In evaluating healthcare AI agents, several challenges arise, including establishing clear performance benchmarks, ensuring accuracy, and navigating complex regulatory, legal, and privacy concerns. AI agents hold potential to reduce costs and improve accessibility in healthcare, particularly in underserved areas and multilingual contexts. However, issues such as liability, trust, and human factors persist, demanding careful consideration. The legal landscape is particularly complex, as AI agents' autonomous nature introduces unprecedented legal puzzles, complicating deployment and accountability. Regulatory bodies like the FDA are actively exploring guidelines to manage these technologies, though the dynamic nature of AI presents unique challenges. While AI agents can streamline administrative tasks and fill healthcare gaps, especially where specific medical specialists are lacking, they also risk exacerbating existing issues like cost distribution, unless systemic changes accompany their integration. Ultimately, the future of AI in healthcare hinges on balancing innovation with robust oversight to ensure equitable benefits across the system.