AI continually transforms cross-border logistics as global trade networks grow more complex and environmentally demanding. From predictive demand forecasting and route optimization to automated customs processing and real-time risk monitoring, AI-driven systems help companies reduce fuel consumption, minimize delays, and enhance supply chain transparency. By integrating data from ports, carriers, and regulatory authorities, these technologies support more sustainable decision-making while maintaining efficiency and compliance. Further exploration may reveal how AI-enabled strategies reshape international logistics to balance economic performance with environmental responsibility and long-term resilience. AI-Enabled Strategies for Sustainable Cross-Border Logistics explores how AI and digital transformation drive sustainability in logistics systems. It provides a comprehensive framework for understanding how AI-driven models, data analytics, and automation can optimize cross-border operations, reduce emissions, and improve resilience across global supply networks. This book covers topics such as data analytics, decarbonization, and environmental science, and is a useful resource for business owners, engineers, academicians, researchers, and scientists.