Quantity and Quality in Innovation: The Effect of Artificial Intelligence on Carbon Emission Intensity

As a new generation of general technology, artificial intelligence (AI) provides crucial technical support for addressing the dilemmas of carbon emission reduction in cities. This paper selects data from 273 prefecture-level cities in China from 2010 to 2024 to examine the impact of AI on urban carbon emission intensity (CEI) and its mechanism of action. The results show that AI is negatively associated with CEI. AI lowers the threshold for scientific research, expands the scale of patent output, and generates groundbreaking high value patents, which indicates that both the quantity and quality of innovation are key paths to facilitating urban carbon emission reduction. The results of the heterogeneity test indicate that the carbon reduction effects of AI exhibit stratified characteristics, with cities southeast of the Hu Line, northern industrial cities, and resource-based cities demonstrating more prominent emission reduction effects. Accordingly, policy recommendations such as establishing regional digital low-carbon layouts and allocating policy resources based on resource endowments are put forward. The research provides a theoretical basis for reducing carbon emissions and achieving sustainable development goals relying on AI.