In today’s ever-changing corporate environment, satisfying consumer demands and maintaining competitiveness heavily depend on supply chain efficiency, especially through business web forums. This paper examines how machine learning (ML) and AI techniques assist in reordering inventory for shopping websites, reducing manual intervention, and providing transparency regarding late product deliveries. For instance, Amazon forecast is a fully managed service that leverages machine learning to generate highly accurate forecasts. It allows businesses to predict essential metrics such as sales, website traffic, and inventory demand without the need to manage infrastructure. Significant changes have occurred in managing the digital world, particularly in reducing human errors and preventing product damage in warehouses. Amazon has enhanced its warehouse operations by integrating AI and ML-driven robotics, which also led to workforce reductions. The findings of this study indicate that demand forecasting powered by machine learning is an effective tool for enhancing supply chain efficiency. It offers valuable insights for inventory management, logistics planning, and overall operational stability.