Personalized medicine, which tailors medical treatment to the individual characteristics of each patient, has seen significant advancements with the integration of artificial intelligence (AI). AI technologies, including machine learning (ML) and deep learning (DL), have the potential to revolutionize healthcare by enabling more accurate diagnoses, predicting treatment outcomes, and optimizing therapeutic strategies. However, the implementation of AI in personalized medicine is not without challenges, including data privacy concerns, algorithmic bias, and the need for robust validation frameworks. This article explores the role of AI in personalized medicine, discussing its applications, challenges, and future directions. We provide a comprehensive review of the current state of AI in healthcare, highlighting key technologies, methodologies, and case studies. Additionally, we discuss the ethical and regulatory considerations that must be addressed to fully realize the potential of AI in personalized medicine.