A study on AI-based demand forecasting in cargo logistics with special reference to Maxtrom Cargo Logistics Private Limited, Coimbatore

This study aims to examine how Artificial Intelligence (AI) technologies contribute to improving demand forecasting accuracy and operational efficiency in cargo logistics. The study focuses on understanding how AI-driven forecasting models assist in predicting demand fluctuations, optimizing inventory levels, and enhancing decision-making at Maxtrom Cargo Logistics. Primary data was collected through surveys and interviews with employees and management, while secondary data was gathered from company records, research journals, and logistics industry reports. The findings indicate that AI-based demand forecasting significantly enhances forecast accuracy, minimizes stockouts and overstocking, reduces operational costs, and supports better planning across logistics functions. The study concludes that integrating AI technologies leads to improved resource utilization, faster response to market changes, and overall business growth. Recommendations include investing in advanced AI forecasting tools, employee training, and data integration systems to achieve higher accuracy, improve service efficiency, and maintain a competitive edge in the logistics sector.