Nonlinear impact of artificial intelligence on clean energy transformation: The asymmetric role of heterogeneous environment regulations.

Abstract

During the critical period of the global clean energy transformation (CET), the mechanism by which artificial intelligence (AI) and environmental regulations jointly drive the CET is still unclear. Using panel data from Chinese prefecture-level cities spanning 2006 to 2022, and linear interpolation is used to process some missing data. This study employs the two-way fixed effects model and Spatial Durbin Model to examine the impact of AI on CET and spatial spillover effects, as well as the role of heterogeneous environmental regulations. The findings reveal that a "U-shaped" relationship exists between AI and CET, which is more significant in central and northeastern regions, large cities, non-resource-based and non-low-carbon pilot cities in China, further verifying Porter's hypothesis. Importantly, there is an asymmetric nonlinear moderating effect. Formal environmental regulation (FER) has a positive moderating effect. Initially, it exacerbates the weak inhibition of AI due to cost effect, but in maturity, it strengthens the promotion of AI by technical synergy. However, informal environmental regulation (IER) is opposite. It is insignificant initially due to flexible constraints, but in maturity, the positive effect of AI is weakened due to the false compliance. In addition, AI in neighboring areas has a positive spillover effect on local CET. These findings provide key decision-making basis for the government to maximize the role of AI in enabling CET by formulating differentiated environmental regulation policies in stages.