Artificial Intelligence, energy transitions, and the pathway to net-zero carbon emissions in OECD Countries

Existing research highlights that artificial intelligence 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. This study also examines whether artificial intelligence can help to form an environmental Kuznets curve (EKC) in OECD countries. To achieve this objective, we design a novel analytical framework that examines the influence of artificial intelligence and nuclear energy on the dynamics of the Environmental Kuznets Curve (EKC). Empirical analysis indicates that nuclear energy contributes to reduced carbon emissions. Additionally, artificial intelligence has a negligible impact on CO ₂ emissions. Furthermore, there is unidirectional causality between artificial intelligence and CO ₂ emissions, as well as between nuclear energy and CO ₂ emissions. To summarize, nuclear energy consumption contributes to the formation of EKC, whereas artificial intelligence does not appear to have a similar effect. Based on these results, some economic policy implications are discussed.