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The AI Preparedness Index (AIPI) measures a country’s readiness for AI adoption by evaluating key macro-structural indicators. It encompasses four crucial dimensions: digital infrastructure, human capital, technological innovation, and legal frameworks. Each dimension is derived by normalizing and averaging various sub-indicators, such as robust digital infrastructure, ongoing human capital investment, inclusive STEM education, labour and capital mobility, a dynamic R&D environment, and adaptable legal systems for digital businesses. Together, these factors provide a comprehensive assessment of how well-positioned a nation is to integrate AI into its economy.
Looking at regional groups, North America leads with the highest overall AI Preparedness Index of 0.74, demonstrating strong performance across all sub-indices. It particularly excels in Regulation and Ethics (0.21) and Digital Infrastructure (0.18). Europe follows with an AIPI of 0.63, showing balanced development across dimensions but slightly lower scores than North America. The Asia and Pacific region ranks third among regional groups with an AIPI of 0.52, while Sub-Saharan Africa shows the lowest regional score at 0.34, indicating significant room for improvement across all dimensions.
Among analytical groups, the G7 (Major advanced economies) shows the highest AIPI at 0.72, reflecting these nations’ technological leadership and robust regulatory frameworks. Their particular strength in Regulation and Ethics (0.20) suggests a strong focus on responsible AI development. Advanced economies as a whole score 0.683, demonstrating strong capabilities across all dimensions, particularly in Digital Infrastructure (0.175) and Regulation and Ethics (0.188). The Euro area (0.67) and European Union (0.66) show very similar scores across all dimensions, indicating consistent AI development and regulatory approaches across European nations. The ASEAN-5 group performs relatively well with an AIPI of 0.60, showing particular strength in Human Capital and Labor Market Policies (0.16), suggesting effective workforce development strategies. There’s a notable gap between advanced and emerging economies. Emerging market economies score 0.465 overall, with particular challenges in Digital Infrastructure (0.111) and Innovation and Economic Integration (0.108). This gap is even more pronounced for low-income countries, which score just 0.322 overall, with particularly low scores in Digital Infrastructure (0.062) and Regulation and Ethics (0.08). Regional variations are also significant. Latin America and the Caribbean (0.43) and the Middle East and Central Asia (0.40) show similar overall levels of AI preparedness, though with different patterns across dimensions. The Middle East and Central Asia shows relative strength in Human Capital (0.12) but lags in Digital Infrastructure (0.09), while Latin America maintains more consistent scores across dimensions.
A clear digital divide between advanced and developing economies, Strong correlation between economic development and AI preparedness, Regional variations in focus areas and challenges, The importance of comprehensive development across all dimensions for high AI preparedness. These findings suggest the need for targeted interventions in different regions, particularly focusing on digital infrastructure in developing regions and regulatory frameworks in emerging markets. The significant gaps between advanced and developing economies also indicate potential challenges in ensuring equitable global AI development and adoption.
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