The era of cancer diagnosis and treatment can change dramatically through Artificial Intelligence (AI). The present paper looks into AI's transformative attributes alongside the barriers and constraints that need to be solved for clinical integration to be successful. We discuss how AI-assisted solutions can help target therapeutic regime investigation and speed up medical decision-making in different medical fields related to oncology. Next, we highlight the challenges that harnessing AI faces like data standardization, ethical matters, and the level of accuracy of the data and adaptability of AI models. In summary, we underline the necessity of international cooperation, the importance of XAI (explainable AI) for establishing trust, and the conduct of the research in a manner that involves clinical trials and real-time demonstration in patients to guarantee database safety and usefulness in cancer care. AI can change the treatment world of cancers by combatting these obstacles and moving onto new ways. Such possibilities entail more accurate diagnosis, effective therapy, and hopefully, improved outcomes for the patients in the end.