AI Fails to Reduce Workers' Burden, Instead Increases Work Intensity

Recent authoritative studies and workplace surveys show that artificial intelligence (AI), once expected to "reduce the burden", has not alleviated the work burden on workers in practical applications. Instead, it has significantly increased the work intensity of workplace employees by accelerating work rhythms, expanding task scopes, and blurring work boundaries. Behind this phenomenon is the combined effect of unbalanced distribution of technological dividends, misplaced corporate management expectations, and cognitive biases, which has become a new pain point in the current workplace.

According to a large-scale study conducted by ActivTrak, a human resources analysis and efficiency tracking software company, an analysis of 1,111 enterprises, 164,000 employees, and more than 443 million hours of working time found that employees' work intensity has increased comprehensively after using AI tools. A comparison of employees' digital behaviors 180 days before and after using AI shows that the time spent on communication tools such as emails and instant messaging has more than doubled, the time spent on management tools such as human resources and finance has increased by 94%, while the time spent on deep work such as solving complex problems and creating has decreased by 9%. No significant changes were observed in employees who did not use AI.

This conclusion is supported by multiple studies. A study led by Aruna Ranganathan, an associate professor at the Haas School of Business at the University of California, Berkeley, tracked a 200-employee technology company for 8 months and found that generative AI improved employees' single-task processing efficiency, but the number of tasks doubled, the work rhythm accelerated, and the total working hours ultimately increased by 18%. Many employees fell into the vicious circle of "the more efficient, the busier". The "2026 Workplace Survival Report" by Zhilian Recruitment further shows that the anxiety rate of workplace people under 34 has risen to 78%, and one of the core incentives is the significant increase in corporate expectations for employees after the popularization of AI.

The core logic of AI increasing work intensity is reflected in three aspects. First, task expansion and workload inflation. AI simplifies basic work processes, allowing employees to quickly complete tasks that originally took a long time. However, enterprises have not converted the saved time into employees' rest time, but instead assigned more tasks, forming a vicious circle of "efficiency improvement = task increase". After introducing AI, Steelhead Technologies, a software startup, automated administrative work and improved code writing efficiency, but the number of tasks undertaken by employees increased simultaneously, and "the work to be done seems endless" has become a common feeling.

Second, blurred work boundaries and prominent multi-task pressure. The convenience of AI allows work to easily penetrate into rest time. Many employees issue instructions to AI during lunch, meeting breaks, and even late at night, constantly compressing the original work gaps. At the same time, AI enables employees to manage multiple work threads at the same time. Although it seems efficient, it actually leads to frequent switching of attention, a sharp increase in cognitive load, and long-term "multi-task stress state", which intensifies physical and mental fatigue.

Third, the hidden increase in rework costs and ability loss. AI-generated content often has logical loopholes and factual errors, and many employees need to spend a lot of time correcting them, forming the embarrassing situation of "AI saves 1 hour, but rework takes 2 hours". More notably, over-reliance on AI can lead to the degradation of employees' deep thinking abilities. A joint study by Stanford University and MIT shows that 60% of employees will directly adopt AI's standardized solutions and abandon personalized optimization. In the long run, they may lose their core competitiveness and fall into anxiety of "being replaced by AI".

It is worth noting that the productivity improvement brought by AI flows more to enterprises and capital rather than workers. A 2026 global survey by McKinsey shows that 42% of enterprises have reduced costs through AI, and 59% have achieved revenue growth. However, these benefits have hardly been used to shorten employees' working hours or increase salaries. Only 12% of employees have received salary increases after the popularization of AI, while 62% of employees have seen their workload increase by more than 30.