Workers are spending over 6 hours a week 'botsitting' AI, fueling job frustration

In an alarming trend, white-collar employees are dedicating an average of 6.4 hours each week to a task dubbed 'botsitting'—essentially managing and refining AI outputs. A comprehensive study conducted by Glean's Work AI Institute, in collaboration with scholars from prestigious institutions like Notre Dame, Stanford, and UC Berkeley, sheds light on this unexpected burden. The research surveyed 6,000 full-time workers across the US, UK, and Australia, revealing that rather than freeing up time, AI is generating a new set of responsibilities. Workers find themselves providing context, debugging errors, and correcting AI-generated mistakes, resulting in a significant disconnect between personal productivity and overall organizational performance. While 87% of respondents acknowledged using AI tools to enhance their productivity, only a mere 13% felt their organizations were reaping substantial benefits from these technologies. Rebecca Hinds, the head of the Work AI Institute, described botsitting as often tedious and exhausting work that goes unrecognized and unmeasured. This workload appears to be adversely affecting employee morale. The findings indicate that those who spend a disproportionate amount of their AI time on botsitting are 73% more likely to seek new job opportunities. The report highlights that while some employees are asked to automate aspects of their roles they find fulfilling, such as customer interactions, they are increasingly relegated to overseeing AI systems instead. Experts suggest that merely increasing AI deployment won't solve the problem. Organizations that are truly succeeding with AI are investing in the necessary support for their employees. This includes providing the right context, effective training, and clear standards for quality AI-assisted work. The report concludes with a stark warning: failing to address the botsitting issue could lead to a cycle of employee dissatisfaction and turnover as workers tire of the constant need to clean up after AI tools.