Personalized medicine represents a paradigm shift from the traditional one-size-fits-all approach to a more precise and individualized model of healthcare. This transformation is driven by advances in genomics, bioinformatics, and artificial intelligence (AI). AI, particularly machine learning, enables the integration and analysis of vast amounts of biological, clinical, and environmental data, allowing for tailored treatments that enhance efficacy and minimize adverse effects. This article explores the role of AI in personalized medicine, highlighting its applications in genomic analysis, biomarker discovery, and predictive modeling. Additionally, we discuss the challenges associated with AI-driven personalized medicine, including data privacy, ethical considerations, and the need for regulatory frameworks. By leveraging AI, personalized medicine has the potential to revolutionize healthcare, improving patient outcomes and optimizing therapeutic strategies.