AI-Driven Enterprise Supply Chain Intelligence: A Technical Deep Dive

Authors

  • Karthikeyan Selvarajan University of Illinois Urbana-Champaign, USA

DOI:

https://doi.org/10.32996/jcsts.2025.7.2.66

Keywords:

Supply Chain Intelligence, Artificial Intelligence, Enterprise Data Platforms, Cloud Integration, Predictive Analytics

Abstract

This article explores the transformative impact of AI-powered data platforms on enterprise supply chain management, focusing on architecture, implementation strategies, and performance optimization. The article examines how modern enterprises are leveraging artificial intelligence to enhance their supply chain operations through advanced analytics, cloud integration, and machine learning capabilities. The article presents a comprehensive analysis of key technical components, including real-time data processing, predictive analytics, and security frameworks, while evaluating their effectiveness in improving operational efficiency and decision-making processes. Through examination of implementation cases and performance metrics, the article demonstrates how AI-driven platforms are revolutionizing supply chain optimization, risk management, and compliance monitoring across various industries.

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Published

2025-04-28

Issue

Section

Research Article

How to Cite

Karthikeyan Selvarajan. (2025). AI-Driven Enterprise Supply Chain Intelligence: A Technical Deep Dive. Journal of Computer Science and Technology Studies, 7(2), 612-617. https://doi.org/10.32996/jcsts.2025.7.2.66