Artificial Intelligence for Alleviating Energy Poverty: Pathways Toward Sustainable and Renewable Energy Transitions

ABSTRACT Energy poverty remains a critical barrier to sustainable development, particularly in underdeveloped and emerging economies. This study investigates how artificial intelligence (AI) can alleviate energy poverty and promote the transition to renewable energy. Using panel data from 89 countries covering the period 2010–2022, we developed a comprehensive AI index through a projection pursuit model optimized by the sparrow search algorithm. Fixed‐effects models reveal that a 1% rise in AI development reduces energy poverty by 0.461% on average. The effect is strongest in countries with moderate poverty but weaker in those with very low or very high levels. Grouped regressions show that AI may worsen energy poverty in low‐ and middle‐income nations, and significantly relieve it in high‐income ones. Furthermore, nonlinear threshold effects indicate that AI's benefits strengthen when coupled with renewable energy transition and sound governance but decline in resource‐dependent economies. Overall, this study highlights AI's potential to advance equitable, sustainable energy systems and contributes to achieving Sustainable Development Goal 7. Policymakers should therefore promote inclusive AI infrastructure, expand renewable energy integration, and ensure that technological progress aligns with equitable energy access goals.