The integration of artificial intelligence (AI) with big health data is transforming longevity research and clinical practice. Advances in machine learning, deep learning, and natural language processing enable the analysis of genomics, proteomics, medical imaging, and electronic health records, supporting early disease detection, biomarker discovery, and precision medicine. This chapter examines global efforts in Europe, North America, and China, highlighting initiatives such as the European Health Data Space, the UK Biobank, and the All of Us program. While private companies and public institutions increasingly leverage health data, challenges persist in ensuring access to more data, in a secure, ethical, and equitable way. Key risks include dual-use concerns, data misuse by commercial brokers, and the limitations of large language models, which are prone to inaccuracies. Opportunities lie in translational science, AI-driven drug repurposing, real-time health monitoring, and the creation of digital twins. The authors recommend stronger international coordination, standardized data governance, and mandatory use of AI where it demonstrably improves health outcomes. Public institutions, with their extensive datasets and social mandate, are well-positioned to lead a “CERN for Longevity,” ensuring that AI-driven health innovations serve collective well-being and extend healthy human lifespan.