Resilient by Design: Exploring the Social Abilities and Actor-Network Roles of Artificial Intelligence in Supply Chain Management - Lansiné Condé; Christopher Münch (Journal of Business Logistics, 2025)
Despite its substantial potential to enhance supply chain resilience (SCRes), artificial intelligence (AI) remains underexplored as an autonomous entity within supply chains (SCs), particularly in terms of its social capabilities and interactions within sociotechnical systems. Current literature has yet to address how AI can transform SC collaboration and network stability from a forward-looking perspective, creating a critical research gap. This study aims to address this gap by examining the social abilities introduced by AI and their implications for SCRes. The exploratory research design of this study is grounded in the actor-network theory and the Gioia method and includes 23 semi-structured interviews with experts. The findings reveal that AI actively influences decision-making processes, power dynamics, and trust among SC actors. By interacting with both human and non-human actors, AI emerges as a critical tool for redefining collaboration and network stability. While AI-driven SCs can enhance organizations' efficiency and adaptability, they also introduce challenges, including ethical considerations, responsibility allocation, and unintended consequences of algorithmic decision-making. This study contributes to the discourse on the embeddedness of AI in SCs by offering theoretical insights into its sociotechnical integration and managerial implications for its governance. Understanding AI as an active tool is crucial for designing resilient and future-proof SCs. The findings emphasize the need for organizations to develop strategies that balance the benefits and risks of AI, ensuring its responsible and effective deployment across SC networks.
Keywords: 650; actor–network theory; artificial intelligence; autonomous actor; social abilities; supply chain resilience