Sarcouncil Journal of Engineering and Computer Sciences

Abstract: This article examines a transformative initiative implemented across Walmart's retail network to modernize truckload receivings and return claims processing through artificial intelligence and predictive analytics. The article details how traditional retail logistics systems face inherent limitations, including manual errors, delayed discrepancy detection, and reactive return processing, creating significant financial and operational challenges. The article demonstrates how a three-pronged approach focusing on proactive error detection, predictive risk assessment, and comprehensive visibility was systematically deployed across more than 500 Walmart clubs. Implementation followed a carefully structured rollout with pilot locations, extensive integration testing, and comprehensive training programs. The results reveal substantial improvements in inventory accuracy, fraud detection, processing efficiency, and financial performance. This article offers valuable insights into how AI-enhanced logistics systems can transform conventional retail operations into strategic assets with measurable business impact while addressing the growing complexity of modern retail environments.