This study investigates the role of Artificial Intelligence (AI) in transforming logistics and supply chain productivity, and its subsequent impact on national Gross Domestic Product (GDP). By analysing the potential of AI applications in demand forecasting, transportation optimization, port and customs operations, warehousing, and supply chain risk management, this paper examines how AI can enhance logistics efficiency and contribute to economic growth. Using Nigeria as a case study, given its strategic trade position and ongoing logistics challenges, the research highlights how AI adoption can alleviate inefficiencies like port congestion, transport bottlenecks, and poor demand forecasting. The study employs a conceptual–analytical research design, synthesizing empirical studies and established economic theories such as Total Factor Productivity, Transaction Cost Economics, and Supply Chain Integration. The findings suggest that AI-driven logistics improvements, particularly in demand forecasting and transportation optimization, significantly reduce logistics costs, enhance trade facilitation, and improve asset utilization. AI's contribution to GDP growth is further supported by empirical evidence showing that optimized logistics systems increase national competitiveness, attract investments, and boost export performance. The study concludes that AI-enabled logistics systems contribute to GDP growth through cost reduction, enhanced operational efficiency, and improved supply chain resilience. Policy recommendations include investments in digital infrastructure, regulatory reform, and human capital development to support effective AI adoption in developing economies. These insights provide an integrated framework for understanding how AI can drive macroeconomic performance through logistics productivity enhancements.