Moving towards the pathway to net-zero carbon emissions through nuclear energy in OECD countries: the moderating role of artificial intelligence

Existing research highlights that artificial intelligence (AI) can enhance energy security and support the pursuit of net-zero carbon emission goals. Yet scholarly attention to its role in shaping the relationship between nuclear energy use and carbon dioxide emissions remains limited. This study addresses that gap by offering one of the earliest empirical investigations linking artificial intelligence, nuclear energy consumption, and CO₂ emissions across 17 Organization for Economic Co-operation and Development (OECD) countries from 1994 to 2020. The Common Correlated Effects Mean Group (CCE-MG) estimator is used for regression analysis. The empirical analysis indicates that nuclear energy consumption does not have a statistically significant direct effect on CO₂ emissions; however, its indirect impact on carbon emissions through AI is significant and negative, helping to reduce them. Hence, AI plays a significant moderating role in the relationship between nuclear energy and carbon emissions in OECD countries. Country-specific Mean Group estimates reveal substantial cross-country heterogeneity in the long-run effects of income, artificial intelligence, and nuclear energy consumption on carbon emissions, underscoring that panel-level results mask important national structural differences. Based on these results, some economic policy implications are discussed.