AI-enabled decision intelligence for supply chain resilience: The roles of Human–AI collaboration and dynamic capabilities

Abstract

Artificial intelligence (AI) is increasingly embedded in supply chain decision-making, yet its contribution to resilience depends on organizations’ ability to combine AI-generated intelligence with human expertise and adaptive organizational capabilities. This study examines how AI-enabled decision intelligence (AIDI) enhances supply chain resilience through human–AI collaboration and dynamic capabilities. Drawing on dynamic capabilities theory, a research model is developed in which AIDI strengthens human–AI collaboration and dynamic capabilities, while dynamic capabilities enable organizations to anticipate, respond to, and recover from supply chain disruptions. The model further proposes that human–AI collaboration and dynamic capabilities sequentially mediate the relationship between AIDI and supply chain resilience. Using survey data from 294 managers and professionals involved in AI-supported supply chain decision-making in Iranian organizations, the proposed relationships were tested using partial least squares structural equation modeling (PLS-SEM). The results support all hypothesized relationships, showing that AIDI positively influences human–AI collaboration, dynamic capabilities, and supply chain resilience. Dynamic capabilities significantly enhance supply chain resilience and mediate the AIDI–resilience relationship, while human–AI collaboration and dynamic capabilities sequentially mediate this relationship. These findings provide a capability-based explanation of how technological intelligence, human expertise, and organizational adaptability jointly contribute to resilient supply chain outcomes. Keywords: AI-Enabled Decision Intelligence, Human–AI Collaboration, Dynamic Capabilities, Supply Chain Resilience, Artificial Intelligence, Supply Chain Management.