The present study aims to investigate the influence of artificial intelligence (AI) on industrial green development (IGD) in China. After constructing comprehensive assessment index systems for AI and IGD, the index values for AI and IGD across 30 provinces in China from 2011 to 2021 were calculated by methods of Intuitive Fuzzy Analytic Hierarchy Process (IFAHP) and Dynamic Grey Relational Analysis (DGRA). Then, based on the PROCESS macro, the direct and indirect effects of AI on IGD, the mediating role of industrial structure upgrading on the relationship between AI and IGD, and the moderating effect of industrial agglomeration on the link between industrial structure upgrading and IGD were detected using the Hierarchical Regression Analysis method. The indirect effect of AI on IGD via industrial structure upgrading with the moderation effect of industrial agglomeration was also tested using bootstrap analysis and the Johnson-Neyman technique. The empirical results show that 1) AI could exert significant direct and indirect influence on IGD; 2) industrial structure upgrading could partially mediate the relationship between AI and IGD; and 3) industrial agglomeration could significantly moderate the effect of industrial structure upgrading on IGD. Specifically, when industrial agglomeration is at a low level, industrial agglomeration strengthens the positive influence of industrial structure upgrading on IGD. However, once the level of industrial agglomeration exceeds a certain threshold, it weakens the impact of industrial structure upgrading on IGD. These findings provide new insights into the influence of AI on IGD and may shed light on future decisions related to industrial green transformation.