Recent advancements in artificial intelligence (AI) hold significant promise for transforming hemophilia care. This review explores AI's impact on critical aspects of hemophilia management, including bleeding risk prediction, biomarker identification, personalized treatment strategies, and patient education. We discuss the application of machine learning models in predicting bleeding risks among children with hemophilia engaging in physical activities, the use of AI in analyzing factor VIII protein structures to determine disease severity, and the development of AI-powered chatbots and digital platforms for patient education and self-management, particularly in resource-limited settings. Furthermore, we address the challenges inherent in implementing AI technologies in clinical practice, such as data privacy concerns, model interpretability, and the need for robust validation. By highlighting current advancements and future directions, we underscore AI's potential to enhance personalized care and improve outcomes for individuals with hemophilia.