Artificial Intelligence, Competition, and Welfare

We propose a policy-relevant research agenda examining how market power in upstream artificial intelligence (AI) affects downstream prices, industry structure, factor returns, and welfare—especially whether labor-displacing AI leaves workers worse off. In our open-economy general equilibrium model, AI is a priced, imported input. Our main model features two nontraded sectors and firms making discrete adoption decisions about technology. Adoption reduces unit costs, displaces some types of workers, and depresses wages for those workers via diminishing returns elsewhere, while leaking AI fees abroad. We identify conditions under which market power in AI leads to a "double harm" for displaced workers, who may experience real wages cuts when AI becomes available at low prices, and then experience further harm from increases in AI prices. Strategic AI pricing reduces welfare by raising downstream marginal costs (via usage fees) and limiting entry and variety (via access fees). We derive an adoption frontier linking feasible usage fees to displaced workers’ outside options, showing that a monopolist typically makes use of both types of fees and prices on the frontier; capping one fee shifts rents to the other. Regulating both fees, alongside policies that absorb displaced labor, can raise national welfare.