Artificial Intelligence and Internet of Things Logistics Optimization: Research on Logistics Robot-Based Optimization – A Case Study of the Amazon Model

With the impressive rise in e-commerce, the implementation of artificial intelligence (AI) and Internet of Things (IoT) in automation of the warehouse became faster. Mobile robots may be widespread in warehouses; nevertheless, their effectiveness proves to be unsatisfactory as they cannot navigate and coordinate effectively, namely breakdown between the implement system and Enterprise Resource Planning, Warehouse Management System lead to low performance. To reach the integrative optimization, this paper implement the in depth case study approach, and the analysis of Amazon logistics model was taken. Using a review of technical literature, industry reports, and publicly available performance data, this paper analyzes the application of the artificial intelligence technologies, including AI bot collaboration and path optimization, at Amazon in a manner that is synergistic. The review reveals that this holistic strategy has enabled innovation in major operation data such as throughput, inventory precision, and scalability. Precisely, the combination of AI and IoT with ERP/WMS systems contributes greatly to the responsiveness of the systems, as well as the effectiveness of decision making which results in a tangible change in the inventory accuracy (more than 95 percent), picking efficiency (by up to 40 percent), and space utilization (by 20 percent-35 percent). The research points out that to become optimized logistics in the Industry 4.0 age, it is important to have technological integration and not isolated automation.