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Public companies linked to 92% of AI medical device recalls
Most AI medical device recalls were linked to publicly traded companies, with established public companies' recalled devices often lacking clinical validation, new research shows.
New research reveals that recalls of AI-enabled medical devices primarily involved devices manufactured by publicly traded companies and lacking clinical validation.
Published in JAMA Health Forum, the study examined recalls of AI-enabled medical devices cleared through the FDA 510(k) pathway. At the end of 2024, the agency finalized new guidance, which includes non-binding recommendations, to simplify the process for approving AI-and machine learning-enabled medical devices as demand for these technologies grew.
As of July 10, 2025, the FDA had approved over 1,200 AI-enabled medical devices.
Researchers from the Johns Hopkins Carey Business School, the Johns Hopkins Bloomberg School of Public Health and Yale School of Medicine noted in the new study that the 510(k) clearance process does not require prospective human testing, which means many AI devices enter the market with limited clinical validation. They set out to examine whether the lack of reported clinical validation and publicly traded manufacturer status were associated with device recalls.
The researchers matched all FDA-cleared AI medical devices to recall entries in the Center for Devices and Radiological Health database from Nov. 15 to Nov. 30, 2024.
Of 950 AI-enabled medical devices, 60 were associated with 182 recalls, with an average of three recalls per device. Diagnostic or measurement errors accounted for 109 recalls, followed by functionality delay (44 recalls), physical hazards (14 recalls) and biochemical hazards (13 recalls).
Publicly traded companies accounted for 53.2% of AI-enabled medical devices but 91.8% of recalls. About 77.7% of recalled devices from established public companies lacked clinical validation compared to 40% from privately traded companies.
Overall, public company status was associated with a 5.9 times higher chance of a recall event.
"The lopsided nature of these recalls should give every advocate for medical AI pause. Publicly traded companies, the big fish in this still-small pond, built just over half the devices but were responsible for nearly all the recalled units," said Tinglong Dai, corresponding author and Bernard T. Ferrari Professor of Business at the Johns Hopkins Carey Business School, in an emailed press release.
Further, researchers observed that 43.4% of the AI device recalls occurred within the first year of device clearance, approximately double the recall rate for all 510(k) devices. This suggests that "the 510(k) process may overlook early performance failures of AI technologies," the researchers wrote.
The researchers concluded that requiring prospective evaluation, as well as increasing pre-market clinical testing requirements and post-market surveillance measures, could help reduce the risk of recalls.
The study comes as AI tools become increasingly integrated in healthcare. However, recalls of these technologies can exacerbate existing trust issues with the technology, and agencies like the FDA play a critical role in cementing that trust in the new era of AI.
Anuja Vaidya has covered the healthcare industry since 2012. She currently covers the virtual healthcare landscape, including telehealth, remote patient monitoring and digital therapeutics.
