Changes in AI health consultations are now reflected in behaviors such as whether to seek medical care, when to do so, and how to communicate with doctors. We have compiled five public research studies released in 2026 by KFF, West Health–Gallup, JMIR, BCG, and AXA Health, covering the US, UK, China, and 15 countries. Some data was collected in 2025; sample sizes and definitions of “AI users” vary by source, and percentages are used only to observe common trends, not for simple cross-market rankings.
Research Background
Past measurements focused primarily on usage rates and information accuracy. Public data from 2026 adds another dimension: whether users who receive answers change their appointments, delay care, seek additional consultations, or adjust communication methods. This study examines AI’s role in symptom assessment, pre-visit preparation, and post-visit understanding; factors such as cost, service accessibility, and personal trust must also be considered simultaneously.
AI Health Consultations Have Entered the Stage of Scaled Adoption
Surveys with varying methodologies collectively show that AI health consultations are no longer confined to a small group of early adopters. A KFF survey of 1,343 people released in March 2026 found that 32% of US adults had used AI for health information in the past year; 29% used social media for health information. The West Health–Gallup survey released in April 2026, covering over 5,500 people, found a rate of 25%, with data collected between October and December 2025.
A BCG report released in April 2026 indicates 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. Due to differences in markets, tool scopes, and user definitions across the three datasets, these figures cannot be interpreted as continuous reliance levels or used to judge market development speed.
AI Is Embedding Itself Into the Decision-Making Process Before and After Medical Visits
The change in AI health consultation isn't just about how many people use it—it's about whether it alters users' subsequent medical actions.
The West Health–Gallup 2026 report shows that among recent users, 59% research before seeing a doctor and 56% look up information afterward; 14% have skipped a doctor's visit in the past 30 days due to AI information. AXA Health's UK survey from April 2026 shows that 59% of AI symptom-check users delayed seeking care due to reassurance, and the same 59% sought medical help they later deemed unnecessary due to worry; 36% turn to AI first when symptoms appear, while 19% visit the NHS website first. These self-reports reflect correlation only and cannot be interpreted as AI being the sole cause of outcomes.
| Market/Scope | Source & Date | Survey Population or Sample | AI Usage Stage | Key Behavioral Data | Reading Limitations |
|---|---|---|---|---|---|
| US | KFF, March 2026 | 1,343 adults | Obtaining health information | 32% used in past year | Not directly comparable to recent users |
| US | West Health–Gallup, released April 2026; surveyed Oct–Dec 2025 | Over 5,500 adults/recent users | Before/after visits and whether to seek care | 59% used before visit, 56% after visit, 14% skipped visits | Includes self-reported data |
| UK | 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 AI user experiences |
| China | JMIR, released 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 are not causation |
| 15 countries | BCG, released April 2026; surveyed November 2025 | 13,353 connected consumers | Health and wellness consultations | Nearly 60% used generative AI or AI tools | Tool scope differs from single-country surveys |
Understanding and Communication Confidence Rise, Alongside Trust, Misinformation, and Privacy Risks
AI's benefits and risks can emerge simultaneously. AXA Health's 2026 UK survey shows that 78% of AI users find the tools helpful for understanding medical terminology, test results, or treatment plans, and 68% feel more confident discussing symptoms; 25% reported receiving incorrect or misleading information. Subjective understanding and factual accuracy are distinct metrics.
JMIR's 2026 Chinese study is based on 2,460 valid questionnaires and simulations. In the adjusted model, the odds ratio for AI trust and delayed care was 1.09, for usage frequency 1.39, and in the mediation model 1.40. Convenience sampling and correlational studies cannot prove causation. The KFF March 2026 survey also shows that 77% of the US public worries about the privacy of medical information; among AI health information users, 41% had uploaded test results or doctor's records, equivalent to 13% of the overall adult sample. Convenience and risk perception can coexist.
Measurement is shifting from “how many people use it” to “at which stage they use it” and “what actions they take afterward.” Information sources, risk boundaries, privacy prompts, and medical care reminders should also be incorporated into the analytical framework.
Research Implications
Future observations can break data down into four layers:
- Reach: number of users, statistical period, and user definitions.
- Stage: symptom assessment, pre-visit preparation, or post-visit understanding.
- Behavior: whether appointments are changed, delayed, canceled, or increased.
- Risk: whether misinformation, privacy uploads, or over-reliance occurs.
Healthcare-related brands can also audit the answer sources, brand information accuracy, and medical risk boundaries within AI engines like ChatGPT, Gemini, and Perplexity.
As users begin understanding health issues through AI engines like ChatGPT, Gemini, and Perplexity, brands can first verify how their information is actually presented in the answers. With aipogeo, you can check your real visibility across 6 major AI engines in just 1 minute, and see brand mentions, citation sources, and answer performance for different questions.
Related Questions
What medical decisions has AI health consultation already influenced?
It is now involved in symptom searches, decisions on whether to seek care, understanding before and after visits, and communication. Some users report changing their medical behavior, but this cannot be solely attributed to AI.
What percentage of US adults use AI to obtain health information?
The KFF March 2026 survey found 32%, while the West Health–Gallup survey released in April 2026 found 25%; the methodologies differ.
Does using AI health advice increase the likelihood of delaying medical care?
The JMIR 2026 study observed a correlation, reporting an adjusted OR of 1.09 and usage frequency OR of 1.39, but cannot prove causation.
Why do users worry about medical privacy yet still upload health data to AI?
Users may want quick explanations of their medical data while simultaneously worrying about how it's used. KFF data shows these two conditions can coexist.