Digital Economy-Driven AI Innovation and Supply Chain Resilience: From Technological Capability to Risk-Buffering Capacity

Frequent disruptions to global supply chains have made the conversion of AI innovation into firms’ capacity to withstand and respond to supply chain risks an important issue in the digital economy. Using 36,658 firm-year observations for Chinese listed companies from 2007 to 2025, this study examines the effect of AI innovation on supply chain resilience. The baseline specification includes firm-level controls, firm fixed effects, year fixed effects, and province-by-year fixed effects, while further analyses examine the role of cost stickiness and the moderating effects of the digital economy, the market-based allocation of data elements, and economic policy uncertainty. AI innovation has a significantly positive coefficient of 0.5084. This effect is concentrated among manufacturing firms and is stronger for state-owned and non-loss-making firms. AI innovation improves supply chain resilience by reducing cost stickiness; city-level digital economy development and the market-based allocation of data elements strengthen this effect, whereas economic policy uncertainty weakens it. By explaining how AI-related technological capability translates into supply chain risk-buffering capacity, this study provides evidence for firms seeking to deepen AI applications and for governments improving digital infrastructure, data trading institutions, and the policy environment.