Mandon, Pierre2025-02-242025-02-242025-02-24https://hdl.handle.net/10986/42856This paper examines global disparities in artificial intelligence preparedness, using the 2023 Artificial Intelligence Preparedness Index developed by the International Monetary Fund alongside the multidimensional Economic Complexity Index. The proposed methodology identifies both global and local overperformers by comparing actual artificial intelligence readiness scores to predictions based on economic complexity, offering a comprehensive assessment of national artificial intelligence capabilities. The findings highlight the varying significance of regulation and ethics frameworks, digital infrastructure, as well as human capital and labor market development in driving artificial intelligence overperformance across different income levels. Through case studies, including Singapore, Northern Europe, Malaysia, Kazakhstan, Ghana, Rwanda, and emerging demographic giants like China and India, the analysis illustrates how even resource-constrained nations can achieve substantial artificial intelligence advancements through strategic investments and coherent policies. The study underscores the need for offering actionable insights to foster peer learning and knowledge-sharing among countries. It concludes with recommendations for improving artificial intelligence preparedness metrics and calls for future research to incorporate cognitive and cultural dimensions into readiness frameworks.en-USCC BY 3.0 IGOAI PREPAREDNESSECONOMIC COMPLEXITYPEER LEARNINGPOLICY OVERPERFORMANCEWorking PaperWorld Bank10.1596/1813-9450-11073https://doi.org/10.1596/1813-9450-11073