AI-Powered Solutions for Urban Carbon Emission Challenges: Evidence from China
Description
This study investigates the impact of artificial intelligenc on urban carbon emission efficienc, addressing the limited empirical evidence on the environmental effects of AI in the existing literature. Using panel data from Chinese cities covering the period 2011–2023, we employ a fixed-effects model to examine the relationship between AI development and carbon emission efficiency. Our analysis reveals that AI significantly improves urban carbon emission efficiency. Mechanism analyses further show that AI promotes CE by stimulating green technological innovation, upgrading industrial structure, and accelerating the development of the digital economy. In addition, the effect is stronger in non-old industrial cities, resource-based cities, and regions with stronger intellectual property protection and higher human capital. These findings provide new insights into the environmental implications of AI and offer important policy implications for promoting low-carbon transition and sustainable urban development.