ARTIFICIAL INTELLIGENCE IN SUPPLY CHAIN MANAGEMENT: FROM OPTIMIZATION TOOL TO STRATEGIC INFRASTRUCTURE

The integration of Artificial Intelligence (AI) into Supply Chain Management (SCM) has evolved significantlyin response to increasing global complexity, uncertainty, and digital transformation. What initially emerged asrule-based optimization and operations research models has progressively developed into predictive, adaptive,and autonomous decision-support systems. This study analyzes the evolution of AI applications in supply chains through a qualitative literature review ofrecent academic research in the field. The analysis examines how AI technologies including machine learning,deep learning, and generative AI are transforming critical supply chain functions such as demand forecasting,inventory optimization, transportation planning, risk mitigation, and warehouse automation.The findings indicate that AI technologies significantly enhance forecast accuracy, operational efficiency, andsupply chain resilience, while also introducing new challenges related to data governance, cybersecurity,algorithmic transparency, and workforce transformation. The study contributes to the literature by demonstrating that AI is no longer limited to operational optimizationbut is increasingly becoming a strategic infrastructure enabling adaptive, data driven, and resilient global supplynetworks.