In recent years, artificial intelligence (AI) has revolutionized several aspects of human life. The availability of high-dimensionality datasets with progression in high-performance computing, and innovative deep learning architectures which are the subdomains of AI, have led to promising functions of AI in the medical contexts, particularly in oncology. Regarding the capacity of AI models in recognition and learning patterns as well as associations, these systems can be utilized in various aspects of cancer research including cancer diagnosis and treatment. To be precise, AI models are able to analyze medical images such as stained histopathology slides and radiology images and consequently pave the way for cancer diagnosis, grading, classification, tumor characterization, and prognosis prediction. Moreover, AI algorithms can assess a myriad of medical data to recognize patterns and make predictions about patient treatment outcomes, enabling more personalized treatment plans. Accordingly, AIassisted cancer treatment strategies have been shown to notably improve the quality of cancer treatment with chemotherapy, immunotherapy, and even radiotherapy while reducing the treatment toxicities.