Poster #80 - Divergent Sociotechnical Pathways to AI Readiness Across Countries

• In Event: Saturday Poster Luncheon

Abstract

National AI readiness has emerged as a crucial component of institutional capacity and policy as governments make significant investments in AI. However, it is still unclear if AI preparedness represents several sociotechnical pathways or a single model of digital evolution. Policymakers that want to create context-sensitive AI governance plans must comprehend this diversity.
The Oxford Insights AI Preparedness Index and a few variables from the Digital Society Project are used in this study to investigate cross-national diversity in AI preparedness. The analysis spans the years 2020 through 2025. It blends a focused comparison of five nations (the United States, the United Kingdom, China, India, and the United Arab Emirates) with a worldwide descriptive evaluation. Three aspects are examined in the study: (1) general trends in AI preparedness; (2) the internal makeup of the index's main pillars; and (3) differences in digital political contexts, such as media freedom, state regulatory capability, and coordinated information systems.
The findings show that countries with relatively strong or rising AI readiness do not converge toward a single institutional model. The United States remains the highest-scoring case, while the United Kingdom remains strong but shows a modest decline. China and the United Arab Emirates achieve mid-level readiness through different institutional setups, and India demonstrates gradual improvement from a lower baseline. Disaggregated analysis also shows that technological capacity is the most stable dimension among high-performing countries, while governance and data infrastructure vary more substantially. In addition, digital political environments do not map consistently onto readiness rankings, indicating that different governance arrangements can support similar levels of AI readiness.
The results emphasize how crucial it is for policymakers to match institutional capacity with technology advancement while acknowledging the possibility of numerous viable governance options. It also adds to current policy debates over cross-national differences in technology policy, digital state capability, and public-sector AI governance.

Author

• Siyu Liu, University of Michigan Ann Arbor
  Presenting Author