Abstract: Anomaly detection has become a critical aspect of automated visual inspection in manufacturing, enabling enhanced quality control, reduced waste, and improved operational efficiency. This paper explores AI-driven methodologies, particularly leveraging computer vision and machine learning techniques, for anomaly detection in industrial settings.