A new study reveals that workers are increasingly using AI to produce “workslop”—low-quality, AI-generated work that appears legitimate but lacks substance and requires others to fix or redo it. Research from BetterUp Labs, a coaching and development platform, and Stanford Social Media Lab found that 40% of 1,150 surveyed employees received workslop in the past month, with recipients spending nearly two hours cleaning up the mess.
What you should know: Workslop represents a fundamental shift in workplace dynamics, where AI tools enable workers to offload cognitive work to their colleagues rather than genuinely improving productivity.
- The researchers define workslop as “AI-generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.”
- Unlike traditional corner-cutting, workslop “uniquely uses machines to offload cognitive work to another human being,” transferring effort from creator to receiver.
- The phenomenon occurs most frequently between peers but also flows from direct reports to managers.
The big picture: This trend highlights a growing contradiction between AI’s promised productivity gains and the messy reality many workplaces are experiencing.
- Professional services and technology sectors are disproportionately affected by workslop, according to the research.
- Despite widespread claims that AI will supercharge productivity, only 5% of companies have seen a return on investment in the technology, according to a recent MIT report.
- Some reports show AI improving productivity in specific areas like coding, while others reveal a more complicated landscape.
Career consequences: Workers who produce workslop face significant reputational damage among their peers and supervisors.
- Half of survey respondents view colleagues who turn in workslop as less creative, reliable, and capable.
- The practice risks professional reputation as managers and peers increasingly recognize and penalize low-quality AI-generated work.
The hidden cost: Recipients of workslop spend an average of one hour and 56 minutes fixing or redoing the work, creating a productivity drain that contradicts AI’s efficiency promises.
What they’re saying: Survey respondents described the frustrating cascade of additional work created by workslop.
- “I had to waste more time following up on the information and checking it with my own research. I then had to waste even more time setting up meetings with other supervisors to address the issue. Then I continued to waste my own time having to redo the work myself,” one respondent explained.
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