Botsitting trend: The hidden AI workload that’s taking up employees’ time

Botsitting is creating a new cognitive workload

Gurleen Baruah, Organizational Psychologist at That Culture Thing, tells indianexpress.com, “AI has entered everyday work at an unprecedented scale, but this has really happened only over the last couple of years. We are still in a transition phase, where both the technology and how people use it are evolving. Recent workplace studies suggest that a large majority of employees spend significant time reviewing, correcting, or verifying AI-generated work. That’s what botsitting is. AI can produce large volumes of content quickly, but humans still have to separate what’s useful from what’s inaccurate or irrelevant.”

Now for employees, Baruah states, this creates a different kind of mental workload. Instead of creating from scratch, people are constantly evaluating, filtering, and correcting. “That sustained vigilance increases cognitive load, leads to mental fatigue, and can sometimes be more exhausting than doing the work yourself. AI can assist judgment, but it cannot replace human judgment or accountability,” states Baruah.

Why botshitting happens and its workplace risks

This is becoming increasingly common. Once people spend a lot of time botsitting, Baruah says, there is a temptation to stop checking every detail and simply pass AI-generated work along. The output may not be completely wrong, but it can lack context, nuance, or good judgment. Over time, this creates several risks. Poor-quality decisions, rework, wasted time, and reduced trust become more likely.

Baruah notes, “It can also discourage critical thinking because people begin relying on AI instead of developing their own reasoning. There is also a hidden cost: every unnecessary AI query consumes resources, including energy and computing power. Most importantly, accountability becomes blurred. We can hold people accountable for decisions, but we cannot hold AI accountable. That responsibility will always remain with humans.”

Balancing AI productivity with human oversight