A Study on the Current Status of Cash Logistics and Future Analysis Based on Artificial Intelligence and Industry 5.0

The significance of logistics and SCM has grown due to intense global competition, disaster and the future pandemics. Additionally, the high cost of logistics processes is also increasing the cost and environmental impact of production. This study analyses the current state of research in the field of cash logistics and identifies future development trends based on methodological findings. In the course of the present study, a total of 78 academic articles published between 2006 and 2024 and retrieved from the WoS, Scopus, ScienceDirect, and Google Scholar databases were examined. The primary analytical approach employed was bibliometric mapping and thematic content analysis, supported by MAXQDA and VOSviewer. The findings indicate that the literature focuses primarily on operations research, constrained vehicle routing, AI-based ATM demand forecasting, and the optimization of physical security risks. The analysis results demonstrate that ML and ANN have a significant impact on cost minimization and operational accuracy. In view of these findings, specific recommendations have been developed for industry research and applications. In accordance with the points, it is recommended that human-machine collaboration be strengthened within the framework of Industry 5.0. Furthermore, dynamic optimization algorithms such as deep reinforcement learning, blockchain-based security protocols, and autonomous vehicle systems should be integrated into cash networks.