AI in cancer care may aid early diagnosis, reduce radiologist workload, assist in clinical trial recruitment, manage data, and determine imaging responses. However, limitations include privacy, reliability, and cost. AI's broad applications span clinical trial design, treatment response, triaging, imaging, pathology, genomics, and more. AI models like Sybil can predict lung cancer risk from a single low-dose CT scan. Despite potential, human oversight remains crucial due to AI's lack of pathophysiological understanding.