THE ROLE OF ARTIFICIAL INTELLIGENCE IN ENHANCING SUPPLY CHAIN RESILIENCE

Abstract

Global supply chains are increasingly exposed to disruptions, creating a growing need for enhanced resilience. While artificial intelligence is widely recognized as a key enabler, existing research often conceptualize it as a single construct or focuses on isolated applications. This research addresses this gap by examining how three AI sub fields-machine learning, computer vision, and natural language processing enhance supply chain resilience. Grounded in dynamic capabilities theory, a systematic literature review of 37 peer reviewed articles and conference papers from Scopus and Web of Science was conducted. The findings show that each subfield contributes through distinct yet complementary mechanisms: machine learning supports predictive and adaptive capabilities, computer vision enhances visibility through real-time monitoring, and natural language processing enables environmental awareness and early risk detection. The research synthesizes these insights to clarify the role of AI technologies and their combined contribution to resilience. It offers both theoretical insight and practical guidance for more informed and integrated AI adoption in supply chain management.