Artificial intelligence (AI) is the core technology of digital economy, which leads the transition to a sustainable economic growth approach under the Chinese-style environmentally decentralized system. In this paper, we first measured the green total factor productivity (GTFP) of 30 Chinese provinces from 2011 to 2020 using the super-efficiency slacks-based measure (SBM) model, analyzed the mechanism of the effect of AI on GTFP under the environmental decentralization regime, and secondly, empirically investigated the spatial evolution characteristics and the constraining effect of the impact of AI on GTFP using the spatial Durbin model (SDM) and the threshold regression model. The findings reveal: a U shape of the correlation of AI with GTFP; environmental decentralization acts as a positive moderator linking AI and GTFP; the Moran index demonstrates the spatial correlation of GTFP; under the constraint of technological innovation and regional absorptive capacity as threshold variables, the effect of AI over GTFP is U-shaped. This paper provides a useful reference for China to accelerate the formation of a digital-driven green economy development model.

The effective enhancement of green total factor productivity (GTFP) through macro-regulatory tools—environmental decentralization and environmental regulation and thus the promotion of high-quality and sustainable economic development—is a hot topic of current research. However, many studies have focused on how environmental decentralization or environmental regulation affects green total factor productivity, lacking attention to the relationships and impact paths among the three. To clarify the mechanisms of action of the three effects, this paper measures the GTFP of 30 Chinese provinces and cities from 2010 to 2020 through the Super-SBM model. The mediating effect of environmental regulation between environmental decentralization and GTFP is examined. Firstly, the study findings suggested that environmental decentralization is significantly negatively related to GTFP, while different environmental regulations are all significantly positively related to GTFP. Secondly, environmental decentralization suppresses GTFP in eastern China, which has a non-significant effect in central China. It has a catalytic effect on GTFP in western China. Finally, environmental decentralization can enhance GTFP by promoting public participation in environmental regulation. The findings of this paper have implications for adjusting environmental decentralization, environmental regulation policies, and formulating green economic transition and development strategies.