ADLM calls for CLIA updates to help ensure safe and reliable use of AI in laboratory medicine

WASHINGTON, Sept. 15, 2026 /PRNewswire/ -- The Association for Diagnostics & Laboratory Medicine (ADLM) has submitted comments in response to a federal request for information regarding potential updates to the Clinical Laboratory Improvement Amendments (CLIA), which are a set of regulatory standards that govern all clinical laboratory testing in the U.S. In the comment letter, ADLM recommends that, under CLIA, emerging artificial intelligence (AI) tools should remain subject to the same professional expertise, quality systems, validation requirements, and monitoring standards that apply to traditional laboratory testing.

Read the full comment letter: https://myadlm.org/advocacy-and-outreach/Comment-Letters/2026/clia-rfi

Clinical laboratory testing has advanced significantly since CLIA was first implemented in 1992, and one of the biggest recent developments in the field is the growing use of AI. Traditional software has long supported high-quality laboratory testing by performing functions such as verifying, interpreting, and reporting results, and newer technologies such as AI and machine learning are playing an increasingly integral role in many of these same areas. However, AI-based tools introduce new modes of failure and safety issues that the current CLIA framework does not address. For example, an error in conventional software generally affects every patient case that meets the same programmed conditions and can be evaluated using cases with known expected outputs. An AI-based model, on the other hand, may produce case-specific errors, making it more difficult to troubleshoot the problem. Generative AI can also produce inaccurate or unsupported information, omit clinically important facts, or change behavior following updates to the model, prompt, or knowledge base.   

As AI-based tools become more prevalent in laboratory medicine, ADLM recommends making targeted updates to CLIA that reflect the new challenges that accompany these technologies. Highlights of the recommendations in ADLM's comment letter include the following:

• The Centers for Medicare & Medicaid Services and the Centers for Disease Control and Prevention (the two agencies that support CLIA) should establish federal oversight for AI-based tools that avoids unnecessary duplication. Specifically, the Food and Drug Administration may regulate particular software products or medical devices, while CLIA governs the laboratory's responsibility for accurate and reliable testing.
• CLIA should distinguish between conventional software and AI models. Laboratories should also account for the differences in how traditional software and learned models perform when validating and monitoring their performance.
• CLIA should adopt a risk-based, technology-appropriate approach that establishes clear quality expectations for AI-based tools while preserving the ability of laboratory directors and qualified laboratory professionals to determine scientifically appropriate methods for meeting these expectations.
• When a facility independently analyzes patient-specific laboratory data or provides specialized laboratory interpretation that generates or helps generate a test result or interpretation for clinical use, those activities are part of the total testing process and should be subject to appropriate CLIA oversight.

Overall, ADLM's comments emphasize that AI-based tools should be evaluated as part of the total testing process within CLIA's existing framework rather than treated as standalone software tools that require the creation of a separate regulatory structure.

"AI has the potential to support tremendous advances in laboratory medicine, but innovation in this area must be balanced with the need to ensure test quality and patient safety," said ADLM President Dr. Stanley F. Lo. "Laboratories have the expertise and quality systems needed to evaluate, implement, and continuously monitor AI tools, making continued laboratory oversight essential to the responsible use of AI in clinical laboratory testing."

About the Association for Diagnostics & Laboratory Medicine (ADLM)
Dedicated to achieving better health for all through laboratory medicine, ADLM unites more than 70,000 clinical laboratory professionals, physicians, research scientists, and business leaders from 110 countries around the world. Our community is at the forefront of laboratory medicine's diverse subdisciplines, including clinical chemistry, molecular diagnostics, mass spectrometry, clinical microbiology, and data science, and is comprised of individuals holding the spectrum of lab-related professional degrees, certifications, and credentials. Since 1948, ADLM has championed the advancement of laboratory medicine by fostering scientific collaboration, knowledge sharing, and the development of innovative solutions that enhance health outcomes. For more information, visit www.myadlm.org.

Christine DeLong
ADLM
Director, Editorial and Media Relations
(p) 202.835.8722
[email protected]

Bill Malone
ADLM
Senior Director, Strategic Communications
(p) 202.835.8756
[email protected]

SOURCE Association for Diagnostics & Laboratory Medicine (ADLM)