JOURNAL ARTICLE

How Generative AI Improves Supply Chain Management.

  • Published In: Harvard Business Review, 2025, v. 103, n. 1. P. 86 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Menache, Ishai; Pathuri, Jeevan; Simchi-Levi, David; Linton, Tom 3 of 3

Abstract

The article focuses on the application of large language models (LLMs), a type of generative AI, to optimize supply chain management by automating data discovery, insight generation, and scenario analysis. Drawing on Microsoft's experience deploying an LLM-based system for managing hardware supply to its global data centers, it highlights how LLMs reduce decision-making time from days to minutes and enhance planners' productivity by enabling direct interaction with supply chain tools without reliance on data scientists. The article also discusses practical benefits such as answering complex what-if questions, updating plans in response to disruptions, and enforcing contracts, while noting challenges including the need for precise user training, verification of outputs, and evolving workforce roles. It concludes that despite these obstacles, LLM technology has the potential to transform supply chain management by increasing efficiency, resilience, and collaboration across business functions.

Additional Information

  • Source:Harvard Business Review. 2025/01, Vol. 103, Issue 1, p86
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0017-8012
  • Accession Number:181526550
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