Sustainable Artificial Intelligence Adoption in E7 Economies: The Roles of Education, Foreign Direct Investment, Economic Growth and Carbon Emissions

Abstract

Artificial intelligence (AI) has become a transformative technology shaping economic development and technological innovation, especially in emerging economies. The factors that influence the adoption of AI, however, are under‐researched, particularly in structurally heterogeneous settings like the E7 countries. This study examines the impact of education spending, foreign direct investment (FDI), economic growth and environmental pressures (proxied by CO 2 emissions) on AI adoption in E7 economies from 2004 to 2024. The research uses a distribution‐sensitive panel estimation method to account for the diverse effects at various levels of AI usage rather than relying on the average effect approach. The empirical results show that education spending and economic growth have a significant positive relationship with AI adoption, with FDI having mixed effects depending on institutional capacity and its development. Environmental pressures display a complex relationship with AI diffusion, reflecting both efficiency‐driven and structural constraints. The results reveal that the adoption of AI is multifaceted and evolves in various stages, influenced by economic capacity, institutional quality and environmental factors. This study adds to resource‐based theory, institutional theory and digital transformation theory by emphasizing the conditional and nonlinear aspects of the adoption of AI in emerging economies. It also provides valuable policy guidance, highlighting the need for holistic strategies that integrate the development of human resources, institutional capacity, sustainable investment flows and the green digital transition. The findings offer practical recommendations for policymakers aiming to drive inclusive and sustainable growth of AI‐driven AI power in emerging economies.