The emergence of AI as a tool for better healthcare offers opportunities to improve patient and clinical outcomes and reduce costs. Robotics and diagnosis and treatment applications can improve outcomes. Robotic process automation that performs structured digital administrative tasks can reduce cost. Big data and predictive analytics aid in improving population health. While all these uses can improve healthcare, they also come with potential pitfalls. Bias in AI presents significant challenges and can lead to false outcomes. This also presents ethical and legal challenges that must be addressed. Additionally, to be truly effective, AI requires multiple data sets and resides in the cloud, which causes concern about the privacy and security of patient data. This presentation will look at each area.