Randomized trial investigates AI's impact on supply chain resilience, highlighting asset efficiency gains.
In the context of economic deglobalization and intensified geopolitical conflicts, supply chain stability and resilience have become critical strategic imperatives for corporate survival and development. Conventional supply chain management paradigms are increasingly inadequate in addressing the growing risks of disruptions and a complex, volatile market environment. Artificial Intelligence (AI), as a core driver of digital transformation, offers a revolutionary tool for redefining risk management paradigms and enhancing the efficiency of dynamic resource allocation, leveraging its robust capabilities in data processing, intelligent forecasting, and autonomous decision-making. However, large-sample empirical evidence on the intrinsic mechanisms through which AI technologies empower corporate supply chain resilience remains scarce. To bridge this gap, this study adopts an operational efficiency perspective, utilizing the Asset Turnover Ratio (ATO) as a key proxy for supply chain resilience. We construct an econometric model and conduct regression analysis on a large sample of Chinese A-share listed companies from 2010 to 2022. Our findings robustly reveal that the adoption of AI (β = 0.031, p < 0.01) significantly improves asset turnover efficiency after controlling for firm-level characteristics, industry, and year fixed effects. The reversal of the AI coefficient from negative to positive after accounting for confounding factors powerfully demonstrates the existence of omitted variable bias and underscores the true positive impact of AI. This study demonstrates that AI technology effectively strengthens supply chain resilience by optimizing operational processes and enhancing risk response capabilities. Our research provides a novel theoretical perspective and robust empirical evidence on the value-creation mechanism of AI in supply chain management, offering important practical implications for firms seeking to leverage digital technologies to bolster their risk resistance in an era of deglobalization.
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Yiqi Liu (2026) studied this question.
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