AI is supposed to save workers time. Instead, some employees report spending hours every week cleaning up after it.
A new report from Glean's Work AI Institute, produced with researchers from universities including Notre Dame, Stanford, and UC Berkeley, found that white-collar workers spend an average of 6.4 hours a week "botsitting" AI — feeding it context, checking outputs, debugging mistakes, and cleaning up errors.
The researchers surveyed 6,000 full-time workers in the US, UK, and Australia who primarily work on computers or digital tools between December 2025 and January 2026.
The term "botsitting" was coined by the report's authors to describe the often-overlooked work required to make AI useful.
"Workers now burn an average of 6.4 hours a week botsitting — most of a full working day, every week," the report said.
'Often tedious' and 'exhausting' work
The findings highlight a growing disconnect between individual productivity gains and companywide performance — a productivity paradox many companies are facing, Business Insider's Juliana Kaplan and Jacob Zinkula reported this week in a multi-part series, "The Great Coding Reset."
While 87% of workers surveyed in Glean's report said they use AI at work and 75% said it makes them more productive, only 13% said their organization was performing significantly better because of it.
According to Rebecca Hinds, head of the Work AI Institute at Glean and one of the report's authors, much of the missing productivity is being consumed by work employees never expected to do.
On the "Cognitive Revolution" podcast on Wednesday, Hinds described botsitting as "often tedious," and "exhausting" work that is "not rewarded and it's not appreciated or tracked or measured and certainly not incentivized within the organization."
The exit risk
The burden appears to be taking a toll on employee morale.
The report found that workers who spend an unusually large share of their AI time botsitting are 73% more likely to be actively looking for another job.
"Workers who absorb it without recognition or reward grow exhausted. Then they grow resentful. Then they start polishing their résumés," the report said.
According to the report, the frustration goes beyond the extra work. Many employees now spend their time moving information between disconnected AI systems, fixing mistakes, and providing context that the tools should already have — effectively becoming the go-between for technologies that don't work well together.
In some cases, workers are also being asked to automate the parts of their jobs they enjoy most, Hinds said on the podcast, pointing to customer-service employees who enjoy building relationships but are increasingly expected to supervise AI agents instead.
"That's what gives you joy and meaning at work," she said. "That is very dangerous."
Breaking the botsitting cycle
The solution isn't simply to deploy more AI, according to researchers. The organizations seeing the biggest gains are often the ones doing more work around AI — helping employees access the right context, teaching them how to use the technology effectively, and establishing clearer standards for what good AI-assisted work looks like.
"The companies pulling ahead are doing something different," the report said.
"They aren't spending a greater share of their AI time using AI. They're spending a greater share on the work around it: setting context, defining what 'good' looks like, building judgment, and deciding what should never have been handed to a model in the first place."
The alternative, the authors warned, is continuing to pay the price in botsitting, and "in the steady departure of the people who got tired of cleaning up after the bots."
Has your company's AI adoption left you "botsitting" or reconsidering your job? Contact this reporter via email at [email protected] or Signal at thibaultspirlet.40. Use a personal email address, a nonwork WiFi network, and a nonwork device; here's our guide to sharing information securely.