The Impact of AI on Global Supply Chain Management: A Review of Literature

Abstract

This paper provides a comprehensive review of the literature on the impact of Artificial Intelligence (AI) on Global Supply Chain Management (SCM). The integration of AI technologies, including machine learning, predictive analytics, and automation, has revolutionized traditional supply chain processes by enhancing efficiency, visibility, and decision-making capabilities. The adoption of Artificial Intelligence (AI) in global supply chain management (SCM) is increasingly seen as a critical enabler of efficiency, resilience, and sustainability. This literature review synthesizes the findings of papers examining the role of AI in transforming supply chains, focusing on its impact on decision-making, operational optimization, and risk management. The review identifies key AI technologies such as machine learning, predictive analytics, and automation that drive improvements in areas like demand forecasting, inventory management, and logistics optimization. Despite the significant potential of AI to enhance supply chain performance, challenges related to data quality, cost of implementation, and workforce adaptation are also highlighted. The review further emphasizes the need for a more integrated approach to AI, combining it with other technologies like the Internet of Things (IoT) and blockchain to maximize benefits. Practical and theoretical implications for supply chain managers, technology developers, and policymakers are discussed, alongside recommendations for future research in areas like AI ethics, SME adoption, and cross-technology integration.