Artificial intelligence (AI) readiness differs widely among countries due to varying capacities to attract, develop, adopt, and govern new technologies. It underscores the need to comprehend these relationships in context rather than simply identifying independent causal effects of overlapping national-capacity indicators. Although existing literature frequently identifies economic development as the primary determinant of AI preparedness, this research investigates the complex interdependencies between institutional, infrastructural, and leadership factors. Utilizing a nested hierarchical stepwise regression analysis of cross-national data from 195 countries, this study assesses the relative influence of GDP per capita, government effectiveness, digital infrastructure, leadership capacity, and geopolitical classification on AI readiness, as quantified by the Oxford Government AI Readiness Index. This hierarchical regression with nested models was chosen because it is theory-driven, which is required when using indices. The results indicate that governance effectiveness and digital infrastructure are the main predictors of AI readiness, outperforming GDP per capita and geopolitical positioning. Notably, digital infrastructure emerges as the single strongest contributor to model performance. GDP per capita initially appeared significant because it captured a nation’s economic development. However, once governance and digital capacity were included, GDP no longer explained AI readiness. This indicates that GDP serves more as a proxy for underlying structural factors rather than functioning as an independent driver in assessments of AI readiness. Consequently, it is essential to evaluate GDP in conjunction with more significant explanatory variables. In this context, key variables include digital infrastructure and governance effectiveness, suggesting that GDP alone should not be considered without recognizing these additional influential factors. Geopolitical classification played no significant role either. These findings shift the analytical focus from economic development alone to the quality of institutions and digital systems. The study contributes to the literature by demonstrating that AI readiness is less a function of a nation’s income than of institutional effectiveness and infrastructural capacity, with important implications for development policy. Efforts to reduce global disparities in AI should prioritize strengthening governance systems and investing in digital infrastructure, particularly in the Global South, rather than relying on economic or growth-led approaches alone. In contrast, the Global South Leadership Index (GSLI) is negatively associated with AI readiness, suggesting that leadership, in the absence of institutional capacity and infrastructure, does not translate into technological advancement.