Implementation Guide
The FDA AI Enabled Medical Device List: Structure, Purpose, and Practical Use
The FDA AI-Enabled Medical Device List is a public CDRH resource identifying devices authorized for U.S. marketing that incorporate AI or machine learning, compiled from internal review of premarket submissions. It provides submission-level data fields useful for regulatory benchmarking but is explicitly not a complete inventory of every AI-enabled device on the market.
The FDA AI-Enabled Medical Device List is a public CDRH resource identifying devices authorized for U.S. marketing that incorporate AI or machine learning, compiled from internal review of premarket submissions. It provides submission-level data fields useful for regulatory benchmarking but is explicitly not a complete inventory of every AI-enabled device on the market.
What the FDA AI-Enabled Medical Device List Is
The FDA Center for Devices and Radiological Health (CDRH) publishes a public list titled “Artificial Intelligence-Enabled Medical Devices” that identifies devices authorized for marketing in the United States which incorporate artificial intelligence or machine learning functionality. The list is not the product of a mandatory AI-disclosure requirement. Instead, FDA compiles it through internal review of premarket submissions, identifying devices whose labeling and technical documentation describe AI or ML components.
FDA explicitly states that the list is not a comprehensive or fully validated inventory of every AI-enabled device legally marketed in the U.S. Devices may incorporate AI/ML functionality without being flagged during FDA’s internal review process, and the agency does not independently verify AI claims beyond what is documented in each submission. For governance leaders, this distinction matters: the list functions as a regulatory reference point, not a definitive registry of market activity.
List at a Glance
- Primary pathway Majority of listed devices authorized via 510(k)
- Leading specialty Radiology has the largest device representation
- Update frequency Periodic updates, no fixed publication schedule
- Core data fields Device name, manufacturer, submission number, pathway, specialty panel, authorization date
How FDA Compiles and Updates the List
Inclusion on the list is based on FDA staff review of premarket submissions, whether cleared through the 510(k) pathway, granted through De Novo classification, or approved via Premarket Approval (PMA). There is no standardized regulatory definition unique to AI classification; reviewers identify AI/ML functionality from the labeling and technical information submitted by manufacturers.
A large majority of devices currently on the list were authorized through the 510(k) pathway, and radiology is the medical specialty with the largest representation. FDA updates the list periodically as new authorizations occur but has not committed to a fixed publication schedule. This means the interval between updates can vary, and organizations tracking a specific device category should not assume a predictable release cadence. Governance teams should treat the absence of a fixed schedule as a planning constraint rather than an oversight.
Data Fields and How to Interpret Them
Each entry on the list includes a defined set of data fields. The list itself does not contain algorithm-level technical detail such as model architecture, training data composition, or performance metrics; that information resides in the underlying submission record referenced by the submission number.
| Field | How to interpret it |
|---|---|
| Device name | Public product identity as reflected in the authorization record |
| Manufacturer / company | Sponsor organization associated with the submission |
| Premarket submission number | Key for retrieving the underlying submission record and supporting documentation |
| Submission pathway | 510(k), De Novo, or PMA; indicates the type of premarket scrutiny applied |
| Medical specialty panel | Maps to FDA review divisions and clinical domains (for example, radiology or cardiology) |
| Date of marketing authorization | Point-in-time status at initial U.S. marketing authorization |
For benchmarking purposes, the submission pathway field carries particular weight. A 510(k) clearance indicates the device was found substantially equivalent to a predicate device, generally involving a different level of premarket scrutiny than a De Novo classification or PMA approval, which typically apply to higher-risk or first-of-kind devices. The medical specialty panel field corresponds to FDA’s internal review divisions and can help teams map competitive activity to a specific clinical domain without needing to independently categorize devices.
Pathway context for governance teams
Treat pathway labels as signals of regulatory posture at authorization, not as substitutes for full submission review. Pair list entries with the submission number when you need technical depth or claim boundaries.
Operationalizing the List in Internal Governance Workflows
Use the list as a structured input to internal process, not as a standalone system of record. A lightweight, repeatable workflow keeps benchmarking and change tracking defensible over time.
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Capture the baseline entry
Record device name, manufacturer, submission number, pathway, specialty panel, and authorization date in your internal inventory or risk register.
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Link supporting evidence
Attach or reference the underlying submission materials and labeling that substantiate AI/ML functionality and intended use.
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Set a review cadence
Because FDA does not publish on a fixed schedule, define an internal cadence (for example, quarterly) to re-check the list and log differences.
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Map pathway and specialty context
Use pathway and specialty fields when comparing predicates, competitive devices, or proposed strategies for new submissions.
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Track post-authorization change boundaries
Where algorithm updates are expected, document PCCP-related limits separately from the list snapshot so modification governance remains clear.
Governance Considerations for Compliance Teams
- Treat the list as a starting reference point, not a complete inventory of AI-enabled devices in the market.
- Maintain an internal risk register entry for each device referencing its submission number, pathway, and specialty panel.
- Log each internal review of the list, including the date reviewed and any changes identified, to support audit traceability.
- Track PCCP-related modification boundaries for any device where algorithm updates are anticipated post-authorization.
- Require regulatory strategy teams to cite comparable list entries when justifying proposed submission pathways for new devices.
Frequently Asked Questions
Does the FDA AI-enabled device list include every AI medical device on the market?
No. FDA states the list is generated from internal review of premarket submissions and is not comprehensive. Devices with AI/ML functionality may exist in the market without appearing on the list, and organizations should not treat absence from the list as evidence a device lacks AI components.
How often does FDA update the AI-enabled device list?
FDA updates the list periodically as new devices receive marketing authorization, but has not committed to a fixed publication schedule. Compliance teams should set their own recurring internal review cadence, such as quarterly, rather than relying on a predictable FDA release pattern.
What should we do if our device isn’t listed but includes AI/ML functionality?
Absence from the list does not indicate a compliance problem since inclusion criteria are based on FDA’s internal submission review rather than a mandatory disclosure requirement. Document your own AI-enabled classification internally and retain submission records supporting that determination.
How does the list relate to Predetermined Change Control Plans?
The list reflects a device’s status at authorization. If a manufacturer later modifies an AI/ML algorithm under an FDA-accepted Predetermined Change Control Plan, that governance framework, not the list itself, defines the boundaries of permissible post-market changes.
Extend Device-Level Oversight Into Continuous AI Governance
Structured device tracking through resources like the FDA AI-enabled device list is one input into a broader AI governance program. Runtime monitoring and policy enforcement extend that oversight into how AI systems actually operate after deployment.
Explore Runtime Governance