Artificial intelligence facilitates urban green transition in the Yangtze River Delta urban agglomeration

Abstract

Abstract This study examines the pivotal role of artificial intelligence (AI) in advancing the urban green transition (UGT), with a particular focus on the Yangtze River Delta (YRD) Urban Agglomeration. Drawing on panel data from 40 cities in the YRD between 2012 and 2024, the research utilizes benchmark regression, non-linear effect analysis, and spatial econometric models to investigate how AI influences UGT through production, consumption, and agglomeration channels. The main findings are as follows: (1) AI exerts a significant positive effect on UGT. (2) UGT exhibits strong spatial autocorrelation, whereas AI’s impact is characterized by robust local promotion but limited spatial spillover. (3) The influence of AI displays marked heterogeneity, varying by urban hierarchy, geographic location, resource endowment, and levels of institutional and market development. (4) The effects of AI on UGT are mediated by fixed capital stock, industrial structure upgrading, and consumption levels. Additionally, digital infrastructure, green consumption awareness, and digital industry agglomeration serve as moderating factors. AI’s influence also exhibits nonlinear diminishing marginal effects at specific thresholds in productive services and agricultural agglomeration. These results highlight the multifaceted mechanisms through which AI drives sustainable urban development and offer policy implications for fostering green transformation in metropolitan regions.