The rapid diffusion of AI simultaneously exacerbates traditional market failures─information asymmetry, externalities, oligopoly, and economies of scale─while creating novel institutional challenges arising from its technical features, such as risk uncontrollability and limited explainability. Governments respond through two domains: governance for risk management and industrial policy for competitiveness. These domains, however, are mutually reinforcing rather than separate: governance builds trust that stimulates markets, while industrial policy provides the technological foundation for effective governance. This paper, grounded in theories of market failure, compares the latest institutional designs in the United States, Europe, China, and Japan. It highlights how the interplay between governance and industrial policy forms a virtuous cycle, and discusses theoretical and policy implications for the integrated design of national AI strategies.
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