AI Vibrancy and Renewable Energy Consumption: A Cross-Country Analysis

This study examines the association between artificial intelligence vibrancy and renewable energy consumption across 36 countries from 2017 to 2023. Using a reduced-form panel framework with Driscoll–Kraay standard errors, the results show that income per capita and government effectiveness are the dominant drivers of renewable energy consumption. At the same time, carbon dioxide emissions are negatively associated. Several dimensions of artificial intelligence vibrancy, including education, diversity, policy and governance, and digital infrastructure, are positively associated with renewable energy outcomes, although their magnitudes are comparatively modest. Research and development intensity shows limited direct association, indicating translational frictions between artificial intelligence capability and energy outcomes. Overall, the maturity of the artificial intelligence ecosystem operates as a complementary enabling factor rather than a primary determinant. The findings highlight the importance of aligning digital capability, institutional quality, and human capital with energy policy to support sustainable development.