This qualitative literature review examines why some countries demonstrate levels of artificial intelligence (AI) readiness that exceed expectations based on their economic complexity. Building on recent advances in AI preparedness measurement and economic complexity theory, the study synthesizes interdisciplinary literature from economics, innovation studies, AI governance, and development policy. The review finds that economic complexity provides a necessary structural foundation for AI readiness but is insufficient on its own to explain cross-country variation. Countries that overperform relative to their structural constraints consistently benefit from complementary drivers, particularly regulatory and ethical governance frameworks, while digital infrastructure and human capital play context-dependent roles across income levels. The analysis further identifies three dominant national coordination models—state-led, market-responsive, and distributed innovation systems—through which countries translate latent capabilities into applied AI readiness. The study contributes a conceptual benchmark for understanding AI overperformance and offers policy-relevant insights for addressing the global AI divide through context-sensitive institutional design
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