AI Applications in Supply Chain Management: A Survey

The advent of Industry 4.0 and the integration of Artificial Intelligence (AI) is transforming supply chain management (SCM), improving efficiency, resilience and strategic decision-making capabilities. This research study provides a comprehensive overview of AI applications in key SCM processes, including customer relationship management, inventory management, transportation networks, procurement, demand forecasting and risk management. AI technologies such as Machine Learning, Natural Language Processing and Generative AI offer transformative solutions to streamline logistics, reduce operational risk and improve demand forecasting. In addition, this study identifies barriers to AI adoption, such as implementation challenges, organizational readiness and ethical concerns, and highlights the critical role of AI in promoting supply chain visibility and resilience in the midst of global crises. Future trends emphasize human-centric AI, increasing digital maturity, and addressing ethical and security concerns. This review concludes by confirming the critical role of AI in shaping sustainable, flexible and resilient supply chains while providing a roadmap for future research and application in SCM.

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Publication Details

Journal
Applied Sciences
Published
2025-03-04
DOI
https://doi.org/10.3390/app15052775
Citations
25
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
52.53
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article

AI Applications in Supply Chain Management: A Survey

Athanasios Kelemis, Nikolaos Kladovasilakis, Ioannis Kostavelis, Adamos Daios
25 citations
Applied Sciences
Big Data and Business Intelligence
52.53
article

AI Applications in Supply Chain Management: A Survey

Athanasios Kelemis, Nikolaos Kladovasilakis, Ioannis Kostavelis, Adamos Daios
article en
25 citations

Abstract

The advent of Industry 4.0 and the integration of Artificial Intelligence (AI) is transforming supply chain management (SCM), improving efficiency, resilience and strategic decision-making capabilities. This research study provides a comprehensive overview of AI applications in key SCM processes, including customer relationship management, inventory management, transportation networks, procurement, demand forecasting and risk management. AI technologies such as Machine Learning, Natural Language Processing and Generative AI offer transformative solutions to streamline logistics, reduce operational risk and improve demand forecasting. In addition, this study identifies barriers to AI adoption, such as implementation challenges, organizational readiness and ethical concerns, and highlights the critical role of AI in promoting supply chain visibility and resilience in the midst of global crises. Future trends emphasize human-centric AI, increasing digital maturity, and addressing ethical and security concerns. This review concludes by confirming the critical role of AI in shaping sustainable, flexible and resilient supply chains while providing a roadmap for future research and application in SCM.

Applied SciencesVol. 15(5)
International Hellenic University (GR)
Openalex Percentile: Top 0%
Big Data and Business Intelligence
52.53
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AI Applications in Supply Chain Management: A Survey — Athanasios Kelemis, Nikolaos Kladovasilakis, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS