Human-augmented AI data labeling combines human expertise with automated processes to produce scalable, high-quality training data. This approach enhances accuracy and consistency in labeled datasets, supporting the development of reliable machine learning models. It enables efficient handling of large volumes of data while maintaining precise annotation standards.