Artificial intelligence and supply chain stabilization

Global supply chains are hit by external shocks frequently at present; enterprises should increase the resilience of supply chains with the help of artificial intelligence transformation. Therefore, this paper comprehensively analyzes the impact and mechanism of corporate AI development on supply chain stability by using the A-share listed companies in Shanghai and Shenzhen from 2013–2023 as the research samples, and using a high-dimensional fixed effect model. Empirical results show that corporate AI development significantly improves the stability of the supply chain, and this conclusion is still valid after a series of endogeneity treatment and robustness test. Mechanism analysis shows that AI mainly achieves through three aspects: reducing the internal operational risks of the supply chain, increasing the production and operational efficiency of the supply chain, and enhancing the response of the supply chain to market fluctuations. Heterogeneity analysis also shows that there are significant differences in the stabilizing effect of AI, which is more obvious in large enterprises, highly competitive industries, and companies with strong digital transformation, but less so in small enterprises, low-competition industries, and companies with weak digital transformation. Further analysis reveals that AI development not only reduces the adverse impact of the COVID-19 pandemic on supply chain stability, but it also improves corporate sustainability by improving supply chain stability. This study provides the micro level evidence that the practical effect of AI in SCM and provides targeted references for related policy making and corporate AI innovation.