Early diagnosis is critical for reducing the number of cancers’ diagnoses and deaths that occur all over the globe. Despite the fact that they are effective, routine cancer screening procedures are hampered by inefficiencies, accessibility problems, and financial limits. Even if these strategies are successful, this is still the case. Cancer detection is being revolutionized by predictive analytics driven by artificial intelligence. Using this method, cancer may be detected at an earlier stage, with more precision, and at a lower cost. This article explores the potential for predictive analytics driven by artificial intelligence to improve cancer screenings in public health. Due to the vast datasets that are derived from medical imaging, genetic profiles, and electronic health records, artificial intelligence models have the potential to discover patterns and risk factors that are missed by traditional methodologies, mainly due to the fact that these models analyze risk variables. As a result of these advancements, sensitivity and specificity have been improved, which enables early identification and reduces the number of false positives and negatives. Furthermore, predictive analytics makes it possible to develop systems that are both scalable and cost-effective. This makes sophisticated screening processes more accessible to the general public, especially in economically disadvantaged areas. Incorporating artificial intelligence into public health systems is a struggle. There are a number of these, including strong regulations, algorithmic bias, and data privacy. This research places a focus on cancer screening that is both ethical and objective in order to maximize the advantages to world health. The use of predictive analytics to the detection of cancer is also discussed. It is essential that research and policy suggestions be conducted.