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# AI/ML Proliferation Leading to Many Issues: Attorney
- URL: https://www.fdaweb.com/ai-ml-proliferation-leading-to-many-issues-attorney/
- Published: 2023-03-29T12:00:00.000Z
- Updated: 2026-09-14T18:22:36.000Z
- Author: David McFarland
- Tags: Devices, #legacy-id-D5154090

Artificial Intelligence/Machine Learning (AI/ML) regulatory principles are in greater flux and progressing at a greater rate than any other area of FDA regulatory oversight. That’s the view of attorney **Jesse Atkins** (Gardner Law) in an online [post](https://www.jdsupra.com/legalnews/the-evolving-fda-regulatory-landscape-2823241/?ref=fdaweb.com).

“In a discipline as dynamic as this,” he writes, “the most important step manufacturers can take is to pay attention to the shifting sands: monitor FDA’s guidance promulgations and rulemaking to ensure you’re up to date on current requirements; keep tabs on FDA approvals and clearances of AI/ML-enabled devices to gain insight into FDA’s evolving approach to AI/ML regulatory oversight; and track FDA enforcement actions to help define potential landmines you can avoid in your own product development.”

The post opens with an extensive overview of FDA AI/ML regulatory activities and guidances. “The landscape of FDA oversight of AI/ML-enabled medical devices is dynamic, and the only constant that industry should expect in the coming years is change,” Atkins writes. “Evidence of this change can be found in the recently announced CDRH proposed guidances for FY 2023\. Draft guidance topics for the coming fiscal year most notably includes ‘Marketing Submission Recommendations for a Change Control Plan for AI/ML-enabled Device Software Functions.’ Additional guidances related to cybersecurity, content of premarket submissions for device software functions, and evaluation of sex-specific and gender-specific data in medical device clinical studies are sure to impact manufacturer activities related to the development, regulatory submission, and maintenance of AI/ML-enabled medical devices.”

Atkins says that in addition to keeping up with FDA activities on this topic, manufacturers and developers should also:

- clearly define the role of AI/ML in a medical device;
- build good machine learning practices into quality processes from the infancy of product development;
- develop total product lifecycle approaches that clearly define post-market iterative activities; and
- make their voice heard in guidance development and rulemaking.

“While it may seem like we’ve witnessed a lifetime’s worth of actions regarding AI/ML in healthcare in just the past several years,” Atkins concludes, “we undoubtedly have only just glimpsed the tip of the iceberg…. With the significant number of unanswered questions that remain, and with recent history demonstrating the rapid change of the AI/MI regulatory environment, manufacturers are encouraged to continue to consume new information as it comes available and participate in the discussions driving regulatory change.”