Artificial Intelligence Innovation and the Global Energy Trilemma: A Cross‐Country Panel Analysis of Conditional Associations

This study examines the associations between artificial intelligence (AI) technology innovation and the three dimensions of the global energy trilemma of security, equity, and environmental sustainability. Drawing on a balanced panel of 61 economies from 2000 to 2023, we utilize the stock of AI patent applications to proxy for R&D intensity and employ two‐way fixed effects models to estimate conditional correlations. The results reveal notable asymmetries. AI innovation is positively associated with energy security and environmental sustainability but negatively correlates with energy equity, underscoring a tension between innovation‐driven efficiency and distributional justice. Mechanism analyses suggest that renewable capacity expansion and industrial structure upgrading serve as primary pathways supporting energy security and sustainability, whereas green technology innovation plays a key role in improving energy equity. Furthermore, climate risk acts as a pivotal boundary condition, dampening the innovation dividends for security and sustainability while partially offsetting equity losses. While AI expands the aggregate performance of energy systems, integrated index analyses show it fails to significantly improve the internal coordination among the trilemma's dimensions. The findings underscore the need to integrate innovation‐driven efficiency gains with affordability, inclusiveness, and climate‐resilient infrastructure to ensure that AI supports a balanced and equitable global energy transition.