TL;DR
Workers are spending over six hours weekly managing and fixing AI tools, which is eroding productivity and increasing job frustration. The report highlights the need for better AI integration strategies.
A new report from Glean’s Work AI Institute reveals that workers spend an average of 6.4 hours per week ‘botsitting’ AI—supervising, debugging, and cleaning up outputs—which is contributing to rising job frustration and burnout.
The report, based on a survey of 6,000 full-time workers across the US, UK, and Australia, found that while 87% of respondents use AI at work and 75% believe it boosts their productivity, only 13% think their organization is experiencing significant performance improvements. Most of the time spent on AI involves tedious tasks such as feeding context, checking outputs, and fixing errors, which often go unrecognized and unrewarded, according to Rebecca Hinds, head of the Work AI Institute at Glean.
Workers who spend a disproportionate amount of time botsitting are 73% more likely to be actively seeking new jobs. The report highlights that this extra workload is often disconnected from meaningful work, with employees acting as intermediaries between disconnected AI systems, which diminishes morale and increases frustration. Some employees are also being asked to automate parts of their jobs they enjoy, such as building relationships with clients, which further erodes job satisfaction.
Impacts of Excessive AI Supervision on Workforce Morale
The findings underscore a growing disconnect between AI’s intended purpose of saving time and actual employee experiences, which include exhaustion and resentment. As workers spend extensive hours managing AI, their overall job satisfaction declines, leading to higher turnover risks. This trend poses challenges for organizations aiming to leverage AI effectively without sacrificing employee well-being.
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Rise of AI Use and Associated Workload in Modern Offices
Recent years have seen rapid adoption of AI tools in workplaces, promising increased efficiency. However, early reports and internal studies have indicated that many employees are spending significant portions of their workweek managing these systems rather than performing core tasks. The concept of ‘botsitting’ emerged as a term to describe this hidden work, which often goes untracked and unrecognized, contributing to employee fatigue and dissatisfaction.
“Botsitting is often tedious and exhausting work that is not rewarded or measured within organizations.”
— Rebecca Hinds, Head of the Work AI Institute at Glean
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Unclear Long-Term Effects of Botsitting on Workforce Stability
It remains uncertain how widespread the long-term impacts of botsitting will be across different industries and whether organizations will implement effective solutions to reduce this burden. The full extent of turnover and morale decline linked to this issue is still being studied.
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Strategies for Reducing AI Supervision Burden and Improving Morale
Organizations are expected to focus on better AI integration practices, including establishing clearer standards, providing training, and improving system interoperability to reduce the need for manual oversight. Further research and internal assessments will likely guide future policies aimed at minimizing botsitting time and supporting employee well-being.
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Key Questions
Why are workers spending so much time supervising AI?
Workers spend time supervising AI to ensure outputs are accurate, relevant, and to fix errors or provide missing context, as AI systems often require manual oversight to function effectively.
What are the consequences of this workload for employees?
The extra workload leads to fatigue, frustration, and increased likelihood of employees seeking new jobs, especially when efforts go unrecognized or unrewarded.
Are companies aware of this issue?
Many organizations are only beginning to recognize the extent of the botsitting burden, and some are exploring strategies to better support employees and improve AI workflows.
Will this problem resolve on its own?
Without targeted efforts to improve AI systems and support structures, the problem is unlikely to resolve naturally and could worsen if workload management is not addressed.
What can organizations do to reduce botsitting time?
Organizations can invest in better AI tools, establish clear standards for AI use, and provide training to help employees use AI more effectively, thereby reducing manual oversight requirements.
Source: Hacker News
