Before an AI tool reaches a clinic, it goes through steps that help show whether it may work safely in real settings.
A clear job to focus on
A reliable tool has one specific purpose. If a tool claims to do everything, it’s reasonable to pause and ask whether any single tool really can.
Learning from many types of images
AI learns from examples. A tool trained only on one clinic’s images may not handle images from elsewhere as well — variety in training data helps it perform more steadily.
Company testing: an essential first step
Developers rigorously test their tools on new images before they ever reach a clinic. This is a critical part of responsible development — and the reason independent follow-up testing is so informative.
Independent testing: the real-world check
When independent teams test a tool with new patients and equipment, results can differ from company testing. That difference is valuable information — it shows how the tool performs beyond the lab.
Regulatory review
In the U.S., many tools go through FDA review, which helps ensure the tool stays within its stated limits and is described clearly.
Ongoing monitoring
AI systems can change over time. Checking back periodically helps confirm a tool still works as expected.
AAAI-D doesn’t approve tools — it helps people understand how they were tested so they can make their own thoughtful decisions.
Our Commitment to the Public
AAAI-D does not endorse or promote commercial products.
Our role is to educate, and support educational and research endeavors, to explain AI clearly, support transparency, and help the public and professionals understand benefits and limitations so AI is used responsibly, ethically, and in the patient’s best interest.
This page is reviewed and updated periodically. The information on this page is current as of October 2026.
AAAI-D does not endorse, certify, or promote commercial products. However, as the field evolves, the Academy may develop neutral, education-focused frameworks that help the public and professionals understand how different AI tools describe their capabilities, provide transparency, or share supporting information. It is intended only to help people make sense of a rapidly changing technology landscape in a balanced, informative way.