Maddala, Suresh Kumar (2025) 7 ways AI is revolutionizing supply chain forecasting and optimization. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 680-686. ISSN 2582-8266
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Abstract
The integration of artificial intelligence into supply chain management represents a profound transformation of traditional approaches to forecasting and optimization. AI technologies enable organizations to leverage vast amounts of data for enhanced prediction accuracy, dynamic inventory management, efficient logistics operations, comprehensive risk mitigation, and adaptive decision-making. Despite significant advantages in operational efficiency and resilience, implementation faces challenges including data fragmentation, model interpretability, cybersecurity concerns, and regulatory compliance requirements. Forward-thinking organizations that systematically address these obstacles can achieve substantial competitive advantages through AI-powered supply chains that respond intelligently to market fluctuations, minimize disruptions, and optimize resource allocation across complex global networks.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.2.0584 |
Uncontrolled Keywords: | Supply Chain Intelligence; Predictive Analytics; Inventory Optimization; Logistics Automation; Risk Mitigation |
Depositing User: | Editor Engineering Section |
Date Deposited: | 04 Aug 2025 16:25 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/3562 |