Can artificial intelligence drive new energy firm growth? A new perspective on supply chain configuration optimization

Abstract In the context of the global energy transition, Artificial Intelligence (AI) has emerged as a transformative solution to the information silos and path dependence that characterize traditional energy supply chains. Leveraging data from listed Chinese new energy firms over the period 2007–2024, this study constructs a novel AI index using Large Language Models (LLMs) based on the industry chain view. Crucially, this paper elucidates the mechanisms linking AI to firm growth through the lens of supply chain configuration optimization. The empirical results indicate that AI significantly promotes the growth of new energy firms. Mechanism analyses reveal that AI drives this growth by optimizing supply chain configurations via two distinct pathways: digitalization and diversification. Furthermore, heterogeneity analysis shows that the promotional effect of AI is more pronounced in non-state-owned enterprises (non-SOEs), firms in the growth stage, and those with low financing constraints. Further structural analysis highlights that the application layer of AI serves as the primary driver of firm growth, surpassing the impact of the base and technical layers. Based on these findings, this study offers targeted managerial implications to foster the high-quality development of the new energy industry.