The Role of AI-Driven Personalized E-Learning In Enhancing Economic Competitiveness: A Comparative Analysis of Developed And Developing Countries

Abstract

This study explores the influence of AI-driven personalized e-learning on the Global Competitiveness Index (GCI) across six countries, comprising three developed (USA, Germany, Japan) and three developing (Pakistan, India and Nigeria) nations, over a span of 17 years (2007-2023). Utilizing a least squares regression model, the analysis incorporates key variables including the Artificial Intelligence Global Index (AIGI), Human Development Index (HDI), and R&D expenditure as control variables to assess their impact on GCI. The model demonstrates a robust fit, with an R2 value of 96.79% and an adjusted R2 value of 96.50%, indicating that AI-enhanced e-learning is a significant predictor as  independent variables of economic competitiveness GCI. The findings underscore the significant role of investment in AI and e-learning technologies, particularly in enhancing economic competitiveness, as evidenced by strong positive correlations between GCI and AIGI, HDI, and R&D expenditure. The results are consistent with IBM's research, which highlights the importance of these variables in driving national competitiveness in the global market. The study concludes that AI-driven personalized e-learning is a critical lever for improving GCI, particularly for developing countries aiming to close the competitiveness gap with developed nations. The implications of this research suggest that targeted investments in AI and e-learning can substantially contribute to sustainable economic growth and international competitiveness. This study offers valuable insights for policymakers and educational institutions aiming to enhance their nation's competitiveness through strategic investments in AI-driven educational technologies.