Health AI: Strategy, Design, and Execution

Catalog description

Artificial intelligence (AI) is promising to revolutionize healthcare, offering unprecedented opportunities to develop new treatments and diagnostic tools, reduce costs, and transform care delivery. However, successfully applying AI in the complex healthcare ecosystem requires not only technical expertise but also a clear understanding of clinical, operational, and strategic context. Healthcare leaders must grasp not only the potential of AI but also its limitations, ethical implications, and operational challenges. This course invites students to explore these issues, equipping them with the tools to think strategically and methodically about the role of AI in the healthcare. This is a practical course that emphasizes what can be achieved today and how to navigate real-world implementation challenges. By focusing on the realities of applying AI on the ground—technical hurdles, clinician collaboration, and organizational readiness—students will develop a nuanced and pragmatic understanding of how to leverage AI to drive concrete impact in healthcare organizations. Through a combination of lectures, case studies, and guest speakers, students will explore the full lifecycle of healthcare AI projects. Topics include evaluating AI use cases, navigating technical and clinical implementation challenges, and designing a roadmap for scaling AI within an organization. The course also addresses broader considerations such as bias and equity, intellectual property, and regulation in healthcare AI. Students will gain practical, hands-on experience by analyzing real-world case studies and engaging in discussions with leaders in healthcare and AI. By the end of the course, participants will be prepared to (1) critically assess AI opportunities, (2) collaborate effectively with technical and clinical teams, and (3) develop strategies for implementing AI solutions that create…