Global Artificial Intelligence Regulatory Convergence and Divergence: Comparative Governance Frameworks and Implications for United States Trade and Diplomatic Policy

Artificial intelligence has entered the infrastructure of trade, finance, health, and public administration faster than governments have agreed on how to govern it. The European Union has enacted a comprehensive risk-based statute, the United States relies on executive guidance and sectoral rules, China has built a security-centered regime, and other major economies sit between those poles. Policymakers lack a quantitative account of how far these frameworks converge, whether that distance already suppresses trade, what produces alignment, and which diplomatic instrument best serves United States interests. This mixed-methods study examines seven jurisdictions that dominate global artificial intelligence investment. It constructs a Global AI Regulatory Convergence Index, estimates an augmented gravity model of bilateral goods and services flows, applies fuzzy-set qualitative comparative analysis, and evaluates four diplomatic alternatives. Scores range from 96.2 for the European Union to 33.2 for India, with the United States at 36.9. Regulatory distance does not yet significantly predict trade; economic size and preferential agreements dominate. Convergence follows two pathways rather than a simple Brussels Effect: European market dependence among non-Western economies, and competitive learning where capacity is rising outside the Organisation for Economic Co-operation and Development. Bilateral regulatory cooperation councils rank first under every weighting tested. The findings give United States officials an evidence base for engagement before compliance costs harden into market structure.