A Typology of Generative Health Care Artificial Intelligence - Definitions and Policy Implications

David Blumenthal, M.D., M.P.P., and Vivian S. Lee, M.D., Ph.D., M.B.A.
Abstract
AI in health care presents persistent challenges for patients, clinicians, and policy makers owing to its rapid evolution and conceptual complexity. The field has progressed swiftly from early generative chatbots to more advanced autonomous agents and, increasingly, to integrated agentic AI systems capable of coordinating complex tasks autonomously. These technologies are often introduced without clear definitions or practical guidance, leaving health care organizations to interpret their capabilities and implications independently. This article aims to clarify key distinctions among emerging AI paradigms and provide a lens for understanding their functional differences, risks, and potential applications in clinical and administrative contexts. Improved conceptual clarity is essential for safe and effective implementation and appropriate regulation and oversight as AI continues to expand its role across the health care system. (Funded by the Commonwealth Fund and the Gordon and Betty Moore Foundation.)

A Typology of Generative Health Care Artificial Intelligence - Definitions and Policy Implications