The exponential growth of e-commerce and the demand for just-in-time delivery models have rendered traditional warehouse management systems (WMS) insufficient for modern logistical challenges. This paper explores the integration of Artificial Intelligence (AI) in facilitating autonomous warehouse management, specifically focusing on the optimization of inbound (receiving) and outbound (shipping) processes. Through a qualitative review of current technologies and industry applications, this study examines how machine learning algorithms, computer vision, and autonomous mobile robots (AMRs) mitigate errors, reduce operational latency, and enhance predictive accuracy. The findings suggest that AI-driven autonomy does not merely automate manual tasks but fundamentally reshapes inventory flow by enabling dynamic decision-making. The paper concludes with a discussion on the future trajectory of "dark warehouses" and the implications for supply chain resilience.
A. Kipper Jose (Wed,) studied this question.