This chapter explores the transformative role of AI in personalized medicine, emphasizing the integration of AI with genomics, microbiome analysis, and medical imaging to tailor treatments to individual patient profiles. Advances in genome sequencing and microbiome mapping are uncovering unique genetic variations and their implications for disease susceptibility. AI-enhanced medical imaging further aids in early diagnosis and targeted treatment. This shift toward patient-centered care, supported by digital tools and AI, is poised to redefine healthcare, empowering individuals to shape their health outcomes. Patients will become more proactive in managing their health, as exemplified by Larry Smarr, who utilizes personal health data to interact with healthcare providers. In parallel, digital twins and virtual patients are transforming healthcare by leveraging AI to create personalized disease models. These models will facilitate data sharing and reduce redundant testing, thereby enhancing patient management. As of today, digital twins simulate organ functions and predict disease impacts. Virtual patients, based on real patient data, simulate drug effects. Future advancements could aim to integrate comprehensive biological and imaging data, creating digital avatars for personalized health decisions and treatment predictions.