This chapter explores the transformative role of Artificial Intelligence (AI) in optimizing demand forecasting and inventory management across various industries. Traditional methods, while useful, often fail to meet the demands of modern, dynamic supply chains, leading to inefficiencies such as stockouts and overstocking. AI-driven solutions, leveraging machine learning, deep learning, and predictive analytics, offer enhanced accuracy, efficiency, and cost reductions. By automating key processes and integrating with advanced technologies like IoT and blockchain, AI enables real-time decision-making and smarter resource allocation. The chapter also examines challenges in data quality, system integration, and workforce adaptation, while highlighting future research directions in AI adoption, optimization, and the integration of emerging technologies.
Nirali DaveDhanraj P. TambuskarRanendu Kumar NathP. SelvakumarT. C. ManjunathPuneet Kumar Gupta
Olamide Raimat AmosuPraveen KumarYewande Mariam OgunsujiSegun OniOladapo Faworaja
Olamide Raimat AmosuPraveen KumarYewande Mariam OgunsujiSegun OniOladapo Faworaja