Artificial Intelligence and Urban Green Productivity in China: The Role of Green Computing Capacity and Transmission Channels

Artificial intelligence (AI) is reshaping production systems, innovation processes, and environmental governance, yet its green productivity effects remain ambiguous because AI may both improve efficiency and increase computing-related energy demand. Using panel data for 287 Chinese prefecture-level and above cities from 2005 to 2023, this study examines the relationship between AI technological development and urban green productivity, through which technological transmission channels this effect may operate, and under what boundary conditions it becomes stronger. Green productivity is measured by an undesirable output Super-SBM model, AI by city-level AI patent grants, and green computing capacity by a composite index covering computing infrastructure, green energy support, low-carbon operating efficiency, and computing–network coordination. The results show a robust positive association between AI technological development and urban green productivity, and this conclusion remains robust after alternative measurements, sample restrictions, winsorization, lagged regressors, and Bartik instrumental variable estimations. Green computing capacity is associated with a stronger AI–green productivity relationship. Mechanism-consistent evidence suggests three channels: green knowledge recombination, intelligent regulation of carbon energy flows, and green value-chain coordination. Heterogeneity analyses reveal stronger effects in cities with higher green computing capacity, stronger industrial foundations and weaker resource-environmental constraints. These findings provide city-level evidence for coordinating AI development with green computing infrastructure and low-carbon governance.