ChainCatcher report: an economic team at Anthropic built a model to analyze the impact of AI on U.S. employment, growth, and unemployment. The model treats the economy as a bundle of tasks based on U.S. Department of Labor O*NET classifications. AI can keep tasks unchanged, enhance them, automate them, or create new tasks. The U.S. economy is described as having a task-instance value of more than US$3 trillion.

Three scenarios depend on AI capability and adoption speed: a mild scenario similar to the internet era—U.S. GDP increases by 1.6% in 2030 (US$34.1 trillion, 2025 prices), the labor share is 59.4%, and the capital share is 40.6%. In a substantive scenario, AI can perform half of knowledge work, GDP rises by 8.3% (US$36.3 trillion), the wages of knowledge workers are roughly unchanged, and the labor share is 56.1%. In an extreme scenario, AI is more efficient in most knowledge work and nearly fully completes it autonomously; GDP increases by 32.4% (US$44.4 trillion), knowledge worker wages fall by more than 10%, the labor share is 45.2%, and the unemployment rate exceeds typical recession levels.

An August survey of more than 10,000 Americans shows that the typical responses are close to realistic scenarios (GDP about 10% higher by 2030, unemployment around 5%), with about 10% of respondents approaching extreme scenarios. GDP increases in all scenarios, and the transformative scenario requires more occupational transitions. The page provides technical reports and an interactive explorer.