TL;DR
Workers are spending over six hours weekly managing and fixing AI outputs, which is causing frustration and higher turnover intentions. The report highlights a productivity paradox in AI adoption.
A new report from Glean’s Work AI Institute reveals that workers spend an average of 6.4 hours each week supervising, cleaning up, and debugging AI systems, a task that is often tedious and exhausting. This development highlights a growing disconnect between AI’s intended productivity gains and the actual burden on employees, raising concerns about job satisfaction and retention.
The report, based on a survey of 6,000 full-time workers across the US, UK, and Australia, found that most employees spend significant time managing AI outputs rather than focusing on core tasks. While 87% of respondents use AI at work and 75% believe it makes them more productive, only 13% feel their organizations are seeing substantial performance improvements. The term “botsitting” was coined by the researchers to describe the often-overlooked work of feeding context, checking outputs, and fixing errors in AI systems.
Rebecca Hinds, head of the Work AI Institute at Glean, described botsitting as “often tedious” and “exhausting,” noting that it is rarely recognized, rewarded, or incentivized within organizations. The report also links this burden to increased turnover, with workers who spend more time botsitting being 73% more likely to actively seek new jobs. Many employees are also burdened with transferring information between disconnected AI systems and fixing mistakes, which further diminishes job satisfaction. Some workers, such as customer service reps, are also being asked to supervise AI instead of engaging in the relationship-building tasks they find meaningful.
Impacts on Employee Morale and Workforce Stability
The findings highlight a significant challenge for organizations adopting AI: while AI aims to improve productivity, the hidden costs of botsitting are leading to worker frustration and increased turnover risk. The report suggests that unless companies address these issues by improving AI integration and providing proper support, they may face ongoing talent attrition and reduced overall efficiency. This situation underscores the importance of managing AI’s role in the workplace carefully to prevent burnout and preserve employee engagement.
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As AI tools become more prevalent in workplaces worldwide, early expectations centered on automation and productivity gains. However, recent studies, including this Glean report, reveal that the actual experience often involves substantial additional work for employees. Previous research indicated that many organizations struggle with integrating AI effectively, leading to workarounds and manual interventions. The current data emphasizes that the problem is not just about deploying AI but managing its operational complexities.
“Botsitting is often tedious and exhausting work that is not rewarded or recognized and is rarely measured or incentivized.”
— Rebecca Hinds, head of the Work AI Institute at Glean
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Extent of Long-Term Impact on Workforce
It remains unclear how widespread the problem will become as AI adoption accelerates and whether organizations will implement effective solutions to reduce botsitting. The long-term effects on employee retention, mental health, and organizational performance are still being studied. Additionally, the specific strategies that could mitigate these issues are not yet fully defined or widely adopted.
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Organizational Responses and AI Management Strategies
Organizations are expected to begin reevaluating their AI integration practices, focusing on providing better context support, setting clearer standards, and rewarding employees’ efforts. Future research and industry reports will likely explore effective interventions to reduce botsitting burdens and improve worker satisfaction. Companies that proactively address these issues may retain talent better and realize more genuine productivity gains from AI investments.
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Key Questions
Why are workers spending so much time supervising AI?
Workers spend time supervising AI because the systems often produce errors, lack context, or generate outputs that need manual review, correction, or additional input to be useful.
What are the consequences of botsitting for employees?
Consequences include increased frustration, exhaustion, and a higher likelihood of seeking new employment, especially when the work is unrecognized or unrewarded.
Can better AI design reduce the botsitting workload?
Potentially, yes. Improving AI systems to be more accurate, context-aware, and integrated could lessen the need for manual supervision and correction.
Does this issue affect all industries equally?
The report primarily focuses on white-collar, digital-dependent roles. The extent of the problem may vary across sectors depending on AI adoption levels and job nature.
What should organizations do to address this problem?
Organizations should improve AI system integration, provide clearer guidelines, reward employees’ efforts, and invest in training to reduce the burden of botsitting and improve job satisfaction.
Source: Hacker News
