How AI Supports Supply Chain Resilience and Risk Management in Global Logistics Operations

Abstract

Global supply chains are becoming more exposed to disruptions caused by geopolitical instability, transport delays, supplier issues, demand fluctuations, and other external risks. As a result, the growing interest in artificial intelligence (AI) as a way of enhancing supply chain resilience and risk management due to forecasting, monitoring, visibility, and decision-support solutions has gained momentum. This paper discusses AI and its role in supply chain resilience and risk management in global logistics operations, specifically how AI-generated insights are perceived and applied by managers in practice. The qualitative multi-case design is chosen on the basis of the data of 10 organizations that represent various industries and six countries. The semi-structured telephone interviews and written questionnaire responses obtained empirical material, which was analyzed with the help of thematic analysis. The concept of AI in sensing, seizing, and reconfiguring capabilities can be explained using the theoretical framework of Dynamic Capabilities Theory. The results indicate that AI is still predominantly applied in an assistive and not autonomous manner. The best contribution it makes is enhancing visibility, speeding up analysis, and aiding in the prior detection of risks. However, AI alone does not generate proactive resilience. Its value depends on organizational conditions such as data quality, system integration, trust in the management, clear decision rights, supplier relations, and cross-functional coordination. The study provides empirically based insights into how AI is used in real-world logistics operations and reveals that resilience is driven by the interaction between technology, organization, and human judgment.