Artificial intelligence (AI) is transforming cancer diagnosis and screening by improving image interpretation, pathology analysis, risk prediction, and early detection. Cancer remains one of the leading causes of morbidity and mortality worldwide, and delayed diagnosis continues to reduce survival outcomes. AI-based tools using machine learning, deep learning, computer vision, and natural language processing have demonstrated promising applications in breast cancer mammography, lung cancer computed tomography, cervical cancer screening, dermatological imaging, colorectal cancer detection, and digital pathology. These technologies can support clinicians by identifying suspicious lesions, reducing diagnostic error, prioritizing high-risk cases, and increasing screening efficiency. However, clinical implementation requires careful validation, regulatory oversight, ethical safeguards, data privacy protection, and equitable access. This review examines the role of AI in cancer diagnosis and screening, highlights current applications, discusses challenges, and proposes a framework for safe and effective integration into oncology practice.