The Role of AI and Machine Learning in Supply Chain Optimization

Abstract

Conventional supply chains are unable to meet the complexity and expectations of contemporary corporate operations in the fast-changing global economy of today. In response to these difficulties, companies are looking for artificial intelligence (AI) and machine learning (ML) (Higgins, O., Short, B. L., Chalup, S. K., & Wilson, R. L., 2023) more and more as potent tools to improve their supply chains.

These technologies help companies to improve predictive maintenance procedures, increase supply chain visibility, accurately forecast demand with never-seen-before precision, and maximize operational expenses. By means of real-time data analysis, artificial intelligence and machine learning deliver companies pertinent information supporting rapid and smart judgments.

Emphasizing demand forecasting, inventory optimization, predictive maintenance, and financial decision-making, this paper explores the transformational opportunities of advanced technology in supply chain management. This emphasizes the need to use big data to improve supply chain openness and lower geopolitical, natural catastrophe, and market volatility associated risks.

Case studies of companies like Walmart (Harrison, 2019) and Siemens show how effectively artificial intelligence and machine learning increase operational efficiency, save costs, and boost financial growth.

 The paper investigates the long-term effects of artificial intelligence and machine learning on supply chains (Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., & Verma, S, 2024) concluding that businesses adopting these technologies are more fit to manage future challenges, achieve sustainable development, and keep a competitive advantage in a sophisticated and linked market.