AI-Powered Inventory Solutions: Enhancing Accuracy and Efficiency in Supply Chains

In today’s rapidly changing business environment, traditional inventory management practices are proving inadequate in addressing dynamic market demands and supply chain disruptions. This research paper explores the transformative potential of Artificial Intelligence (AI) in revolutionizing inventory management systems across manufacturing and retail industries. It critically analyzes how AI tools—such as machine learning, predictive analytics, automation, and digital twins—enhance inventory accuracy, forecasting precision, and overall operational efficiency. Through case studies involving global corporations like Amazon and healthcare institutions like the Mayo Clinic, as well as a primary case study of Safe Shop India, this study presents evidence-based improvements achieved via AI integration, including reduced stockouts, optimized holding costs, and improved customer satisfaction. The findings strongly advocate for the strategic adoption of AI in inventory management to build agile, data-driven, and resilient supply chains capable of responding to uncertainty and customer expectations.