tech
Harvard Business Review warns AI 'workslop' is rotting companies from the inside
HBR says companies that went all-in on AI face “knowledge decay” as low-quality outputs pile up, erode trust, and cost $9M a year in rework.
TL;DR
- Companies that heavily adopted generative AI are facing "knowledge decay," where low-quality AI outputs degrade organizational information.
- AI-generated content, termed "workslop," masquerades as good work but lacks substance, requiring significant time for correction.
- Workslop costs businesses an estimated $186 per worker per month, translating to over $9 million annually for a 10,000-employee company.
- Receiving workslop diminishes trust in colleagues, impacting perceptions of capability and reliability.
- Most organizations are not seeing measurable returns on generative AI investments, with no clear economy-wide productivity gains.
- Knowledge decay is distinct from AI hallucinations and describes the cumulative effect of errors and low-effort work on an organization.
- The hiring process is particularly damaged, with AI-generated resumes and screening tools leading to diminished trust.
- Some workers are actively sabotaging AI strategies due to fear of job displacement.
- Addressing workslop requires human oversight and verification, undermining the initial efficiency arguments for AI adoption.
- Targeted AI use on company-specific data can be valuable, unlike generic LLMs applied to unsuitable tasks.
- The true measure of AI success should be whether it improves organizational decision-making, not just individual task speed.
- While the knowledge decay framework synthesizes existing evidence, it has not yet been tested through controlled empirical studies.