UK workers spend nearly a day weekly ‘botsitting’

A study by Glean’s Work AI Institute found UK digital workers use AI in day-to-day tasks but spend significant time making it usable. The institute reported an average of 6.4 hours per week spent “botsitting”: providing missing context, checking outputs, debugging errors, rerunning prompts and cleaning up confident-but-wrong responses.

Glean surveyed digital workers in the UK, the US and Australia. In the UK, 90% of respondents said they use AI daily. Seventy-seven percent reported that AI makes them more productive and described an average time saving of about 12 hours per week from automation and faster task completion. The institute said much of that gain is offset by time spent supervising and correcting AI.

The study found UK workers spend a larger share of their time botsitting than peers in the US and Australia. Glean also reported that 69% of UK respondents admitted to what the institute calls “botshitting”—submitting AI-generated work they had not fully reviewed, did not fully understand, or could not defend if asked.

More than half of UK workers in the survey, 53%, said critical information needed for their jobs is not accessible through their AI systems. Glean classified workplaces as “context-poor” or “context-rich” based on how much job data AI tools can access. Employees in context-poor environments were more than three times as likely to report feeling worn out by AI. Workers in context-rich organisations were 52% less likely to deliver low-quality AI work, spent less time botsitting and were 31% less likely to admit to botshitting.

The institute reported that only 18% of respondents said AI has significantly improved overall organisational performance. Glean pointed to cases where firms focused on user numbers and tool adoption without changing workflows, data access or governance, which increased the burden on employees rather than reducing it.

Rebecca Hinds, head of the Work AI Institute at Glean, noted that organisations succeeding with AI start by examining the work to be done, choose tools that fit tasks and ensure AI is governed within normal workflows. She added that UK organisations have moved quickly to put structure around AI, and the next step is giving AI the right enterprise context and measuring whether it improves outcomes.

Glean recommended that firms give AI access to relevant data and context, change processes to incorporate AI safely and measure success by outcome improvements rather than raw adoption metrics. The institute warned that without such changes, the net effect of workplace AI could be limited or negative as workers spend substantial time making the technology usable.