The artificial intelligence (AI) is transforming public health by enhancing cancer prevention, early detection, and management. The increasing burden of cancer, particularly in resource-limited settings, necessitates innovative solutions that improve accessibility, accuracy, and efficiency in healthcare. The influence of AI techniques including deep learning, predictive analytics, and federated learning on cancer diagnosis, risk assessment, and treatment planning is evaluated in this systematic study. AI-powered telemedicine, natural language processing (NLP) for electronic health records, and AI-driven image analysis are changing public health tactics and clinical decision-making. Assuring model generalizability across various populations is a major obstacle to AI deployment. The efficacy of current AI models in under-represented areas is limited by their frequent struggles with biased training data. The application of AI in healthcare is also severely hampered by ethical and privacy issues. We suggest the AI-Powered Cancer Control (AI-PCC) framework, which incorporates federated learning to improve data diversity and protect patient privacy in order to overcome these constraints. By using scalable AI models designed for global health systems, the framework guarantees dependability and accessibility across a range of healthcare infrastructures. AI improves patient outcomes, expedites healthcare workflows, and increases the accuracy of cancer diagnosis, according to findings. However, in order to gain widespread use of AI, issues including data heterogeneity, regulatory compliance, and ethical concerns need to be solved. Future research should focus on developing transparent, explainable AI models, establishing global AI governance policies, and fostering interdisciplinary collaboration among policymakers, healthcare providers, and AI developers. By leveraging AI responsibly, healthcare systems can enhance early cancer detection, optimize resource allocation, and reduce disparities in care. This study underscores the transformative potential of AI in oncology and emphasizes the need for continued research and policy development to ensure equitable and effective cancer care worldwide.