What FDA is considering
In August 2026, FDA issued a discussion paper on potential regulatory approaches for generative AI-enabled medical devices and opened a public docket for stakeholder feedback. The Digital Health Center of Excellence within the Center for Devices and Radiological Health is leading the effort.
FDA explicitly states that the paper is for discussion purposes only. It is not draft or final guidance, does not propose or implement policy changes, and does not communicate proposed or final CDRH regulatory expectations.
Comments may be submitted under docket FDA-2026-N-7874 through October 19, 2026.
1. Risk may depend on both device activity and the consequences of an incorrect output
CDRH presents a possible two-axis framework for thinking about risk. One axis reflects what the software function does, ranging from informational and non-directive functions to action-directing and fully autonomous functions. The second axis reflects the severity of harm that could result from relying on an incorrect output.
Under the proposed heuristic, risk increases as device activity becomes more independent and the consequences of an incorrect output become more severe. CDRH is seeking feedback on whether this framework captures the dimensions most relevant to generative AI-enabled device risk; it is not presented as a finalized classification system.
2. Premarket evaluation could use a competency-based approach
CDRH is also considering a competency-based approach to premarket evaluation. The concept combines non-clinical device benchmarking with clinical confirmation and evaluates the final user-facing device as configured for real-world deployment, rather than evaluating an underlying foundation model in isolation.
The paper discusses benchmarking elements that may address safety, clinical proficiency, generalizability, and additional capabilities relevant to agentic AI. The nature and rigor of evidence could be tailored to intended use and device risk.
3. Postmarket monitoring could become a larger part of the evidence strategy
Generative AI-enabled devices may change or degrade because of shifts in input populations, data environments, model components, or third-party foundation models. CDRH therefore discusses possible approaches including periodic re-benchmarking, sample-based clinician review, and performance degradation monitoring.
The paper also asks whether some GenAI-enabled devices could appropriately carry greater premarket uncertainty if that uncertainty were managed through stronger postmarket monitoring. FDA has not established such an approach; it is specifically seeking stakeholder input on when, if ever, it may be appropriate.
What manufacturers can examine now
The paper does not create a new compliance checklist, but it provides a useful set of questions for teams already developing GenAI-enabled devices:
- How independently does the device direct or take action?
- What is the most serious consequence of relying on an incorrect output?
- Can current verification and validation evidence address safety, clinical proficiency, generalizability, and relevant deployment environments?
- If the device relies on a third-party foundation model, can the manufacturer detect and assess model changes that affect device behavior?
- Is there a defined postmarket approach for detecting drift, performance degradation, or other GenAI-specific failure modes?
- If the architecture is agentic, how are autonomous multi-step actions, tool use, and reduced opportunities for human review evaluated?
The most useful signal in this discussion paper is the structure of the regulatory questions CDRH is asking. Risk stratification, competency evidence, change control, foundation-model dependencies, and ongoing performance monitoring are all likely to remain important issues as FDA develops its approach to generative AI-enabled devices.
Sources
- Primary official sourceConsiderations for the Regulation of Generative AI-Enabled Medical Devices: Discussion Paper and Request for Feedback (opens in a new tab)U.S. Food and Drug Administration
- Supporting sourceConsiderations for the Regulation of Generative AI-Enabled Medical Devices: Discussion Paper and Request for Feedback (opens in a new tab)U.S. Food and Drug Administration
- Supporting sourceFDA Seeks Public Feedback to Inform Regulatory Approach for Generative AI-Enabled Medical Devices (opens in a new tab)U.S. Food and Drug Administration