Authors : Md Raisul Islam Khan; Ayan Barua; Fazle karim; Niropam Das

Volume/Issue : Volume 10 - 2025, Issue 6 - June

Google Scholar : https://tinyurl.com/33ahwzun

DOI : https://doi.org/10.38124/ijisrt/25jun1161

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The fast expansion of digital supply chain management has been fueled by the integration of artificial intelligence (AI) and business analytics, which has transformed traditional logistics, procurement, and manufacturing operations. This article investigates the influence of AI-powered technologies like machine learning, predictive analytics, robotic process au- tomation (RPA), and the Internet of Things (IoT) on increasing efficiency, lowering operating costs, and improving decision- making. Case studies from Amazon, Walmart, and Tesla demonstrate the effective application of AI-driven supply chains, highlighting practical benefits such as improved inventory management, predictive maintenance, real-time logistics track- ing, and accurate demand forecasting. Despite these developments, enterprises confront barriers to AI adoption, such as high implementation costs, data security threats, and workforce adaptation difficulties. Addressing these limitations through organized AI integration methods, personnel training, and data governance frameworks is critical for realizing the full po- tential of AI in supply chain operations. As AI evolves, firms who engage proactively in these technologies will gain more agility, sustainability, and competitive advantage in the global supply chain landscape.

Keywords : Artificial Intelligence, Business Analytics, Digital Supply Chain, Machine Learning, Robotic Process Automation, Internet of Things.

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