Three of four leading AI-powered search tools accurately identified home blood pressure monitors that met validated clinical standards only 63% to 83% of the time, according to preliminary research presented at the American Heart Association's Hypertension Scientific Sessions 2026. The findings, which are not yet peer-reviewed, highlight a critical gap in AI's ability to support health decisions, particularly for a condition affecting more than 125 million U.S. adults.
High blood pressure is the number one risk factor for cardiovascular disease, yet only about 1 in 4 of those adults have their blood pressure within the target range of less than 120/80 mm Hg. The The 2025 American Heart Association Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults recommends using a home blood pressure monitor that has been validated for accuracy. People can check validation status at www.validatebp.org.
As AI-powered search tools become integrated into online platforms, patients increasingly ask chatbots whether home health devices like blood pressure monitors are validated. A monitor is considered validated when independent, third-party testing proves it gives consistently accurate readings, and three primary registries list these devices. However, researchers found AI chatbots unreliable at making this determination. "We found that most AI tools performed only slightly better than if you had flipped a coin for each question," said Anna Soriano, M.D., a third-year internal medicine resident at the University of Montreal and the study's presenting author. "People may unknowingly think a device is validated based on the AI tool's inaccurate responses. Using that device may result in inaccurate blood pressure readings, which could lead to an inappropriate diagnosis or treatment decisions."
The study tested 324 home blood pressure monitors in Canada between April and May 2026: 145 validated devices and 179 non-validated devices, drawn from three validation registries (StrideBP, ValidateBP and Hypertension Canada), a list of known non-validated devices, and top-selling monitors on Amazon in Canada, Australia and the U.S. Four AI tools were evaluated: Google Gemini, Microsoft Copilot, ChatGPT and Perplexity. Google Gemini scored highest, answering correctly 86% to 91% of the time, while correct responses from the other three ranged from only about 63% to 83%. All four tools were less accurate at identifying validated monitors compared to unvalidated ones. When researchers retested 20% of devices that had produced mixed results, using different examiners, computers and days, the AI tools often gave different answers.
"It is surprising, and almost counterintuitive, that AI tools had so much difficulty specifically identifying validated devices, since those devices are the ones with clear listings on official registries," Soriano said. "In many cases, the AI tools found the blood pressure monitor was listed within an official website, however, it seems AI was not able to interpret being listed on the registry as proof of validation."
Keith C. Ferdinand, M.D., FAHA, an American Heart Association volunteer expert and vice chair of the Association's 2025 High Blood Pressure Guideline, emphasized caution. "The potential shortcomings of AI demonstrated by this study's results should remind clinicians and the public that the use of AI for clinical decision-making requires caution," Ferdinand said. "In addition, home blood pressure devices need to be both validated [listed on the national registry validatebp.org] and accurate. With the proper technique and regular monitoring, readings from home BP devices are a valuable component of integrated, individual treatment plans that can improve patient care and outcomes."
The study's limitations include that AI technology is rapidly evolving, and private browsing sessions could not fully prevent language model training. The findings underscore the need for healthcare professionals and the public to confirm validation through independent registries like validatebp.org rather than relying on AI chatbots. As AI becomes more embedded in health information seeking, these results suggest that critical decisions about blood pressure monitoring should be based on trusted, human-verified sources to avoid misdiagnosis and inappropriate treatment.
