According to the World Health Organization, cancer is one of the leading causes of death globally, accounting for approximately ten million fatalities annually (2020). Cancer encompasses more than 100 distinct types, including breast, lung, skin, and blood cancers. These diseases are characterized by the uncontrolled growth of abnormal cells, which can invade nearby tissues and metastasize to other parts of the body. The complexity of cancer arises from the interplay of genetic, environmental, and lifestyle factors, such as smoking, diet, lack of physical activity, and exposure to carcinogens. Both inherited and acquired genetic mutations play significant roles in the development and progression of cancer, resulting in diverse clinical presentations and varying responses to treatment. Given this complexity, there is an urgent need for advancements in prevention strategies, early detection methods, and personalized interventions. Recent developments in artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), have revolutionized cancer care. These technologies facilitate earlier and more accurate cancer detection, prediction, and prognosis, thereby improving patient outcomes. This chapter explores the potential of AI-driven automation to address the complexities of cancer diagnosis and treatment, emphasizing its transformative role in enhancing global cancer care.