The paradigm of oncology is transitioning from generalized treatments to precision medicine, an approach that customizes care based on a patient’s unique biological makeup. This shift is empowered by artificial intelligence (AI), which enhances diagnostic accuracy and efficiency across various domains, including medical imaging, pathology, and genomic analysis. The implementation of AI in cancer care, however, necessitates overcoming significant challenges related to data quality, algorithm bias, and ethical considerations to ensure equitable and responsible deployment.