Can Artificial Intelligence Drive Sustainable Growth? Empirical Evidence on the AI–Energy–Growth Nexus in Advanced Economies

This study examines the short-run relationship between artificial intelligence (AI), re-newable energy, and economic growth across the G7 countries, China, and South Korea over the 2010–2025 period. Motivated by the ongoing debate on whether AI-driven digital transformation can coexist with environmental sustainability, the analysis integrates technological and energy-economics frameworks. Using panel data and the Fixed Effects (FE) estimator with Driscoll–Kraay robust standard errors, four models (A1–A2–B1–B2) are estimated to explore how AI investment affects economic growth and energy demand. The results reveal that AI investment alone does not significantly enhance short-run economic growth; however, its interaction with renewable energy capacity yields positive and significant effects, confirming the moderating role of sustainable energy infrastructure. Conversely, AI development initially increases energy demand due to the expansion of data-driven infrastructure, but a non-linear (inverted U-shaped) relationship suggests that efficiency improvements emerge beyond a certain adoption threshold. Financial development and energy prices also play significant roles in shaping energy consumption dynamics. Overall, the findings indicate that AI-driven growth and energy efficiency are complementary in the presence of strong renewable capacity and innovation systems. The study provides empirical evidence for integrating AI policies with green energy strategies to foster sustainable digital transformation.