IMPACT OF ARTIFICIAL INTELLIGENCE ON MONITORING AND MANAGEMENT OF STOCK LEVELS

Abstract

Inventory management is one of the main issues facing businesses in the current business environment because of the increased unpredictability, quick changes in the market, and increasing complexity of supply chains. Through the use of sophisticated analytical and predictive models, artificial intelligence (AI) becomes a crucial tool for enhancing inventory level monitoring and management. This paper's goal is to examine how artificial intelligence affects inventory management efficiency, with a particular emphasis on automating inventory monitoring, optimizing ordering, and cutting expenses associated with both excess and inadequate inventory. The theoretical examination of contemporary inventory management techniques and the identification of critical domains where the use of artificial intelligence enhances decision-making serve as the foundation for this work. The use of machine learning algorithms in demand forecasting, identifying obsolete and slow-moving goods, and enhancing supply chain coordination are all given particular attention. Along with possible dangers related to data quality and reliance on automated judgments, organizational and information conditions for the effective adoption of VI systems in inventory management are also covered.

The study's conclusions show that artificial intelligence can greatly increase inventory level monitoring accuracy and help make better use of resources, but that its full impact requires integration with current information systems and sufficient management oversight.Managers, accountants, and researchers interested in the digital transformation of inventory management procedures may find the study interesting as it offers a foundation for more empirical research.