The Botsitting Economy: AI’s Hidden Labour Problem

AI was meant to lighten work. Instead, many workers are feeding, fixing, checking, and explaining the machines. This week: botsitting, graduate career bottlenecks, regulated trust, the selective white-collar slowdown, and another Cut List shaped by AI spending.

By EBN 14 min read
A group of colourful toy robots standing together against a plain background, representing workplace AI tools that need human supervision and management.
Meet the new team. They’re fast, tireless, and apparently still need three meetings, six prompts, and a responsible adult before they can ship anything useful.

The workplace has discovered a new job. Nobody advertised it. Nobody costed it. Nobody put it on the org chart.

It is botsitting.

Workers are spending more time prompting, correcting, feeding context into AI systems, checking the output, explaining the output, and occasionally apologising for the output when it wanders into the bushes wearing a confident little hat.

That is the contradiction sitting underneath this week’s stories. AI is presented as leverage. In practice, it often creates a new layer of supervision. Humans are still there, but the job shifts from doing the work to managing the machine that is supposed to do the work.

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That has consequences. For early-career talent. For managers. For HR. For recruiters. For trust.

This Week’s Paper Cut's