Author
Abstract
This article investigates the transformative impact of Artificial Intelligence (AI) on retail distribution systems through comprehensive case studies of global enterprises. By examining successful implementations across diverse retail sectors, it analyzes how AI-driven solutions optimize supply chain operations through predictive analytics, automated decision-making, and dynamic resource allocation. It reveals significant improvements in operational efficiency, inventory management, and delivery optimization while highlighting critical challenges in data integration, scalability, and organizational adaptation. Through qualitative and quantitative analysis of implementation strategies and outcomes, the article demonstrates how AI technologies enable enterprises to build resilient, adaptive supply chains capable of responding to market fluctuations and disruptions. This article contributes to the growing body of knowledge on AI applications in retail logistics and provides practical insights for organizations pursuing supply chain digital transformation. This article synthesizes best practices and implementation frameworks that can guide future AI adoption in retail distribution, while also addressing the broader implications for industry standards and competitive dynamics in global retail operations.
Suggested Citation
Srinivas Ankam, 2025.
"Transforming Retail Distribution: AI-Enabled Supply Chain Optimization in Global Enterprises,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 3105-3112, February.
Handle:
RePEc:jbh:ijsrcs:v11:y2025:i1:id:985
DOI: 10.32628/CSEIT251112328
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112328
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