Since 2020, the world has faced unprecedented challenges due to the COVID-19 pandemic, accelerating the adoption of Artificial Intelligence (AI) in healthcare. AI has revolutionized disease detection and clinical diagnostics through machine learning algorithms, improving patient outcomes. However, integrating AI into healthcare introduces cybersecurity risks, necessitating robust protection mechanisms. This paper explores AI’s role in enhancing medical security, focusing on machine learning-driven cybersecurity approaches. By analyzing emerging threats and countermeasures, this study presents a comprehensive review of AI’s impact on smart healthcare and the security challenges that accompany it. Additionally, it discusses the integration of blockchain technology, federated learning, and robust encryption mechanisms to enhance AI-driven healthcare security.