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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

AI-driven predictive analytics for demand forecasting and inventory optimization in Oracle Supply Chain Cloud

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  • AI-driven predictive analytics for demand forecasting and inventory optimization in Oracle Supply Chain Cloud

Rajeev Vinodkumar Rungta *

Symbiosis (SCMHRD), Pune, India.

Review Article

 

World Journal of Advanced Engineering Technology and Sciences, 2025, 17(02), 311–316

Article DOI: 10.30574/wjaets.2025.17.2.1498

DOI url: https://doi.org/10.30574/wjaets.2025.17.2.1498

Received on 24 September 2025; revised on 10 November 2025; accepted on 13 November 2025

Artificial intelligence (AI) and predictive analytics are converging, which is changing the process of supply chain management and allowing organizations to forecast market dynamics, enhance decision-making, and maximize operational efficiency. The Oracle Supply Chain Cloud uses AI to predict the future, boost demand forecasting, and manage inventory management in global businesses at a lower cost and without compromising performance. In this article, the author will give a detailed overview of AI-based projections and optimization in the cloud ecosystem of Oracle. It discusses the importance of data-driven models, integration issues, and adaptive algorithms in the development of resilient supply chains. The study shows that AI-based predictive analytics can help organizations switch to future-ready strategies that are driven by ex-post to the ex-ante ones.

Artificial intelligence; Oracle Supply Chain Cloud; Data-driven models; Economic order quantity; Demand Forecasting

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2025-1498.pdf

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Rajeev Vinodkumar Rungta. AI-driven predictive analytics for demand forecasting and inventory optimization in Oracle Supply Chain Cloud. World Journal of Advanced Engineering Technology and Sciences, 2025, 17(02), 311-316. Article DOI: https://doi.org/10.30574/wjaets.2025.17.2.1498.

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