AI-oriented policy and urban ecological quality: Evidence from China's national AI innovation and development pilot zones

Artificial intelligence (AI) is increasingly embedded in urban industrial upgrading and policy experimentation, yet its implications for urban ecological conditions remain unclear. This study examines the impact of China's National New Generation Artificial Intelligence Innovation and Development Pilot Zone (AI-IDPZ) policy on urban ecological environment quality (EEQ). Using panel data for 290 Chinese cities from 2008 to 2022 and a staggered difference-in-differences approach, we estimate the average treatment effect of AI-IDPZ implementation and explore its mechanisms, heterogeneity, moderating conditions, and spatial spillovers. The results show that AI-IDPZ implementation significantly reduces urban EEQ in the early stage of policy implementation. Mechanism tests suggest that this adverse effect is associated with infrastructure expansion, rising electricity consumption, and increased water use. The negative effect is stronger in southern and resource-based cities. We also find that green technological innovation, green finance, digital talent supply, green industrial development, and green data-centre construction mitigate the ecological costs of AI-oriented development. In addition, AI-IDPZ implementation generates significant negative spatial spillovers within approximately 150 km of pilot cities. These findings imply that AI-led urban development does not automatically improve ecological outcomes and may intensify short-term resource and environmental pressures without complementary green governance. The study contributes to urban sustainability research by showing that the ecological consequences of AI policy are contingent on local development conditions, green governance capacity, and cross-city coordination.