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A new global study has found that the rise of artificial intelligence at work is creating an unexpected burden: employees are now spending hours every week “babysitting” the very tools meant to boost productivity.
According to research by Glean’s Work AI Institute, workers spend an average of 6.4 hours a week supervising AI system—roughly the equivalent of an entire workday. This time goes into tasks like feeding the system context, checking outputs, correcting errors, and re-running prompts to get usable results.
The findings come amid rapid adoption of AI tools across workplaces. As many as 87% of employees now use AI regularly, and 75% say it helps them work faster or more efficiently. However, these individual gains are not translating into meaningful organisational outcomes. Only 13% of respondents reported significant business performance improvements, highlighting what researchers call a widening “AI productivity paradox.”
The report introduces the term “botsitting” to describe the growing workload tied to managing AI. While AI can quickly generate drafts or automate tasks, much of that time is offset by the need to verify accuracy, rewrite sections, and ensure outputs meet professional standards. In many cases, the effort required to fix the results cancels out the time initially saved.
Another concern flagged by the study is what researchers call “botshitting”—when employees submit AI-generated work without fully reviewing or understanding it. Around 69% of workers admitted to doing this at least once, raising serious questions about content quality, accountability, and decision-making in AI-assisted environments.
Read more: 94% praise AI-generated code, but 82% report production failures: Report
The added workload is also affecting employees’ well-being. Workers who spend a disproportionate amount of time supervising AI systems are 73% more likely to look for a new job, suggesting that the hidden labour behind AI adoption is leading to fatigue and dissatisfaction.
A key issue identified by researchers is that AI tools often lack the specific context needed for workplace tasks. As a result, employees must continuously guide and correct the systems, effectively acting as intermediaries between the technology and the final output.
The study underscores a growing reality in modern workplaces: while AI is making certain tasks faster, it is also creating a new layer of invisible labour. Instead of replacing work, it is reshaping it—turning employees into supervisors, editors, and quality controllers of digital systems.
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