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Generative AI: Opportunities, challenges, and research directions for supply chain resilience

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  • Boone, Tonya
  • Fahimnia, Behnam
  • Ganeshan, Ram
  • Herold, David M.
  • Sanders, Nada R.

Abstract

Generative Artificial Intelligence (GenAI) is emerging as a transformative force in supply chain resilience, offering new ways to enhance decision-making, automate operations, and improve adaptability to disruptions. Unlike traditional AI, which relies on historical data for prediction and optimization, GenAI can generate novel solutions and simulate alternative scenarios in real time. Despite its potential, research on GenAI’s role in supply chain resilience remains limited. This paper explores GenAI applications and possible research questions across key supply chain areas while also addressing challenges such as misinformation, security risks, and governance. As GenAI integrates with existing technologies, its adoption raises critical questions about accountability and systemic dependencies. To ensure responsible implementation, further research is needed to refine oversight mechanisms, establish benchmarks, and develop hybrid decision-making models where AI enhances, rather than replaces, human expertise. These insights provide guidance to managers and policymakers to help make informed decisions about the strategic deployment of GenAI in resilience-oriented supply chains.

Suggested Citation

  • Boone, Tonya & Fahimnia, Behnam & Ganeshan, Ram & Herold, David M. & Sanders, Nada R., 2025. "Generative AI: Opportunities, challenges, and research directions for supply chain resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:transe:v:199:y:2025:i:c:s1366554525001760
    DOI: 10.1016/j.tre.2025.104135
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    2. Sorina Moica & Tripon Lucian & Vassilis Kostopoulos & Adrian Gligor & Noha A. Mostafa, 2025. "GenAI Technology Approach for Sustainable Warehouse Management Operations: A Case Study from the Automative Sector," Sustainability, MDPI, vol. 17(20), pages 1-25, October.
    3. Xuhui Chen & Guanghui Cheng & Yong He, 2025. "Mathematical Modeling and Optimization of Platform Supply Chain in the Digital Era: A Systematic Review," Mathematics, MDPI, vol. 13(17), pages 1-33, September.

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