Artificial Intelligence and Business Analytics: Driving Efficiency in Digital Supply Chain Management

The fast expansion of digital supply chain management has been fueled by the integration of artificial intelligence (AI) and business analytics, which has transformed traditional logistics, procurement, and manufacturing operations. This article investigates the influence of AI-powered technologies like machine learning, predictive analytics, robotic process au- tomation (RPA), and the Internet of Things (IoT) on increasing efficiency, lowering operating costs, and improving decision- making. Case studies from Amazon, Walmart, and Tesla demonstrate the effective application of AI-driven supply chains, highlighting practical benefits such as improved inventory management, predictive maintenance, real-time logistics track- ing, and accurate demand forecasting. Despite these developments, enterprises confront barriers to AI adoption, such as high implementation costs, data security threats, and workforce adaptation difficulties. Addressing these limitations through organized AI integration methods, personnel training, and data governance frameworks is critical for realizing the full po- tential of AI in supply chain operations. As AI evolves, firms who engage proactively in these technologies will gain more agility, sustainability, and competitive advantage in the global supply chain landscape.