Botsitting: The Work Draining AI Gains
June 26, 2026
AI Summary
5 min readBotsitting: The Hidden Labor Eating AI's Productivity Gains
A new report from Glean and the Work AI Institute, part of their 2026 Work AI Index, surfaces a phenomenon most knowledge workers will recognize immediately: the work required to make AI usable is itself becoming a significant drain on time and energy. The report's headline numbers tell a contradictory story — 87% of digital workers now use AI at work, 75% say it makes them more productive, and they report saving an average of 11 hours per week through automation. Yet only 13% say their organization is performing significantly better as a result. The gap between individual gains and organizational outcomes is where the real story lives.
What Botsitting Actually Looks Like
The Work AI Institute organized workers' AI-related time into three categories. Learning and building agents accounted for 27% of AI time. Actually using AI to complete work took 36%. But the largest chunk — 37% of all AI time — went to what they call "botsitting": the labor required to make AI usable, including feeding it missing context, checking its outputs, debugging its mistakes, rerunning prompts, and cleaning up confident but wrong answers.
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What you'll learn
- 1 (01:02) **Report Introduction** - Overview of the Glean/Work AI Institute report on bot sitting as hidden labor from AI adoption
- 2 (02:17) **Headline Statistics** - 87% use AI, 75% report 11 hours saved weekly, but only 13% see significant organizational improvement
- 3 (03:06) **Host Disagreement on Gains** - Individual productivity does not automatically become organizational performance without deliberate mechanisms
- 4 (04:31) **Bot Sitting Definition** - Invisible labor of feeding context, verifying outputs, debugging, and cleaning up AI mistakes (average 6.4 hours/week)
- 5 (05:08) **AI Time Allocation** - Breakdown showing 37% of AI time spent on bot sitting versus 36% on active work and 27% on learning agents
- 6 (05:35) **Productive vs Unproductive Bot Sitting** - Productive includes verification and context addition; unproductive includes tool switching and repeated cleanup
- 7 (06:30) **Exhaustion Multiplier** - Every 10% more time on context feeding correlates with 25% higher burnout likelihood
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Show Notes
As AI spreads through the workplace, workers are saving time — but also spending hours feeding context, checking outputs, debugging mistakes, and cleaning up the mess. Today’s episode digs into why “botsitting” may become one of the defining challenges of the agentic AI era, and what separates organizations that turn AI use into real transformation from those that don’t.
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