Are We Ready for AI? From Measurement to Policy Governance

Artificial intelligence readiness indexes have become influential tools shaping national strategies and international development priorities. But major AI readiness and governance rankings show average correlations of only 33-47%, revealing fundamental disagreements about what constitutes AI readiness and how to measure it. This paper empirically documents these divergences across seven leading indexes and identifies five structural problems: definitional confusion, data blind spots, temporal lags, context insensitivity, and misalignment with systemic transformation, which might incentivize countries to "invest for the index" rather than for genuine capability building. These problems particularly disadvantage Latin America and the Caribbean (LAC) countries, which despite demonstrating overlooked strengths in digital governance and adaptive innovation, tend to underperform in certain rankings. We propose an Adaptive AI Readiness Scorecard (AARS) that calibrates to country context and policy priorities in LAC, and outline a pilot implementation roadmap.