced “AI brain fog,” and it listed the top ten roles most prone to this condition.

“AI brain fog” is defined as mental fatigue caused by overuse or regulation of AI tools beyond one’s cognitive capacity.

BCG conducted a study on 1,488 full-time employees at large U.S. companies, examining their AI usage patterns, workload, work experience, and cognitive and emotional issues. Respondents spanned multiple industries, roles, and levels, with nearly equal gender representation. About 60% were independent contributors, and 40% were management.

Participants reported that during “AI brain fog,” they experience a buzzing sensation or mental confusion, characterized by difficulty concentrating, slower decision-making, and headaches.

The study found that when AI is used to replace routine or repetitive tasks, burnout scores decrease, but mental fatigue scores do not.

How does AI usage trigger “AI brain fog”?

1. The most mentally demanding form of AI operation is supervision. Employees using AI with high supervision requirements experience 14% more mental effort, 12% more psychological fatigue, and 19% more information overload compared to less supervised AI use.

2. Increased AI tool usage raises workload. Supervising AI and increased workload expand employees’ responsibilities, leading to higher cognitive load and subsequent psychological fatigue.

Interestingly, when employees increase from using one AI tool to two, productivity significantly improves. Using a third tool further boosts productivity but at a slower rate, and using four or more tools actually decreases productivity.

The study indicates that information overload and task switching are key factors leading to “AI brain fog.” There is a strong correlation between “AI brain fog” and information overload, but the relationship with task switching is less direct.

What are the negative impacts of “AI brain fog”?

1. Decision fatigue. When employees are overwhelmed by high-intensity AI work, their cognitive resources for making high-quality decisions diminish. Employees experiencing “AI brain fog” show a 33% higher level of decision fatigue.

2. Error frequency. Employees with “AI brain fog” have a significantly higher error rate, with minor errors up 11% and major errors up 39% compared to those without.

3. Talent attrition. Among employees who have not experienced “AI brain fog,” 25% express active intent to leave, while this rises to 34% among those who have. Notably, high-performing employees who heavily use AI are often the key talent companies want to retain.

The research suggests that AI can help employees improve work efficiency, expand thinking, and boost innovation. However, it can also lead to cognitive overload and a series of personal and organizational impacts. The findings indicate that the key is not how much individuals use AI, but how employees, teams, leaders, and organizations shape AI usage. Therefore, it is recommended to: 1) redesign work, tasks, and tools to foster human-AI collaboration; 2) set clear expectations for AI and workload; 3) shift measurement metrics from activity volume and intensity to impact; 4) develop employees’ skills in managing AI workload; 5) treat human attention as a limited resource and deploy it strategically.