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US Federal·In Effect·Effective January 12, 2021

FDA Action Plan for AI/ML-Based Software as a Medical Device

Dates and status re-checked against primary sources on October 19, 2026. How we verify

The FDA regulates AI and machine learning software that meets the definition of a medical device (Software as a Medical Device, or SaMD). Its January 2021 AI/ML action plan led to guidance on pre-market review and on predetermined change control plans (PCCPs). The FDA finalized its PCCP guidance for AI-enabled device software functions on December 4, 2024 and re-issued it on August 18, 2025, letting manufacturers pre-authorize planned modifications as part of a 510(k), De Novo or PMA submission instead of filing a new one for each change. On August 18, 2026 the FDA also published a discussion paper on regulating generative AI-enabled devices, with comments due by October 19, 2026 under docket FDA-2026-N-7874; the paper is not draft or final guidance. The FDA says it had authorized over 1,600 AI-enabled devices as of September 2026.

What this means for your team

If you build or sell software that analyzes medical images, assists clinical diagnosis, monitors patient vitals, or supports treatment decisions, and your software influences the diagnosis or treatment of disease, it may be a medical device subject to FDA regulation. This includes AI tools embedded in electronic health records, telehealth platforms, or wearable devices that make clinical recommendations. Whether you need FDA review, and through which pathway, depends on the device's classification and intended use. A PCCP can spare you a new submission for each planned model update.

Key requirements

  • AI/ML SaMD may need 510(k) clearance, De Novo authorization or PMA before US marketing, depending on risk
  • Predetermined Change Control Plan (final guidance December 4, 2024, re-issued August 18, 2025): pre-authorize planned modifications within the initial marketing submission
  • Describe the planned modifications, how they will be validated, and their impact in the PCCP
  • Plan for post-market monitoring of real-world performance
  • Good Machine Learning Practice (GMLP) principles apply to development and validation
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