The role of artificial intelligence in renewable energy development: Insights from less developed economies

Global climate change and the growing pressure of energy transition pose complex challenges for less developed economies in achieving environmental sustainability . Artificial intelligence technology offers a promising avenue for advancing renewable energy development. This study analyzes the non-linear impact of AI technology on the renewable energy, drawing on AI patent data from 56 less developed economies from 2007 to 2022. The findings reveal a significant “inverted U-shaped” relationship. That is, AI initially drives renewable energy adoption, but as technological development reaches a certain threshold, its marginal benefits decline, potentially leading to negative effects. Moreover, institutional quality plays a crucial moderating role, with a strong rule of law enhancing AI's positive impact, while digital economic expansion exerts a weakening effect. Technological innovation acts as a key mediating mechanism, facilitating AI's influence on renewable energy adoption. Furthermore, the impact of AI varies across different renewable energy sources , with significant non-linear effects observed for biomass and wind energy , while its influence on solar and hydropower remains limited. These insights contribute to the literature on sustainable energy transitions and provide valuable policy implications for optimizing AI-driven renewable energy strategies in less developed economies. • AI drives energy transitions in less developed economics. • AI and renewable energy demonstrate an inverted-U relationship. • Legal frameworks strengthen AI's impact on energy transitions. • The digital economy moderates AI's role in energy development.