OM Forum—Supply Chain Management in the AI Era: A Vision Statement from the Operations Management Community
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.
Authors
- Morris A. Cohen (ORCID: https://orcid.org/0000-0002-8644-8820)
- Georgia Perakis (ORCID: https://orcid.org/0000-0002-0888-9030)
- Gad Allon (ORCID: https://orcid.org/0000-0002-4815-6667)
- Jayashankar M. Swaminathan (ORCID: https://orcid.org/0000-0002-1224-5422)
- Maxime C. Cohen (ORCID: https://orcid.org/0000-0002-2474-3875)
- Masha Shunko (ORCID: https://orcid.org/0000-0003-4864-0798)
- Robert Peels (ORCID: https://orcid.org/0000-0001-5242-0320)
- Gérard P. Cachon (ORCID: https://orcid.org/0000-0002-7046-8835)
- Jeevan Pathuri
- Francis de Véricourt (ORCID: https://orcid.org/0000-0003-2832-0738)
- Hannah K. Smalley (ORCID: https://orcid.org/0000-0002-0275-1807)
- Caleb Kwon
- Konstantina Mellou (ORCID: https://orcid.org/0000-0001-9245-8956)
- Ishai Menache (ORCID: https://orcid.org/0000-0002-2540-236X)
- Tava Lennon Olsen (ORCID: https://orcid.org/0000-0002-5477-6280)
- Joren Gijsbrechts (ORCID: https://orcid.org/0000-0002-0846-6855)
- Yongzhi Qi (ORCID: https://orcid.org/0009-0004-1434-379X)
- Maximiliano Udenio (ORCID: https://orcid.org/0000-0002-2971-2795)
- Christopher S. Tang (ORCID: https://orcid.org/0000-0001-9597-7620)
- Hau L. Lee (ORCID: https://orcid.org/0000-0003-2910-6696)
- Rares Cristian
- Dennis Zhang (ORCID: https://orcid.org/0000-0002-4544-775X)
- Ming Hu (ORCID: https://orcid.org/0000-0003-0295-226X)
- Vinayak Deshpande (ORCID: https://orcid.org/0000-0002-6681-028X)
- Pavithra Harsha
- Ananth Raman
- Anne G. Robinson
- Serguei Netessine
- Jason W. Miller
- Sheng Liu
- Zuo-Jun Max Shen
- Yuqian Xu
- Jan Van Mieghem
- Zhe Chen
- Narendra Agrawal
- Jing-Sheng Song
- Sridhar Tayur
- David Simchi-Levi
- Robert N. Boute
- Jan C. Fransoo
- Pınar Keskinocak
- Tinglong Dai
Institutions
- Northwestern University (US)
- University of North Carolina at Chapel Hill (US)
- Microsoft (United States) (US)
- Georgia Institute of Technology (US)
- IBM (United States) (US)
- Johns Hopkins University (US)
- University of California, Los Angeles (US)
- Santa Clara University (US)
- The University of Melbourne (AU)
- Duke University (US)
- University of Toronto (CA)
- Tilburg University (NL)
- University of Washington (US)
- Washington University in St. Louis (US)
- East Surrey Hospital (GB)
- Harvard University Press (US)
- Jingdong (China) (CN)
- Vlerick Business School (BE)
- McGill University (CA)
- Universitat Ramon Llull (ES)
- Massachusetts Institute of Technology (US)
- Carnegie Mellon University (US)
- University of Pennsylvania (US)
- The University of Texas at Austin (US)
- Michigan State University (US)
- University of Hong Kong (HK)
- European School of Management and Technology (DE)
- Stanford University (US)
- KU Leuven (BE)
Publication Details
- Journal
- Manufacturing & Service Operations Management
- Published
- 2026-03-26
- DOI
- https://doi.org/10.1287/msom.2025.1065
- Primary Topic
- Supply Chain Resilience and Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00