Artificial intelligence (AI) employs mathematical algorithms to replicate human cognitive functions, addressing formidable healthcare challenges like intricate biological anomalies such as cancer. The remarkable surge in AI over the past decade suggests its potential as a platform for super-intelligent decision-making, surpassing human limitations in processing vast data within tight timeframes. Cancer, an intricate and multifaceted disorder with myriad genetics and epigenetic variations, stands to benefit significantly from AI-based algorithms. These algorithms show promise in early-stage detection of genetic mutations and abnormal protein interactions. Collaborating with pathologists and physicians, AI assistance marks a significant stride in predicting disease risk, facilitating diagnosis, prognosis, and treatment. This review outlines several recent instances where AI applications in oncology have notably enhanced prediction, diagnosis, and treatment across various cancer types, revolutionizing the field. The integration of AI has resulted in groundbreaking progress in cancer diagnostics, prognosis, and treatment by extracting valuable insights, particularly from sources like radiology imaging. By adopting AI-based systems, researchers can engage in real-time collaboration and digitally share knowledge, potentially benefiting millions in the quest for improved healthcare outcomes.