Supply Chain Resilience Through Artificial Intelligence: Predictive And Adaptive Approaches In Risk Management

The purpose of this study is to examine the role of artificial intelligence (AI) in enhancing supply chain resilience through predictive and adaptive approaches in risk management. This research is applied and quantitative in nature, utilizing structural equation modeling (PLS-SEM). Data were collected from ۳۰۰ supply chain managers and specialists across various industries in Iran, and analyses were performed using Smart PLS ۴ software. The results revealed that AI’s predictive and adaptive capabilities have a significant positive impact on risk management and supply chain resilience. Moreover, risk management partially mediates the relationship between AI and resilience. Findings indicate that adaptive AI capabilities exert the strongest overall effect on supply chain resilience (β = ۰.۵۴). The simultaneous use of predictive and adaptive approaches can transform organizations into intelligent, dynamic, and resilient supply chains. This study provides empirical and practical evidence for managers to design and implement proactive and adaptive decision-making processes in supply chains using AI technologies.

کلیدواژه ها:

Artificial Intelligence ، Supply Chain Resilience ، Risk Management ، Predictive Capability ، Adaptive Capability ، PLS-SEM