ALT A table showing phase-based framework for evidentiary maturity in clinical artificial intelligence. The table includes five phases: Model development and representation learning, Internal validation, External validation, Decision impact and implementation readiness, and Postdeployment monitoring. Each phase details core questions, evidence expected, and example claims supported, from technical feasibility to durable clinical effectiveness.

ALT A quote from a Perspective published in NEJM AI reads as follows: “Access to agentic research capacity should ... be treated as a shared — potentially national or international — scientific resource rather than a local institutional asset.” The Perspective is titled “Agentic AI Teammates in Medical Research — From Tools to Collaborators — and the Accelerating Digital Divide” and the authors are Lars Masanneck, M.D, M.Sc., and Sibylle C. Mellinghoff, M.D. The background color is orange and includes the NEJM AI logo.

ALT A bar chart showing the average large language model–patient agreement (blue bars) compared with average human proxy–patient agreement (horizontal brown and black dotted lines) across 10 repetition trials (±95% confidence intervals).

ALT Dark navy image with an illustration of a doctor using technology to evaluate diagnostic and imaging results. Below the illustration reads the following: Reinventing Clinical Guidelines in the AI Era October 21, 2026 Free Virtual Event The NEJM AI logo is centered at bottom.

ALT Figure 1 illustrates the current versus proposed regulatory pathways for clinical AI. Panel A: The current pathway, which relies on retrospective evidence and includes no systematic postmarket evaluation. Panel B: The proposed pathway, which adds multisite validation and continuous monitoring with a feedback loop for reevaluation when performance thresholds are not met.

ALT Page 1 of the editorial "The Promise and Perils of Autonomous AI in Science"