A boy who had a metal straw impaled in his brain was saved when doctors repurposed an AI-powered medical device typically used for stroke detection to better characterize the damage. This critical information guided treatment decisions and ultimately saved the child's life.
This example of how AI is increasingly being used to save lives was one of several highlighted recently by the Advanced Medical Technology Association (AdvaMed) in a report detailing an “AI Policy Roadmap” for regulators and lawmakers to help maintain the pace of innovation in the field.
“While none of us can anticipate all the change-making applications of AI in medtech to come, we can confidently predict that transformation will continue at a rapid pace,” Scott Whitaker, President and CEO of AdvaMed, wrote in the report. “This is the right time to promote the development of AI-enabled medtech to its fullest potential to serve all patients, regardless of zip code or circumstance.”
The FDA has already authorized more than 1,000 AI-enabled medical devices during its 25-year history of reviewing such technologies. While radiology and imaging applications dominate, AI-enabled devices, cardiovascular, neurology, and hematology are increasingly adopting the technology.
However, the pace of new products and novel uses of AI in healthcare will require adjustments for both regulators and companies to keep patients safe, the AdvaMed wrote.
Three Key Takeaways for AI-enabled MedTech Entrepreneurs
1. Regulation Will Tighten, but FDA Remains in the Lead
One of the strongest recommendations in the report is to preserve the FDA’s role as the lead agency regulating AI-enabled medical technologies. In anticipation of continued growth in the sector, the FDA issued draft guidance in January 2025, which included recommendations to sponsors of AI-enabled devices on design, development and documentation.
Companies should anticipate closer scrutiny as AI systems evolve from narrow-use tools to more general-purpose systems capable of adapting to new data in real time.
Developers also should design with "good machine learning practices" and plan for ongoing model updates, as the FDA is increasingly emphasizing this in its regulatory frameworks.
2. Medical Devices’ Payment Pathways Need More Clarity
Even the most innovative AI devices can struggle to reach patients without a clear reimbursement strategy.
With coverage and payment decisions typically lagging behind regulatory approvals, the report suggests companies begin their conversations with payers well in advance of any regulatory submissions. Real-world evidence, long-term outcomes data and health economic analyses will likely be critical for payment strategies.
While the Centers for Medicare and Medicaid Services (CMS) has extended coverage to digital mental health treatment devices, the reimbursement is limited to specific conditions, such as insomnia, substance use disorder, depression or anxiety. Understanding the nuance of what is covered and what is excluded can help guide startups on which what areas to focus.
One way to potentially expand what’s covered is to partner with CMS to design and participate in models testing AI's ability to improve care and lower costs, which could create faster pathways to reimbursement than waiting for system-wide policy changes.
3. Privacy and Data Security are Non-Negotiable
Balancing patient privacy with data collection is one key challenge in the AI-driven future.
Too many medical devices and healthcare systems rely on limited datasets that don’t provide enough information to gain broader insights for improving treatment. Larger datasets could help AI systems identify previously unseen trends, concerns or new uses. But building such datasets needs to be accomplished while complying with evolving privacy standards and maintaining patient trust.
Given the expanding cybersecurity threats to healthcare AI platforms, robust security protocols will also be central to product success and regulatory acceptance.
Looking Ahead to AI-Enabled Medical Devices
With Congress increasingly interested in the role of AI in healthcare, developers have a rare window to help shape the policies that will define the future of AI-enabled medicine.
Companies that build for safety, transparency and payment readiness from the outset will be better positioned to navigate upcoming regulatory changes and achieve commercial success.
“We see tremendous potential to harness AI not only to automate routine tasks, but also to deliver deeply personalized care and treatment,” said Taha Kass-Hout, MD, Global Chief Science and Oechnology officer, GE HealthCare, and chair of AdvaMed’s Digital Health Tech division board, in a news release. “The continued support of Congress and the Administration will be important in creating policies necessary to help further ensure as many patients as possible have access to AI-enabled innovations to speed diagnosis, promote the right treatment, and increase access to high quality and affordable care.”