Americans Increase Use of AI For Health Advice

According to KFF's June 17, 2026 tracking poll (conducted May 7-31, 2026, n=2,480), 29% of U.S. adults now use AI tools or chatbots -- including ChatGPT, Google Gemini, and Claude -- for health information or advice on a monthly basis. KFF reports that share has nearly doubled in two years, up from roughly one in six (17%) in June 2024. About 31% of adults use social media for health information at least once monthly, including about one in six (16%) who say they do so "every day," according to KFF. A majority of adults say they "never" or only "occasionally" use AI tools (71%) or social media (69%) for medical information. (KFF, June 2026)

KFF reports that among adults who use social media for health information and advice, relatively few follow up with other sources to verify accuracy. Fewer than four in ten say they follow up with a doctor or health care professional (36%) "every time" or "most of the time," consult another online source like WebMD (35%), or check with health agency websites like the CDC (21%) after using social media for health queries. A majority of social media users say they either "some of the time," "rarely," or "never" followed up with a health care provider (64%), consulted another online source (65%), or checked a government health agency website (78%).

Among social media users, the top reasons cited as "major" include wanting to learn from people with the same health condition or shared experiences (36%) and wanting immediate information or support (35%). KFF's earlier March 2026 poll found that for AI health users, the primary driver was also speed and immediacy (65%), while about 1 in 5 cited affordability or access barriers as a major factor -- rising to roughly a third among uninsured and lower-income adults. KFF notes that Black and Hispanic adults and younger adults (ages 18-29) are among the most likely to use social media for health information. (KFF March 2026 AI poll; KFF June 2026 Social Media and AI poll)

Consumer adoption metrics from public polls indicate growing reliance on general-purpose conversational models and social platforms for initial medical queries. For practitioners, that trend increases the frequency of patient-sourced diagnostic suggestions arriving in clinical settings and raises the operational need for clinicians and health systems to validate or correct externally generated guidance. The low follow-up verification rates shown in the KFF data suggest patients often treat AI or social sources as a definitive source rather than a first step, which has implications for triage, documentation, and patient education.

For practitioners: monitor whether patient-sourced AI guidance changes care-seeking behavior, creates additional confirmatory workload, or affects diagnostic timelines. Observers should track follow-up studies from KFF or health-system analytics that break down use by condition and whether AI-driven queries led to clinical encounters or delays. Policymakers and professional societies may develop guidance for documenting patient-reported AI outputs and patient education about limitations of consumer-facing chatbots.