AI implementation modernizes cancer diagnosis and treatment procedures to create faster accurate patient care which additionally produces personalized treatment plans. This paper studies emerging AI trends in oncology treatment that revolutionizes diagnostic techniques throughout different stages of cancer. First the paper introduces standard AI technology knowledge followed by discussions about its medical applications within the field of oncology. The article examines AI diagnostic tools used for cancer detection by combining biodetectors with imaging devices and taxonomic tumor identification methods to enhance diagnostic precision. The assessment emphasizes AI contributions to medical plan generation through precision oncology treatment administration and enhanced chemotherapy delivery and radiation therapy methods for individual patients. The research examines the ways AI strengthens both individual disease prediction technology and statistical model implementations for disease tracking. The use of AI in cancer care management produces intricate challenges which include safety risks and treatment disparities while also causing privacy implications and understanding troubles for AI models. The document introduces essential solutions for critical problems with details about mandatory regulatory structures for deploying AI technologies throughout clinical operations. The assessment shows that forthcoming healthcare innovation necessitates explainable AI (XAI) systems and federated learning and multi-omics information integration approaches for individualized oncology care. Future-oriented analysis in this paper supplies useful information to help researchers and clinical professionals together with governmental officials create the next generation of AI-based cancer medicines.