TY - JOUR
T1 - OM Forum—Supply Chain Management in the AI Era
T2 - A Vision Statement from the Operations Management Community
AU - Cohen, Maxime C.
AU - Dai, Tinglong
AU - Perakis, Georgia
AU - Agrawal, Narendra
AU - Allon, Gad
AU - Boute, Robert N.
AU - Cachon, Gérard P.
AU - Chen, Zhe
AU - Cohen, Morris
AU - Cristian, Rares
AU - Deshpande, Vinayak
AU - de Véricourt, Francis
AU - Fransoo, Jan C.
AU - Gijsbrechts, Joren
AU - Harsha, Pavithra
AU - Hu, Ming
AU - Keskinocak, Pınar
AU - Kwon, Caleb
AU - Lee, Hau
AU - Liu, Sheng
AU - Mellou, Konstantina
AU - Menache, Ishai
AU - Miller, Jason
AU - Netessine, Serguei
AU - Olsen, Tava Lennon
AU - Pathuri, Jeevan
AU - Peels, Robert
AU - Qi, Yongzhi
AU - Raman, Ananth
AU - Robinson, Anne
AU - Shen, Zuo-Jun Max
AU - Shunko, Masha
AU - Simchi-Levi, David
AU - Smalley, Hannah
AU - Song, Jing-Sheng
AU - Swaminathan, Jayashankar M.
AU - Tang, Christopher
AU - Tayur, Sridhar
AU - Udenio, Maxi
AU - Van Mieghem, Jan A.
AU - Xu, Yuqian
AU - Zhang, Dennis J.
N1 - Publisher Copyright:
© 2026 INFORMS.
PY - 2026/5/1
Y1 - 2026/5/1
N2 - Problem definition: Artificial intelligence (AI) is rapidly transforming the research and practice of supply chain management. Yet its impact depends on how effectively it is integrated with the theories, methods, and fundamental principles of operations management (OM), which must also evolve to account for the informational, incentive, and institutional changes brought by AI. The OM community has an important role and responsibility to lead in shaping not only how AI transforms supply chains but also how the supply chains that enable AI are designed to be sustainable, resilient, and equitable. Methodology/results: This vision statement organizes the discussion around five layers of the interaction between AI and supply chain management: intelligence, execution, strategy, human, and infrastructure. It synthesizes recent research and industry practice to show how AI enhances forecasting, planning, decision making, risk management, and human–machine collaboration and also examines the supply chains that support AI. Finally, it highlights persistent challenges in data quality, model integration, governance, and workforce adaptation. Managerial implications: Realizing AI’s promise in supply chain management requires reliable data and infrastructure, integration of learning and optimization, transparent and explainable decision systems, and a long-term commitment to human–AI collaboration. Together, these elements form the foundation for resilient, adaptive, and trustworthy supply chains in the AI era.
AB - Problem definition: Artificial intelligence (AI) is rapidly transforming the research and practice of supply chain management. Yet its impact depends on how effectively it is integrated with the theories, methods, and fundamental principles of operations management (OM), which must also evolve to account for the informational, incentive, and institutional changes brought by AI. The OM community has an important role and responsibility to lead in shaping not only how AI transforms supply chains but also how the supply chains that enable AI are designed to be sustainable, resilient, and equitable. Methodology/results: This vision statement organizes the discussion around five layers of the interaction between AI and supply chain management: intelligence, execution, strategy, human, and infrastructure. It synthesizes recent research and industry practice to show how AI enhances forecasting, planning, decision making, risk management, and human–machine collaboration and also examines the supply chains that support AI. Finally, it highlights persistent challenges in data quality, model integration, governance, and workforce adaptation. Managerial implications: Realizing AI’s promise in supply chain management requires reliable data and infrastructure, integration of learning and optimization, transparent and explainable decision systems, and a long-term commitment to human–AI collaboration. Together, these elements form the foundation for resilient, adaptive, and trustworthy supply chains in the AI era.
KW - artificial intelligence
KW - human–AI collaboration
KW - machine learning
KW - operations management
KW - optimization
KW - resilience
KW - supply chain management
UR - https://www.scopus.com/pages/publications/105041364660
U2 - 10.1287/msom.2025.1065
DO - 10.1287/msom.2025.1065
M3 - Article
SN - 1523-4614
VL - 28
SP - 687
EP - 705
JO - Manufacturing & Service Operations Management
JF - Manufacturing & Service Operations Management
IS - 3
ER -