Abstract: Breast cancer is the most common malignant tumor in women worldwide, and its incidence rate is increasing annually. Early diagnosis is essential for improving patient prognosis. In recent years, artificial intelligence (AI) technology has emerged as a transformative tool, providing new directions for accurate diagnostic and prognostic assessments. This article systematically reviews research progress in the application of AI to breast cancer screening, multimodal imaging techniques for diagnosis, pathological diagnosis, treatment, and prognostic modeling. Through machine learning and deep learning algorithms, AI has demonstrated significant advantages in the enhancement of diagnostic accuracy, efficiency, and accessibility, including improvement of the detection rate of small lesions, reduction in the radiologists’ workload, and optimization of treatment decisions. Despite challenges, including the integration of explainable technology in clinical transformation, lack of data standardization, complexity of multimodal data, and risk of model generalization, AI is expected to play a more prominent role in the precise diagnosis and intelligent therapy for breast cancer, thereby contributing to the full realization of the goal of precision medicine.