This paper presents the concept and research findings on an intelligent monitoring system for the automated product packaging process. The system was designed to enhance the efficiency and accuracy of quality inspection, minimize production losses, and eliminate human errors. The scope of the research included an analysis of existing quality control methods, the development of an advanced vision system, the implementation of artificial intelligence algorithms, and their integration with the production monitoring system. The methodology applied encompassed the analysis of historical data, the creation of a product defect image database, the development and training of machine learning algorithms, and their validation under real production conditions. The system was validated on a production line, demonstrating high effectiveness in identifying packaging and labeling defects. The implementation of the system contributed to improved process stability, a reduction in the number of complaints, and increased operational efficiency. The developed solution is flexible and scalable, allowing its application in other production processes.