Artificial intelligence and green total factor energy efficiency: evidence from non-linear models

This research examines how Artificial Intelligence (AI) affects Green Total Factor Energy Efficiency (GTFEE) in China, emphasizing regional differences and their impacts on sustainable urban growth. By introducing a non-linear analytical approach, the study offers fresh insights into how AI influences GTFEE in diverse regions and urban areas. It provides valuable information for policymakers and urban planners by exploring spatial GTFEE variations and the influence of industrial structure as a moderating factor. Key findings include: (1) AI impacts GTFEE in a non-linear pattern, showing initial increases, subsequent declines, and eventual growth; (2) the Yangtze River Economic Belt and specific urban clusters experience the most significant effects; (3) while industrial structure enhances AI’s marginal effect on GTFEE, this influence weakens in some areas; (4) regional development stages play a crucial role in shaping the AI-GTFEE relationship. This research contributes to understanding AI and GTFEE dynamics, broadens existing literature on regional energy efficiency, and provides a detailed framework to enhance urban sustainability.