Research on Artificial Intelligence-Driven Supply Chain 
Risk Early Warning and Dynamic Response Mechanism

Shuo Liu

doi:10.70711/memf.v3i3.8861

Research on Artificial Intelligence-Driven Supply Chain Risk Early Warning and Dynamic Response Mechanism

Shuo Liu

Abstract

The deepening of globalization and the complex and volatile market environment have made the risks faced by supply chains characterized by rapid transmission, wide impact, and strong uncertainty. The traditional risk management model relying on empirical judgment
can no longer meet the dynamic management and control needs of modern supply chains. This paper focuses on the full-process intelligent
management of supply chain risks and constructs an integrated mechanism of "risk identification-intelligent early warning-dynamic response".
By integrating artificial intelligence technologies such as text mining, Bayesian networks, and machine learning, it achieves accurate capture
of multi-source risk factors, scientific judgment of risk levels, and dynamic matching of response strategies. Taking the bulk commodity supply chain as an empirical scenario, the significant effectiveness of this mechanism in improving risk identification accuracy, shortening early
warning response time, and reducing risk losses is verified, providing technical support and practical reference for enterprises to strengthen
supply chain resilience.

Keywords

Artificial Intelligence; Supply Chain; Risk Early Warning; Dynamic Response Mechanism

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References

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DOI: http://dx.doi.org/10.70711/memf.v3i3.8861

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