Artificial Intelligence, and Environmental Performance: The Moderating Role of Digital Economy and Energy Transition for Sustainable Development

ABSTRACT Amid escalating climate change pressures and growing global commitments to the Sustainable Development Goals (SDGs), digital technologies are increasingly recognized as key enablers of sustainable and low‐carbon development. Artificial intelligence (AI), in particular, has the potential to transform energy systems by improving energy efficiency, optimizing resource allocation, and accelerating the deployment of renewable energy. However, empirical evidence remains limited regarding how AI interacts with the digital economy (DE) and energy transition (ET) to shape environmental outcomes. This study addresses this gap by examining the direct and indirect effects of AI on environmental performance and pollution dynamics across G‐20 economies over the period 2010–2020. Using Hayes' (2017) PROCESS moderated‐mediation framework, we investigate the mediating role of energy transition and the moderating role of the digital economy in the AI environment nexus. Environmental outcomes are captured using the Environmental Pollution Index and related pollution indicators, while research and development, economic growth, and population size are included as control variables. The results show that when considered in isolation, AI does not consistently improve environmental quality. Instead, its sustainability benefits emerge indirectly through an accelerated transition toward cleaner and renewable energy systems. Moreover, the digital economy significantly strengthens the positive influence of AI on energy transition, thereby amplifying improvements in environmental performance and reducing pollution levels. The study underscores the importance of sustained investments in AI infrastructure, digital transformation, renewable energy systems, and innovation‐oriented policies to support long‐term environmental sustainability and the achievement of the SDGs.