Optimizing Supply Chain Decisions: Navigating the Future with AI-Powered Demand Forecasting and Inventory Management in Retail

Authors

Devender Yadav

Abstract

The retail landscape is a dynamic environment that poses significant challenges for supply chain management. Accurate demand forecasting and effective inventory management have become essential for survival and prosperity. This research examines the transformative potential of Artificial Intelligence (AI) as a significant tool for revolutionizing critical aspects of retail operations. This study examines the application of AI algorithms, supported by extensive datasets and advanced analytical methods, to enhance the accuracy of consumer demand predictions compared to conventional approaches, thereby improving inventory management practices. This paper outlines potential benefits such as decreased operational costs, reduced occurrences of stockouts and overstock, and improved customer experience. The text recognizes the challenges associated with AI adoption and outlines a framework for effective implementation. This paper presents a novel perspective on the topic, highlighting the interconnectedness of advanced forecasting and human oversight, despite existing research in the field.

Keywords

Retail, Supply Chain Optimization, Demand Forecasting, Inventory Management, Artificial Intelligence, Machine Learning, Predictive Analytics, Operational Efficiency, Big Data, Stockouts, Overstock, Consumer Behavior, Retail 4.0

Optimizing Supply Chain Decisions: Navigating the Future with AI-Powered Demand Forecasting and Inventory Management in Retail. Devender Yadav. 2022. IJIRCT, Volume 8, Issue 5. Pages 1-10. https://www.ijirct.org/viewPaper.php?paperId=2502031