Abstract: Artificial intelligence, as a new generation of general-purpose technology, has been applied in various fields such as intelligent manufacturing, supply chain management, and risk warning, continuously expanding its application scenarios. It promotes the optimization and reorganization of production factors, reshapes the industrial division of labor pattern, and enhances the efficiency of resource allocation. Its innovative development has become an important driving force to overcome the resilience dilemma of the industrial chain and is also becoming the core engine for the new round of technological revolution and industrial transformation. Based on the panel data of 281 cities in China from 2011 to 2023, a dual machine learning model was used to systematically examine the impact of artificial intelligence on the resilience of industrial chains. The findings are as follows: First, AI promotes industrial chain resilience. This effect is more pronounced in cities with digital ecological advantages, such as those possessing data trading platforms, high levels of financial technology development, and well-established digital infrastructure, as well as in non-resource-based and non-old industrial base cities. Second, AI enhances the resilience of industrial chains through deepening industrial integration. Third, the impact of artificial intelligence on the resilience of industrial chains has a nonlinear threshold characteristic. The effect of technological investment is a single threshold effect, and it can only activate its enabling role by crossing the critical value; digital talents show a dual threshold, and their reserves need to successively break through two critical points to enable the gradual and stepwise rise of the promoting effect of artificial intelligence. Therefore, it is necessary to further strengthen the deep integration of artificial intelligence and industrial chains, consolidate the foundation for resilience improvement; build a comprehensive supporting policy system for industrial integration, form a coordinated promotion path; strengthen the threshold management of key supporting elements, implement phased investment and cultivation plans, and especially increase investment in common technology research and development platforms for artificial intelligence, computing infrastructure, and other fields with public goods attributes.

Key words: artificial intelligence, industrial integration, industrial chain resilience, double machine learning, threshold effect