Charting Global Government AI Readiness Index: A Five Year Longitudinal Review (2020-2024)
DOI:
https://doi.org/10.52131/pjhss.2026.v14i1.3222Keywords:
Artificial Intelligence, Government Artificial Intelligence , Readiness Index, Global Comparative AnalysisAbstract
The Government Artificial Intelligence readiness is a multi-faceted issue as AI-ready government needs a strategic vision, institutional capacity, digital infrastructure and human resources to develop and govern AI in an ethical way. This study attempts to provide comprehensive review of global government AI readiness trends and regional dynamics over the period 2020-2024, using Oxford Insights government AI readiness index. A 5-year longitudinal comparative approach is used to reveal inter-regional differences and intra-regional variations in AI readiness scores across 155 global economies. The global economies are grouped into 9 regions including North America, Latin America and Caribbean, Western Europe, Eastern Europe, East Asia, Middle East and North Africa, South and Central Asia, Pacific, Sub-Saharan Africa. Heat maps are utilized to visualize the spatial distribution of government AI readiness. To classify economies into five categories of government AI readiness - Very Low, Low, Moderate, High and Very High - data driven classification framework of AI readiness scores is utilized. The analysis reveals notable divergence in AI readiness among global regions with North America leading the ranking in AI readiness followed by Western Europe. In contrast, Latin America and Caribbean, South and Central Asia remained among the least in AI readiness followed by Sub-Saharan Africa. The substantial heterogeneity is also observed within the economies of the same region, indicating varying levels of institutional capacity, digital innovations, human skills and infrastructure. The findings offer valuable insights for governments and policy makers seeking to identify regional gaps and benchmark national performance.
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Copyright (c) 2026 Asma Awan

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.