7 ways AI is revolutionizing supply chain forecasting and optimization

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.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-09
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0584
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

7 ways AI is revolutionizing supply chain forecasting and optimization

Suresh Kumar Maddala
World Journal of Advanced Engineering Technology and Sciences
Big Data and Business Intelligence
article

7 ways AI is revolutionizing supply chain forecasting and optimization

Suresh Kumar Maddala
article en

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.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 84%
Big Data and Business Intelligence
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