FDA’s July 2026 non-device software update: AI apps and patient safety

When an AI app “gives advice,” the key question isn’t just whether it uses generative AI. The key question is what the software is intended to help the user do and how it presents recommendations—because that influences whether the function falls within FDA’s medical device focus or outside it.

On July 14, 2026, FDA posted an update requesting public comment as it prepares its 2026 report on certain medical software functions excluded from the medical device definition under the 21st Century Cures Act. The comment deadline is August 13, 2026, submitted under docket FDA-2018-N-1910.

FDA’s practical framing: “function” matters more than the buzzword “AI”

FDA’s “Reports on Non-Device Software Functions” update describes medical software functions that are excluded from the medical device definition by the Cures Act and are the subject of FDA’s next report. FDA is asking for input to help identify best practices that may promote patient safety, education, and competency related to these non-device functions.

In plain terms: FDA isn’t saying “all AI apps are low risk” or “all AI apps are regulated.” Instead, FDA is asking how particular software functions—as they are used in real life—could affect patient safety and what guardrails should be considered.

What FDA is treating as “non-device software functions” in this request

FDA’s update describes the non-device software functions it expects to cover in the 2026 report as including software functions intended for:

Administrative support of health care facilities
Encouraging a healthy lifestyle
Serving as electronic patient records
Transferring, storing, converting formats, or displaying data
Providing limited clinical decision support

These categories matter because the 21st Century Cures Act draws a boundary between software that is treated as a medical device and software functions that may be excluded.

Non-device software vs. clinical decision support: the boundary can look blurry to patients

Even when an app is marketed with “wellness” language, the patient experience can look like clinical advice. FDA’s materials on Clinical Decision Support (CDS) explain why the distinction matters: “decision support” is a broad label, and software described as decision support can end up outside FDA’s device definition or still meet the definition of a medical device—depending on what the software does and how it’s intended to be used.

FDA also cautions that the CDS guidance is only one tool to consider and shouldn’t be treated as the only reference when assessing regulatory status.

For example, FDA’s CDS FAQs explain that software meant to perform simple medical calculations routinely used in clinical practice is not considered Non-Device CDS. However, FDA describes that if such software provides only one clinically appropriate recommendation and meets other criteria, FDA intends to exercise enforcement discretion for that type of function.

FDA also explains that software intended to support time-critical decision making does not meet the definition of Non-Device CDS—because it can be difficult to support that clinicians are not meant to rely on the recommendation without spending time to understand its basis.

What this could mean for everyday people using AI health apps

What’s known

FDA is collecting input to inform its 2026 report on patient safety risks and benefits related to certain non-device software functions, including limited clinical decision support.
FDA’s CDS approach focuses on how software is intended to be used and what the function actually does—not just whether it uses AI.
CDC highlights that generative AI outputs can be wrong or misleading, and therefore they require human oversight and review before use.

What’s not yet known

FDA’s final “best practices” recommendations may evolve after public comments are reviewed.
For any specific AI app, readers generally can’t determine whether the function is treated as a device-eligible medical function or outside FDA’s device focus from the word “AI” alone—details depend on the product’s specific function and intended use.

Who may be most affected

Patients and caregivers who use chat-style tools to interpret symptoms, manage chronic conditions, or turn medical information into next steps.
Clinicians-adjacent readers (care managers, nurse navigators, caseworkers) who may need to validate or contextualize AI outputs for a care plan.
People using AI outside the clinic, where there may be fewer built-in checks before a user acts on guidance.

CDC-style guardrails you can translate into patient-safe habits

CDC’s considerations for generative AI in public health emphasize practical safety guardrails: ensure resources exist for monitoring and oversight, and always review GenAI outputs before use. CDC also advises reviewing outputs for accuracy, completeness, and potential hallucinations or misleading content.

For everyday use, that translates into a simple habit: treat AI output as something to verify—especially when the text could lead to time-sensitive actions or changes in clinical decision making.

Clinician-adjacent takeaway: “assist, don’t replace”

The American Medical Association (AMA) has policies stressing that AI should “support—not replace” physician judgment, with meaningful physician oversight and accountability when AI is used in patient care.

For patients and caregivers, a practical translation is to ask: “Who is responsible for the final decision?” and “What does the recommendation rely on—my clinician’s plan, my data, and approved instructions?” If that isn’t clear, it’s a signal to confirm with the appropriate care team.

Real-world context (from STAT): interface vs. decision-maker

STAT reported on an FDA-cleared diabetes app from UpDoc that uses a chatbot-like, patient-facing large language model interface. STAT described the app as supporting diabetes management using a treatment plan defined by the patient’s doctor, in a product category similar to drug dose calculators—while patients receive “treatment instructions” through the AI-style interaction.

The takeaway isn’t that every AI chat is dangerous. It’s that an AI-style interface can blur roles. That’s why FDA’s broader question—how users reasonably rely on these functions—matters for patient safety.

What readers can do now

Slow down on “next steps.” If an AI output suggests a specific clinical action (especially dose changes or urgent actions), verify it with the clinician or care team that owns the treatment plan.
Check whether it’s patient-specific. Look for whether the guidance ties to your clinician’s plan and labeled instructions, versus being general information.
Use AI for drafting, not final decisions. AI can help summarize or draft questions for a visit, but it should be reviewed before treating it as medical truth.
Watch for timing cues. If symptoms feel severe or time-critical, don’t wait for AI—seek urgent or emergency care as appropriate.
If you comment on policy: FDA’s comment window for this report-related request runs through August 13, 2026.

Overall, the safest mindset is: AI may help organize information, but the responsible pathway for decisions depends on the software’s function, intended use, and—when choices are safety-critical—human oversight.

Sources

Editorial note: Weence articles are researched from cited public-health, medical, regulatory, journal, and reputable news sources and may be drafted with AI assistance. They are checked for source support, clarity, and safety guardrails before publication.

This article is for general informational purposes only and is not medical advice. Research findings can be early or incomplete, and health guidance can change. Always talk with a qualified healthcare professional about personal symptoms, diagnosis, medications, vaccines, screenings, or treatment decisions. If you think you may have a medical emergency, call emergency services right away.