Study: AI workslop costs companies $9M annually in lost productivity

Companies are facing a new productivity challenge called AI “workslop” — low-quality AI-generated content that masquerades as good work but lacks substance to advance tasks meaningfully. According to research from Stanford Social Media Lab and BetterUp Labs, 40% of US employees report receiving AI workslop from coworkers within the past month, with this subpar content comprising roughly 16% of workplace communications and costing organizations millions in lost productivity.

What you should know: AI workslop occurs when employees use AI tools without proper training or oversight, creating content that appears polished but fails under scrutiny.

• The Stanford study found that AI workslop is most prevalent in professional services and technology industries, with workers reporting it across all organizational levels.
• “AI workslop is what happens when organizations use the wrong AI at the wrong time, deploying large language models designed for creativity and reasoning into situations that demand precision, governance, and reliability,” says Don Schuerman, CTO of Pegasystems, a business process automation company.
• Erik Roth, founder of McKinsey’s generative AI platform Lilli, describes it as occurring when “employees take outputs from large language models almost verbatim” without proper refinement or fact-checking.

The hidden costs: Poor-quality AI content creates significant downstream burdens for recipients who must fix errors and rewrite content.

• Employees spend nearly two hours of additional work on average dealing with AI workslop, carrying an “invisible tax” of up to $186 per month per affected worker.
• An organization of 10,000 employees with 41% AI workslop prevalence can incur nearly $9 million in lost productivity annually, according to the labs’ calculations.
• Paul Farnsworth, president at Dice, a tech recruiting platform, warns that “over-reliance on AI can create a false sense of efficiency” where workers think they’re moving faster but end up “spending more time revisiting and clarifying later.”

Impact on workplace relationships: AI workslop is damaging trust and collaboration among colleagues.

• When receiving low-quality AI content, 53% of employees report feeling annoyed, 38% confused, and 22% offended.
• Workers view colleagues who produce AI workslop as “less creative, capable, and reliable,” with 42% considering them “less trustworthy” and 37% viewing them as “less intelligent.”
• The problem is escalating workplace tensions, with 34% of employees reporting AI workslop incidents to management and 32% saying they’re less likely to work with someone after receiving such content.

How to prevent AI workslop: Education and governance emerge as the primary solutions for organizations struggling with low-quality AI outputs.

• “The first lines of defense against AI workslop are education and governance,” Schuerman advises, recommending AI literacy training and encouraging employees to question AI outputs.
• Organizations need structured workflows with “visibility, feedback loops, and audit trails” so workers can see what quality AI work looks like.
• Farnsworth emphasizes that “organizations need to remember that AI is only as good as the human behind the wheel” and must invest in guidance and governance to prevent AI tools from becoming liabilities.

What they’re saying: Industry experts stress that addressing AI workslop requires both technical and cultural changes.

• “Poorly managed AI doesn’t just slow work down, it erodes trust. When employees are constantly fixing or fact-checking AI-generated outputs, it creates fatigue and skepticism,” Schuerman explains.
• “Training employees to effectively use generative AI starts with demystifying it,” Farnsworth notes, adding that as employees become more comfortable with AI tools, workslop incidents will decrease over time.
• “Ultimately, AI quality isn’t just a technical issue; it’s a cultural one. Organizations that invest in predictable, governed AI not only get better results, but they also build a workforce that trusts and amplifies those systems responsibly,” Schuerman concludes.