Paul Osterman

Paul Osterman is a professor at the MIT Sloan School of Management and one of the United States' leading labour economists. In June 2026 he argued publicly that AI attribution in corporate layoff announcements is largely a cover story — that firms have used successive waves of technology as an excuse for planned restructuring for at least twenty years, with AI being the latest iteration. He cited Harvard Business Review research finding that only 2% of layoffs in AI-citing companies actually followed a demonstrable AI deployment, a figure that entered the AI-displacement debate as a benchmark for scepticism about employer claims.

Osterman's academic career spans more than four decades of research into internal labour markets, job quality, and workforce policy. He is the author of several influential books including Securing Prosperity and Good Jobs America, and served on the National Academy of Sciences committees examining the future of work. His work on internal labour markets — how firms structure careers, wage ladders, and job security internally — became foundational to understanding why external shocks (technology, offshoring, automation) translate into workforce disruption differently across industries and firm types. He has advised the US Department of Labor and Congressional committees on workforce policy.

Osterman's 'AI-washing' thesis is significant because it complicates the dominant narrative that AI is directly responsible for the current wave of white-collar reductions. If layoffs would have occurred regardless, the policy response (advance notice laws, retraining funds, tax incentives) may be addressing symptoms rather than causes. His intervention has been widely cited in the US legislative debate over bills such as New York A 9581 and California SB 947, where the question of causality directly determines what obligations employers should face.