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OM Forum—Supply Chain Management in the AI Era: A Vision Statement from the Operations Management Community

Author

Listed:
  • Maxime C. Cohen

    (Desautels Faculty of Management, McGill University, Montreal, Quebec H3A 0G4, Canada)

  • Tinglong Dai

    (Carey Business School, Johns Hopkins University, Baltimore, Maryland 21202)

  • Georgia Perakis

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Narendra Agrawal

    (Santa Clara University, Santa Clara, California 95053)

  • Gad Allon

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Robert N. Boute

    (Vlerick Business School, 1210 Brussels, Belgium; and KU Leuven, 3000 Leuven, Belgium)

  • Gérard P. Cachon

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Zhe Chen

    (JD.com, Beijing 101111, China)

  • Morris Cohen

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Rares Cristian

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Vinayak Deshpande

    (University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599)

  • Francis de Véricourt

    (European School of Management and Technology Berlin, 10178 Berlin, Germany)

  • Jan C. Fransoo

    (Tilburg University, 5037 AB Tilburg, Netherlands)

  • Joren Gijsbrechts

    (Ramon Llull University (Esade), 08034 Barcelona, Spain)

  • Pavithra Harsha

    (IBM, Armonk, New York 10504)

  • Ming Hu

    (University of Toronto, Toronto, Ontario M5S 1A1, Canada)

  • Pınar Keskinocak

    (Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Caleb Kwon

    (University of Texas at Austin, Austin, Texas 78712)

  • Hau Lee

    (Stanford University, Stanford, California 94305)

  • Sheng Liu

    (University of Toronto, Toronto, Ontario M5S 1A1, Canada)

  • Konstantina Mellou

    (Microsoft, Redmond, Washington 98052)

  • Ishai Menache

    (Microsoft, Redmond, Washington 98052)

  • Jason Miller

    (Michigan State University, East Lansing, Michigan 48824)

  • Serguei Netessine

    (University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Tava Lennon Olsen

    (University of Melbourne, Parkville, Victoria 3010, Australia)

  • Jeevan Pathuri

    (Microsoft, Redmond, Washington 98052)

  • Robert Peels

    (Flostock, 5251 CC Vlijmen, Netherlands)

  • Yongzhi Qi

    (JD.com, Beijing 101111, China)

  • Ananth Raman

    (Harvard University, Cambridge, Massachusetts 02138)

  • Anne Robinson

    (Robinson Insights, Redhill, Surrey RH2 9AR, Great Britain)

  • Zuo-Jun Max Shen

    (The University of Hong Kong, Hong Kong)

  • Masha Shunko

    (University of Washington, Seattle, Washington 98195)

  • David Simchi-Levi

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Hannah Smalley

    (Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Jing-Sheng Song

    (Duke University, Durham, North Carolina 27708)

  • Jayashankar M. Swaminathan

    (University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599)

  • Christopher Tang

    (University of California, Los Angeles, Los Angeles, California 90095)

  • Sridhar Tayur

    (Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

  • Maxi Udenio

    (KU Leuven, 3000 Leuven, Belgium)

  • Jan Van Mieghem

    (Northwestern University, Evanston, Illinois 60208)

  • Yuqian Xu

    (University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599)

  • Dennis Zhang

    (Washington University in St. Louis, St. Louis, Missouri 63130)

Abstract

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.

Suggested Citation

  • Maxime C. Cohen & Tinglong Dai & Georgia Perakis & Narendra Agrawal & Gad Allon & Robert N. Boute & Gérard P. Cachon & Zhe Chen & Morris Cohen & Rares Cristian & Vinayak Deshpande & Francis de Véricou, 2026. "OM Forum—Supply Chain Management in the AI Era: A Vision Statement from the Operations Management Community," Manufacturing & Service Operations Management, INFORMS, vol. 28(3), pages 687-705, May.
    • Handle: RePEc:inm:ormsom:v:28:y:2026:i:3:p:687-705
    DOI: 10.1287/msom.2025.1065
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