Inventory Management System and Prediction Using AI - ML

Abstract

The application of Artificial Intelligence (AI) and Machine Learning (ML) in inventory management has revolutionized business processes by enabling precise demand forecasting, stock optimization, and an efficient supply chain. This study examines an AI-based inventory management system based on predictive analytics to solve the problems of stockouts, overstock, and fluctuation in demand. By leveraging sophisticated forecasting models, real-time monitoring, and independent decision-making processes, this study recognizes the manner in which AI enables the optimization of inventory control and operational efficiency. The paper reviews the existing literature on AI-based inventory management, defines system implementation processes, and evaluates the pros and cons of these systems. The study determines that AI-based inventory systems significantly reduce operational inefficiencies, improve capabilities to make better decisions and enable a competitive edge in modern supply chain management. The implemented system is scalable and seamlessly integrated as an AI-based inventory solution for different business sizes.