According to a review published on News-Medical on Jun 26 2026, artificial intelligence (AI) is improving diagnostic accuracy, efficiency, and reproducibility in clinical breast pathology. The review reports concrete applications including detection of lymph node metastases, Nottingham grading, classification of benign versus malignant lesions, automated quantification of biomarkers, prognosis and risk stratification, and tumor microenvironment analysis. The authors highlight the field's technical evolution from rule-based systems to deep learning and multimodal foundation models, and identify real-world implementation challenges including data quality, bias, regulatory considerations, cost, infrastructure, and workflow integration.