This chapter focuses on the integration of AI and FMs in industrial logistics. It highlights the pivotal role of OT in monitoring and controlling physical processes, tracing its evolution from isolated systems to integrated enterprise networks. Integrating AI with OT revolutionizes warehouse automation and transportation systems, equipping them with advanced capabilities in predictive maintenance, resource optimization, and automated decision-making. The implementation framework centers on four key components: AI-driven digital twins, Industrial Internet of Things (IIoT) integration, natural language interfaces, and comprehensive data analytics [Möller et al., 2021 IEEE International Conference on Electro Information Solutions (EIT) (pp. 413–418). IEEE. https://doi.org/10.1109/EIT51626.2021.9491874 (2021)]. This framework enables real-time monitoring, control, and optimization of logistics processes. The chapter also addresses the significant challenges in cyber security and underscores the importance of protecting against data breaches, hostile attacks, and logistics vulnerabilities. It outlines strategic approaches to implementing FMs in organizations and emphasizes the importance of ethical leadership, change management, and ongoing maintenance. It recommends a hybrid approach that combines proprietary and public data for optimal model training. Implementing AI in logistics requires careful planning, significant investment in solutions and skilled personnel, and robust cybersecurity measures to protect sensitive operational data.