Stoking the flames of change: AI-driven energy transition in urban China through nonlinear dynamics and spatial spillover effect

Global warming and energy security challenges have intensified globally, compelling nations to pursue sustainable energy transition pathways. Artificial intelligence (AI) plays a pivotal role in addressing complex systemic challenges and enhancing industrial efficiency, and is widely recognized as a critical catalyst for efficiency transformation and economic advancement. This study employs panel data from 282 prefecture-level cities in China, spanning the period 2007–2021, to empirically examine the relationship between AI and energy transition. The key findings are that: AI significantly promotes energy transition development, and this effect is mediated through its role in driving digital upgrades and green transformation of industrial chains. The association between AI and energy transition exhibits nonlinearity: at low levels of AI development, AI exerts the strongest driving effect on the Energy Transition Index; at moderate AI levels, this driving effect weakens; and at high AI levels, the driving effect strengthens again, presenting a distinct U-shaped pattern. AI exerts a significant positive spatial spillover effect on energy transition, indicating that technological diffusion generates favorable impacts on neighboring regions. Regional heterogeneity analysis reveals marked disparities in AI's influence on energy transition across China, exhibiting a gradient effect characterized by “strengthening in eastern regions, stabilization in central territories, and differentiation in western regions”. This research provides valuable guidance for policymakers by highlighting AI's pivotal role in advancing energy transformation. • Reveal the nonlinear impact characteristics of AI on energy transition. • Analyze the impact mechanism of AI on energy transition. • Identifying Regional Heterogeneity in AI Development influencing the energy transition Using City-Level samples.