Abstract
Artificial Intelligence (AI) is revolutionizing prostate cancer (PCa) care, addressing the major clinical challenges of subjectivity and overtreatment. Our traditional tools - like PSA, DRE, mpMRI, and Gleason scoring - often lack the precision needed to distinguish truly aggressive tumors from indolent disease, leading to unnecessary morbidity in up to 50% of low-risk men. This review explains how AI, specifically machine learning (ML) and deep learning (DL), is poised to solve this. We cover AI's role from initial diagnosis, where radiomics and digital pathology boost grading accuracy and reduce inter-reader variability, to treatment selection and surgical precision through predictive models and Augmented Reality (AR) guidance. We also detail its utility in predicting biochemical recurrence (BCR) and managing long-term side effects. Finally, we address the critical barriers to adoption, including the need for large, diverse datasets (to combat algorithmic bias), the "black box" problem (solved by Explainable AI, XAI), and navigating FDA regulation. The future of PCa care hinges on this precise, data-driven approach.