Drivers of heterogeneous artificial intelligence in corporate energy transition

As global companies pursue sustainable development goals, corporate energy transition (ET) has emerged as a critical focus. Artificial intelligence (AI) plays a pivotal role in this process through its integration capabilities. This study introduces a novel taxonomy distinguishing between production-oriented AI and R&D-oriented AI, and examines their differential impacts on ET using panel data from 4416 A-share listed Chinese firms from 2010 to 2023. The findings reveal that both types of AI facilitate the shift toward clean energy consumption, albeit via distinct mechanisms: production-oriented AI enhances ET by improving energy efficiency, while R&D-oriented AI promotes ET by driving energy technology innovation and improving energy efficiency. Heterogeneity analysis further demonstrates that AI-driven ET is more pronounced among firms with higher environmental attention, more competitive industries, and firms located in non-resource-based cities. This study provides strategic guidance for firms seeking to integrate AI into their ET processes and offers a theoretical foundation for policymakers aiming to accelerate ET initiatives and advance sustainable development goals.