Artificial Intelligence (AI) has significantly transformed Non-Destructive Testing (NDT) by enhancing data analysis, defect detection, and predictive maintenance. Integrating AI into NDT methods has led to improved accuracy, efficiency, and automation.Initially, NDT relied heavily on human expertise for interpreting complex data, such as ultrasonic signals. Traditional methods were manual and time-consuming, with limited automation. The advent of AI introduced machine learning algorithms capable of processing vast datasets, leading to automated defect detection and characterization. Deep learning techniques, particularly convolutional neural networks, have been applied to ultrasonic data, enabling systems to learn from data and identify patterns without explicit programming.