AI-POWERED SUPPLY CHAIN AND LOGISTICS OPTIMIZATION IN ONLINE RETAIL

Abstract

The rapid expansion of online retail has created unprecedented challenges in supply chain and logistics management, driving the adoption of artificial intelligence (AI) technologies to optimize operations. This research paper examines the current state of AI implementation in online retail. Through a systematic review of recent literature and case studies, this study identifies machine learning-based demand forecasting, intelligent warehouse automation, and predictive logistics optimization as primary areas of AI impact. The findings indicate that while AI technologies offer significant potential for operational efficiency improvements and cost reduction, successful implementation requires addressing challenges related to data quality, organizational change management, and technology integration. This research contributes to the growing body of knowledge on AI applications in supply chain management and provides insights for practitioners and researchers in the field.