Economists Warn AI Layoffs Could Trigger Demand Crisis

Companies are racing to deploy generative AI as a way to cut labor costs, but workers are also the consumers who sustain corporate revenue. A Wharton School model calls this an “AI layoff trap”: each company captures the full savings from automation while sharing the resulting loss of demand with rivals. That incentive can push otherwise rational firms into an automation arms race, producing more displacement than is collectively optimal and ultimately hurting both workers and shareholders.

The Wharton paper, “The AI Layoff Trap,” by Brett Hemenway Falk and Gerry Tsoukalas was posted on April 11, 2026, and revised on June 2. It finds that retraining, universal basic income and worker equity cannot fully correct the demand externality, while a Pigouvian automation tax can. Separately, the World Economic Forum said in January 2025 that 59 of every 100 workers would need reskilling or upskilling by 2030 and 11 may not receive it — equivalent to more than 120 million people at medium-term risk of redundancy. Experts say governments should consider taxes and transition subsidies.