Supply Chain Management and Logistics: A Data Analytics, Machine Learning, and Artificial Intelligence Perspective

The digital transformation has opened supply chain management (SCM) and logistics to the new frontiers of operations beyond the traditional scope and into the realm of an intelligent and data-driven ecosystem. The combination of data analytics, machine learning (ML), and artificial intelligence (AI) has changed how supply chain operations are planned, monitored and optimized. In this literature review, attention will be paid to the combination of these technologies to enhance visibility, predict demand, decrease transportation expenses and enhance the efficiency of decision-making. The current research paper unites the most recent studies and business tendencies in explaining how the concept of artificial intelligence as predictive analytics, machine learning as optimization regimes, and big data structures are making it possible to develop a resilient and agile logistics network. Also, it touches upon the up-to-date concerns including data fragmentation, model interpretability, and cybersecurity and brings some understanding of resilient and intelligent SCM models aligned with the concept of Industry 5.0. Our findings indicate that analytics and artificial intelligence, combined, do not only enhance the quality of operations, but also is the basis of self-learning and independent supply branches in the future.