Top Use Cases for Document AI in Supply Chain and Logistics

Executive Summary

Supply chain and logistics organizations have long explored emerging technologies to improve efficiency, reduce costs, and increase visibility across increasingly complex operations. From process automation and route optimization to predictive analytics and large language models, AI has steadily become embedded in the modern supply chain technology stack. One area gaining significant momentum is document AI. While document processing technologies have existed for years, recent advances in machine learning, computer vision, and natural language processing have made it far easier — and more scalable and reliable, when supported by quality data and validation processes — to extract, understand, and act on information embedded in logistics and supply chain documents.