AI-Powered Supply Chain and Operations Management (SCOM): Capabilities and Challenges

Yuhong Li (), Kedong Chen () and Jiawei Zhang
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Yuhong Li: Old Dominion University
Kedong Chen: Rensselaer Polytechnic Institute
Jiawei Zhang: PRA Group

A chapter in Handbook of Ripple Effects in the Supply Chain, 2025, pp 139-165 from Springer

Abstract: Abstract Artificial intelligence (AI) has emerged as one of the most transformative technologies that revolutionize various sectors including supply chain and operations management (SCOM). AI’s ability to process large datasets, generate predictions, and optimize decision-making processes offers significant operational advantages. However, the integration of AI also introduces challenges, particularly from the aspects of data management and integration, operational and technical challenges in decision-making, and relational and ethical considerations. The enhanced interconnectedness, when combined with AI-powered automation, also significantly amplifies the ripple effect throughout the supply chain when disruptions occur. This chapter explores the capabilities and challenges of AI in SCOM, focusing on data management, decision-making under uncertainties, and buyer-supplier relationship management in the context of resilience and ripple effect. Through a systematic review of the literature, we aim to provide a comprehensive understanding of AI’s role in SCOM and present frameworks for managing the complexities and risks associated with AI-powered operations.

Keywords: Artificial intelligence (AI); Supply chain management; Operations management; Capabilities; Challenges; Ripple effect (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-85508-5_7

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