Breast imaging faces significant challenges with the increasing volume of medical imaging requests and the potential for missed lesions in breast screening programs. Solutions to address these challenges are being actively sought, particularly with the recent advancements and adoption of artificial intelligence (AI)-based applications to enhance workflow efficiency and improve patient-healthcare outcomes. AI tools have been proposed and used to analyze various forms of breast imaging, and most published studies focus on their use for detecting and classifying breast lesions, segmenting breast tissue, evaluating breast density, and assessing breast cancer risk. This article reviews the background of conventional computer-aided detection (CAD) systems and AI, as well as AI-based applications in breast medical imaging for lesion identification, segmentation, and classification, breast density evaluation, and cancer risk assessment. Additionally, the challenges and limitations of AI-based applications in breast imaging are discussed.