Al And ML Applications in Supply Chain Management: A Review

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies into Supply Chain Management (SCM) has emerged as a transformative force, revolutionizing traditional practices and fostering efficiency, agility, and innovation. This review research paper provides a comprehensive analysis of the diverse applications of AI and ML in SCM, aiming to elucidate their impact, challenges, and future prospects.

The paper begins by delineating the foundational principles of AI and ML and their relevance to SCM. It explores how AI, with its ability to simulate human intelligence, and ML, with its capacity to learn from data, offer powerful tools for optimizing various facets of the supply chain, from demand forecasting to inventory management, logistics, and beyond.

Subsequently, the review delves into the manifold applications of AI and ML across different stages of the supply chain. It examines how predictive analytics powered by AI and ML algorithms enable more accurate demand forecasting, reducing stockouts and excess inventory while enhancing customer satisfaction. It also discusses how AI-driven optimization algorithms streamline production planning and scheduling, improving resource allocation and minimizing lead times.

Furthermore, the paper explores the role of AI and ML in enhancing supply chain visibility and resilience. It discusses how real-time data analytics and predictive modeling enable proactive risk management, allowing organizations to identify and mitigate disruptions promptly. Additionally, it examines how AI-powered predictive maintenance enhances asset reliability and reduces downtime, contributing to operational efficiency and cost savings.

The paper also addresses the challenges and considerations associated with the adoption of AI and ML in SCM, including data quality and accessibility, algorithm transparency, and organizational readiness. It underscores the importance of interdisciplinary collaboration and organizational change management in maximizing the benefits of AI and ML technologies.

This research paper highlights the transformative potential of AI and ML applications in SCM, offering insights into their diverse applications, challenges, and implications. It underscores the imperative for businesses to embrace AI and ML-driven innovations to remain competitive in an increasingly complex and dynamic global supply chain landscape. Finally, it outlines future research directions aimed at harnessing the full potential of AI and ML in redefining the future of supply chain management.Top of Form