AI washing

Harvard Business Review research found only approximately 2% of organisations reported layoffs tied to genuine AI deployment; the remainder were cutting in anticipation of capabilities that did not yet exist. High-profile cases include Jack Dorsey eliminating over 40% of Block workforce citing AI, with former employees disputing whether the roles could be automated.

AI washing entered the mainstream labour market vocabulary in early 2026, as corporate restructurings cited artificial intelligence while showing scant evidence of deployment. Yale Budget Lab coined the term formally, flagging companies attributing workforce reductions to AI when the underlying causes were conventional: slowing growth, weak demand, and cost pressure. Challenger, Gray & Christmas recorded 108,000 US job cuts in January 2026, the highest monthly total since 2009, with 12,304 explicitly attributed to AI.

Orgvue found 55% of business leaders admitted wrong decisions on AI-driven layoffs, with one in three having already rehired 25-50% of cut roles at greater cost. Gartner predicted 50% of companies that cut customer service staff for AI will rehire by 2027. Legislatively, California and US senators are advancing disclosure requirements to force substantiation of AI justifications.