Abstract The continuous rise in carbon emissions intensifies global climate warming and creates a serious challenge for sustainable urban development. Artificial intelligence (AI) has emerged as a key technology that supports energy management, industrial upgrading, and urban governance, providing new opportunities for advancing low-carbon urban development. Using panel data from Chinese cities for the period 2008 to 2022, this study applies a two-way fixed effects model to evaluate the influence of AI on urban carbon emission intensity (CI) as well as the underlying mechanism. The results show that AI significantly lowers urban CI and promotes low-carbon transformation (LCT). This conclusion remains valid across multiple robustness checks. Mechanism analysis indicates that AI reduces emissions by stimulating green technological innovation and facilitating an upgrade of the industrial structure. Heterogeneity analysis reveals stronger emission reduction effects in large cities, southern cities, resource-based cities, and low-industrial-level cities. This study offers new empirical evidence on the role of AI in urban LCT and provides analytical support for cities seeking to advance green development and strengthen technological momentum.
Zhai et al. (Thu,) studied this question.