Changes in AI health consultations are beginning to reflect in behaviors such as whether people seek medical care, when they do so, and how they communicate with doctors. We have compiled five public research studies published in 2026 by KFF, West Health–Gallup, JMIR, BCG, and AXA Health, covering the United States, the United Kingdom, China, and 15 other countries. Some data was collected in 2025; sample sizes and definitions of “AI users” vary across sources, so the percentages are intended only to observe common phenomena, not to be ranked horizontally or compared directly.
Research Background
Previously, measurement focused primarily on usage rates and information accuracy. Public data from 2026 adds another dimension: whether users change appointments, delay care, increase visits, or adjust communication methods after receiving answers. This research examines the role of AI in symptom assessment, pre-visit preparation, and post-visit comprehension. Factors such as cost, service accessibility, and personal trust must also be considered concurrently.
AI Health Consultation Has Entered a Phase of Widespread Use
Surveys using different methodologies collectively show that AI health consultation is no longer limited to early adopters. A KFF survey of 1,343 people published in March 2026 found that 32% of U.S. adults had used AI for health information in the past year, compared to 29% who used social media for the same purpose. A West Health–Gallup survey published in April 2026, covering over 5,500 people, reported a rate of 25%, with data collected between October and December 2025.
A BCG report from April 2026 indicated that nearly 60% of respondents had used generative AI or AI tools for health-related matters, based on a November 2025 survey of 13,353 connected consumers across 15 countries. The three sets of figures differ in market coverage, tool scope, and user definitions; they cannot represent sustained reliance levels nor be used to judge market development speed.
AI Is Becoming Embedded in Pre- and Post-Visit Decision Processes
The change in AI health consultation is not just about how many people use it, but whether it alters users' subsequent medical behaviors.
The West Health–Gallup 2026 report shows that 59% of recent users research before seeing a doctor, and 56% look up information after their visit; 14% have skipped a medical appointment in the past 30 days due to AI information. An AXA Health survey from the UK in April 2026 found that among AI symptom checker users, 59% have delayed seeking care due to reassurance, while another 59% have sought medical help they later felt was unnecessary due to worry; 36% turn to AI first when symptoms arise, compared to 19% who visit the NHS website first. These self-reported behaviors reflect correlations and cannot be interpreted as AI being the sole cause of the outcomes.
| Market / Scope | Source & Date | Survey Subjects / Sample | AI Usage Point | Key Behavioral Data | Reading Limitations |
|---|---|---|---|---|---|
| United States | KFF, March 2026 | 1,343 adults | Obtaining health information | 32% used in the past year | Not directly comparable to recent users |
| United States | West Health–Gallup, published April 2026; surveyed Oct–Dec 2025 | Over 5,500 adults / recent users | Pre-/post-visit and care-seeking decisions | 59% used before visit, 56% after visit, 14% skipped a visit | Includes self-reported data |
| United Kingdom | AXA Health, April 2026 | 2,000 AI users and non-users | Symptom assessment and care choices | 59% delayed care, 59% sought additional medical help | Based on experiences of AI users |
| China | JMIR, published February 2026; surveyed Dec 2024 – May 2025 | 2,460 valid questionnaires & simulations | Trust, usage, and delayed care | Adjusted OR 1.09; usage frequency OR 1.39–1.40 | Correlation and simulation do not equal causation |
| 15 countries | BCG, published April 2026; surveyed November 2025 | 13,353 connected consumers | Health and wellness consultations | Nearly 60% had used generative AI or AI tools | Tool scope differs from single-country surveys |
Comprehension and Communication Confidence Rise, Alongside Trust, Misinformation, and Privacy Risks
AI's benefits and risks can co-exist. The AXA Health 2026 UK survey shows that 78% of AI users find the tools help them understand medical terminology, test results, or treatment plans, and 68% feel more confident discussing symptoms; however, 25% have encountered incorrect or misleading information. Subjective understanding and factual accuracy are distinct metrics.
The JMIR 2026 China study is based on 2,460 valid questionnaires and simulations. In the adjusted model, the odds ratio for AI trust leading to delayed care is 1.09, for usage frequency is 1.39, and 1.40 in the mediation model. Convenience sampling and correlational studies cannot prove causation. The KFF March 2026 survey also shows that 77% of the U.S. public worries about the privacy of their medical information; among AI health information users, 41% have uploaded test results or doctor's records, representing 13% of the entire adult sample. Convenience needs and risk perception can coexist.
Measurement is evolving from “how many people use it” to “at which stage they use it” and “what actions they take afterwards.” Information sources, risk boundaries, privacy notices, and medical referral reminders should also be incorporated into the analytical framework.
Implications for Research
Future observations could categorize data into four layers:
- Reach: Number of users, statistical period, and user definitions.
- Stage: Symptom assessment, pre-visit preparation, or post-visit comprehension.
- Behavior: Whether appointment scheduling, delays, cancellations, or increased visits occur.
- Risk: Whether misinformation, privacy uploads, or over-reliance appear.
Healthcare and wellness brands can also inspect the answer sources, brand information accuracy, and medical risk boundaries within AI engines such as ChatGPT, Gemini, and Perplexity.
When users begin turning to AI engines like ChatGPT, Gemini, and Perplexity to understand health issues, brands should first verify how their information is actually represented in the answers. With aipogeo, you can check your real visibility across 6 major AI engines in 1 minute, and review brand mentions, citation sources, and answer performance across different questions.
Related Questions
How have AI health consultations already influenced medical decisions?
AI now plays a role in symptom queries, decisions on whether to seek care, pre- and post-visit understanding, and communication. Some users report having changed their medical behaviors, but this cannot be attributed to AI alone.
What percentage of U.S. adults use AI to obtain health information?
The KFF March 2026 survey reported 32%, while the West Health–Gallup survey published in April 2026 reported 25%; the two surveys use different methodologies.
Does using AI health advice increase the likelihood of delaying medical care?
The JMIR 2026 study observed a correlational link, reporting an adjusted OR of 1.09 and a usage frequency OR of 1.39, but it cannot prove causation.
Why do users worry about medical privacy yet still upload health information to AI?
Users may want to quickly understand their medical information while simultaneously being concerned about how that data is used. KFF data shows that both feelings can coexist.