Abstract
This article explores the applications of artificial intelligence (AI) technologies in metrology, particularly in the field of optical measurement. The study analyzes the early-stage use of artificial intelligence, machine learning, and deep learning algorithms in quality control tasks such as image segmentation and classification. The use of AI in optical measuring instruments for detecting abrasive grains on the surface of grinding tools—evaluating their distribution, size, and height—is examined as a practical example. Additionally, the article discusses future scenarios in which AI could not only detect defects but also identify production deficiencies, provide feedback, and even autonomously trigger corrective actions. The findings demonstrate that AI in metrology holds strong potential not only to reduce human workload but also to support complex decision-making processes in industrial environments.