HBR IdeaCast The Hidden Causes of AI Workslop—and How to Fix Them
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Mar 10, 2026 
Jeff Hancock, Stanford communication professor who studies human–computer interaction and trust, joins to dissect AI-generated 'workslop.' He explains how AI can produce convincing but low-quality outputs. He explores management pressures, lack of training, and hidden AI use. He discusses team redesign, measuring mandates and mindsets, and building trust to prevent workslop.
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Workslop Signals Leadership Failures
- Workslop is usually a symptom of organizational issues, not individual laziness.
- Two main drivers are vague top-down AI mandates and pressure to do more because AI exists.
Workslop Harms Trust And Wastes Time
- The costs of workslop are cognitive and emotional, not just time lost.
- Recipients spend ~2 hours resolving an instance and often feel annoyed, judge senders as less competent, and lose trust.
Stop Mandating AI Use Start Redesigning Team Workflows
- Avoid blanket AI mandates; instead redesign team workflows to integrate AI where it helps specific tasks.
- Treat teams like Toyota did factories: involve employees in rethinking how work gets done with AI.