A learning health system, in which medicine as a field learns from the care of every patient, has been a longstanding goal of both academia and industry. The emergence of AI (and technology more broadly) has the potential to solve critical challenges in this arena, including to medical data across systems, curation and harmonization of disparate and unstructured datasets, and even biobanks and formal registries. This panel will explore how the idea of a learning health system may benefit from these technological advances and the impact they could have on patient care, biomedical research, and drug development. The session will also explore the obstacles to creating a truly adaptive learning framework, including data interoperability and ethical considerations for patient privacy.