Abstract
This review paper examines the pivotal role of AI-driven predictive analytics in optimizing supply chain operations within the IT industry. By leveraging machine learning, deep learning, and neural networks, predictive analytics can significantly enhance demand forecasting, inventory management, supplier selection, and risk management. Despite its potential to revolutionize supply chains, the integration of AI faces challenges, including data quality, the need for skilled personnel, and organizational resistance. Strategic implementation approaches are discussed, emphasizing robust data infrastructure, stakeholder engagement, and continuous innovation. This paper contributes to the academic discourse by highlighting AI's economic and social implications in supply chains and suggesting directions for future research. It is a comprehensive guide for practitioners and academics navigating the complexities of AI-driven predictive analytics in supply chain optimization. Keywords: AI-driven Predictive Analytics, Supply Chain Optimization, IT Industry, Machine Learning, Strategic Implementation.
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