A new, invisible form of labor called "botsitting"—feeding context, checking outputs, and debugging—consumes 37% of workers' AI time. This is more time than they spend actively using AI to complete tasks (36%), creating a significant, hidden productivity drain and burnout risk.

Employees, burned out from the unrewarded labor of "botsitting" (managing AI), eventually hit a breaking point. This leads them to "botshit"—delivering AI-generated work they can't explain or defend. The root cause is systemic, not just individual laziness.

The shift to powerful AI agents creates a new psychological burden. Professionals feel constant pressure to keep their agents running, transforming any downtime—like meetings or breaks—into a source of guilt over 'wasted' productivity and underutilized AI assistants.

The employees engaging most with AI, and therefore doing the most "botsitting," are also more likely to be on the job market. This isn't just about tedious work; it signals to them that their current employer lacks a coherent AI strategy and isn't providing them with effective, context-aware tools.

Andrew Wilkinson reveals the hidden cost of using AI agents for automation. He spends the majority of his time debugging and improving them, with only a small fraction dedicated to actual productive output. This highlights the immaturity of current agent technology despite its power.

Despite employees saving 11 hours weekly with AI, only 13% of organizations see significant improvement. This highlights a structural failure to translate individual efficiency into organizational effectiveness, a problem that exists even without the cost of "botsitting"—the hidden labor of managing AI.

The burnout from "botsitting" leads to "botshitting"—a slow surrender of agency where workers ship unverified AI outputs. This creates a vicious cycle of low-quality work, increased rework, and moral disengagement, with 40% of workers blaming AI for failures instead of themselves.

The widely touted time savings from AI are significantly eroded by "botsitting": the untracked, unrewarded work of feeding AI context, debugging outputs, and cleaning up its messes. This hidden labor is a primary reason individual gains don't translate to organizational wins.

When AI empowers non-specialists to perform complex tasks (e.g., marketers writing code), it creates a new, hidden workload for experts. These specialists must then spend significant time reviewing, correcting, and guiding the AI-assisted work from their colleagues, creating a new form of operational drag.