The AI Revolution in Industry: A Review of Its Usage in Reverse Logistics Returns Prediction

As a result of the increasing growth of various industrial sectors in the modern era, and the remarkable progress in Artificial Intelligence (AI) technologies, predicting product returns, their causes, and the various processes that follow the return stage has become a matter of great importance and a modern trend for industrial and commercial companies. The primary goal of this approach is to achieve customer satisfaction by improving operational efficiency, reducing costs, and reducing the risk of excess inventory. This study analyzes scientific papers published between 2020 and 2025 that included forecasting returns and associated processes, including recycling, remanufacturing, and refurbishment as a post-return stage. We also highlight a variety of artificial intelligence methods, such as deep learning, machine learning, and large language models. AI is being used in a wide range of industries and businesses, such as consumer goods, fashion, automotive, and auto parts, to improve their operations. This research also addresses the generalizability of the results, research gaps, future directions, and the data they relied on. Additionally, exploring emerging technologies and providing a comprehensive analysis of AI methods for predicting returned products in reverse logistics.