Robert E. Litan proposes a government insurance plan for AI-driven job disruption. It combines wage insurance, retraining assistance, and entry-level tax credits. The plan would cost about $60 billion yearly under a 6% unemployment equivalent scenario. Private insurers cannot cover AI job risks due to high correlation and unknown actuarial bases. UBI is dismissed as too costly and insufficient for higher-income displaced workers. The proposal treats AI disruption like other low-probability, high-impact events. Each policy targets a different aspect of worker transition. Over 1,000 economists have urged action on AI labor market risks. Public concern about AI job disruption remains high in the U.S.

• $60 billion per year
• 6% sustained unemployment equivalent
• $784 billion net annual cost for UBI