Infusing Generative AI into Supply Chain Management: Driving Intelligent and Anticipatory Operations

Because global supply chains are changing so quickly, businesses need to use new technologies to make them more flexible, accurate, and strong. This study looked into the possible use of Generative Artificial Intelligence (GAI) in supply chain management (SCM) to make operations smarter and more proactive. The study looked at GAI's effects on important supply chain tasks like demand forecasting, inventory optimization, supplier risk assessment, and logistics coordination using a mix of approaches, including simulation modeling and expert reviews. The results showed that GAI made forecasts much more accurate, sped up decision-making, improved inventory levels, and made lead time less variable. Experts agreed that GAI had a lot of technological potential, but they also stressed the importance of human control, interpretability, and ethical use. The results showed how GAI can change the way supply chain ecosystems work by making them more proactive and data-driven, which lets them adapt to changing market conditions.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-29
DOI
https://doi.org/10.5281/zenodo.17227221
Primary Topic
Cultural Identity and Heritage
Type
article
Field-Weighted Citation Impact
0.00
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article

Infusing Generative AI into Supply Chain Management: Driving Intelligent and Anticipatory Operations

Zenodo (CERN European Organization for Nuclear Research)
Cultural Identity and Heritage
article

Infusing Generative AI into Supply Chain Management: Driving Intelligent and Anticipatory Operations

article en

Abstract

Because global supply chains are changing so quickly, businesses need to use new technologies to make them more flexible, accurate, and strong. This study looked into the possible use of Generative Artificial Intelligence (GAI) in supply chain management (SCM) to make operations smarter and more proactive. The study looked at GAI's effects on important supply chain tasks like demand forecasting, inventory optimization, supplier risk assessment, and logistics coordination using a mix of approaches, including simulation modeling and expert reviews. The results showed that GAI made forecasts much more accurate, sped up decision-making, improved inventory levels, and made lead time less variable. Experts agreed that GAI had a lot of technological potential, but they also stressed the importance of human control, interpretability, and ethical use. The results showed how GAI can change the way supply chain ecosystems work by making them more proactive and data-driven, which lets them adapt to changing market conditions.

Zenodo (CERN European Organization for Nuclear Research)
Jisc (GB)
Openalex Percentile: Top 40%
Cultural Identity and Heritage
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