Carbon reduction in the AI era: How does urban digital intelligence transformation facilitate low-carbon development?

Under the backdrop of global climate governance and China's dual carbon objectives, this research explores how urban digital intelligence transformation (DIT) aids low-carbon development. By using city-level panel data from China (2016-2021) and applying the difference-indifferences (DID) approach, we assess the influence of Artificial Intelligence Innovation Development Pilot Zones (AIIDPZs) on carbon emission intensity (CEI). Results demonstrate that AIIDPZs significantly reduce CEI, primarily through technological progress and energy efficiency improvements. Heterogeneity analysis reveals stronger effects in non-resource-based cities, eastern areas, high-GDP cities, and areas with advanced internet infrastructure, while resourcedependent and less-developed regions exhibit limited benefits. Further, public participation and stringent environmental regulations amplify the policy's effectiveness, underscoring the importance of "technology-society-institution" collaborative governance. Notably, AIIDPZs achieve emission reductions without increasing industrial pollution, balancing technological innovation with environmental sustainability. This research offers fresh perspectives on the role of urban DIT in fostering low-carbon development and offers empirical support for policymaking.