The rapid integration of generative artificial intelligence (AI) into social media platforms has transformed digital health communication, particularly in the dissemination of cancer-related information. This study presents a systematic review and meta-analysis examining the role of generative AI–driven health communication on social media, with a specific focus on engagement metrics, information trustworthiness, risk perception, and cancer prevention outcomes. Following PRISMA guidelines, peer-reviewed studies published between 2015 and 2026 were systematically identified across major academic databases. Quantitative synthesis was conducted using random-effects meta-analytic models to estimate pooled effect sizes for user engagement indicators, including likes, shares, comments, and time spent interacting with AI-generated content. The analysis further evaluates the credibility and trustworthiness of generative AI–produced health messages and their influence on users’ perceived cancer risk and preventive behavioral intentions. Results indicate that AI-generated health communication significantly enhances user engagement compared to traditional content, while trustworthiness is moderated by source transparency, algorithmic explainability, and message framing. Additionally, increased engagement and perceived credibility were positively associated with heightened risk awareness and improved cancer prevention outcomes, such as screening intentions and information-seeking behaviors. However, concerns related to misinformation, ethical governance, and bias in AI-generated content remain substantial. This review underscores the potential of generative AI to advance scalable and personalized cancer prevention communication, while highlighting the need for robust regulatory frameworks, ethical safeguards, and interdisciplinary research to ensure accuracy, trust, and public health impact..