Workslop is the workplace form of AI slop . The researchers who coined the term define it as “AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.”

Origin

The term was introduced on 22 September 2025 in the Harvard Business Review article “AI-Generated ‘Workslop’ Is Destroying Productivity”, by Kate Niederhoffer, Gabriella Rosen Kellerman, Angela Lee, Alex Liebscher, Kristina Rapuano and Jeffrey T. Hancock of BetterUp Labs and the Stanford Social Media Lab. BetterUp is a commercial coaching company, which is worth knowing when reading the survey behind the article.

How it differs from AI slop

AI slop is low-quality generated content published for an audience: articles, images, videos. Workslop is handed to a colleague. The authors describe the mechanism: workers can now quickly produce “well-formatted slides, long, structured reports, seemingly articulate summaries of academic papers by non-experts, and usable code”, but some use that ability “to create content that is actually unhelpful, incomplete, or missing crucial context about the project at hand.” The cost then lands on the recipient: “it shifts the burden of the work downstream, requiring the receiver to interpret, correct, or redo the work. In other words, it transfers the effort from creator to receiver.”

AI slopWorkslop
AudienceThe public, a platformA colleague, a team
HarmA degraded information environmentRework, delay and lost trust between people
Who noticesReaders, moderatorsThe person who has to fix it

Why it matters

Workslop explains part of the gap between how much organisations use generative AI and how little measurable return many report: output volume rises, but if the output needs rework, the work has only moved. Practical counter-measures follow from the definition: judge AI-assisted deliverables by whether they advance the task, make the author responsible for checking what they send, and say when content was drafted with AI so the receiver knows what to check.

Sources

Further reading

  • AI slop : the public-facing version of the same problem
  • Hallucination : one common reason workslop is wrong rather than just thin
  • Shadow AI : AI use the organisation does not see, which makes workslop harder to trace