INTERNATIONAL JOURNAL OF PROFESSIONAL STUDIES

AI reshapes societies across the globe, and each country adopts AI with different levels of commitment and adapts to the shifts caused from cross-tech influences, economies, cultures, and technologies. Moreover, investment in AI R&D differs across countries. Ready-made assessments offer a snapshot of AI integration that value AI at one point in time, and not as an ongoing integration dynamic. This study aims to address that gap using advanced algorithms such as Random Forests, XGBoost or Stacking that allow for profiling national AI adoption indicators real time. Utilizing information obtained from the Global AI Vibrancy Measurement Tool makes this analysis much more sophisticated, providing a better ranking that adapts and predicts beyond obsolete systems. It is apparent that having many differing countries per AI cluster is not feasible for controlling AI adoption per country, since flexibility regulations along with economic support and an AI-enabled labor force determines dominance. Currently, the US and China remain at the forefront, but the rapid adoption AI policies in India or Egypt may contribute to shifts in competition concerning emerging economies. This strategy allows real-time information to capture the dynamism of investment and provide shifts in policies along with operational frameworks for policymaking.

Keywords: Artificial Intelligence Adoption; Machine Learning; AI Readiness Index; Global AI Competitiveness; AI Policy; AI Investment.