Infusing Generative AI into Supply Chain Management: Driving Intelligent and Anticipatory Operations
DOI:
https://doi.org/10.5281/zenodo.17227221Keywords:
generative AI, supply chain management, demand forecasting, inventory optimization, predictive analytics, intelligent operations, anticipatory decision-making, logistics efficiency, artificial intelligence in SCMAbstract
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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Copyright (c) 2025 Vijayendra Vittal Rao
This work is licensed under a Creative Commons Attribution 4.0 International License.
Research Articles in 'Applied Science and Engineering Journal for Advanced Research' are Open Access articles published under the Creative Commons CC BY License Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/. This license allows you to share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and build upon the material for any purpose, even commercially.
