1 in 4 Americans Asked an AI Chatbot for Medical Advice Because They Couldn't Afford a Doctor, Survey Finds

Rising healthcare costs are pushing more Americans to look for alternatives when they can’t afford to see a doctor. While chatbots are commonly used to understand health insurance coverage, compare plans, and make sense of medical bills, a growing number of Americans are now relying on them for something much more consequential, medical advice.

An Insuranceopedia Health Insurance & AI Survey found that one in four insured Americans turned to an AI chatbot for medical advice in the past year because they couldn’t afford to see a doctor.

Gen Z Is Driving the Shift, with More than Half Turning to AI When They Can’t Afford a Doctor

According to the U.S. Centers for Medicare & Medicaid Services, Americans’ out-of-pocket healthcare spending is projected to have reached $591 billion in 2025, up $34 billion in a single year and roughly $202 billion more than five years ago. As healthcare becomes increasingly expensive, more Americans are looking for lower-cost alternatives to traditional medical care, and a growing number are turning to AI chatbots.

Insuranceopedia surveyed 1,250 insured U.S. adults to better understand how Americans are using artificial intelligence in healthcare, revealing that AI is no longer just a tool for navigating the healthcare system but is increasingly being used for higher-risk health decisions.

According to the survey, one in four Americans (25%) said they asked an AI chatbot a medical question in the past year because they couldn’t afford to see a doctor, making it the single most common AI healthcare use measured in the survey.

By comparison, 22% used AI to better understand their health insurance coverage, 19% sought help interpreting medical bills, and 16% used it to compare health insurance plans. Appealing a denied insurance claim ranked last, with just 8% saying they had used AI for that purpose.

The survey also found age was one of the clearest dividing lines, with younger Americans far more likely to turn to AI when they couldn’t afford to see a doctor. In fact, no age group embraced AI for medical advice more than Gen Z. More than half (53.1%) of adults ages 18–24 said they had asked an AI chatbot for medical advice because they couldn’t afford to see a doctor.

Millennials weren’t far behind, with 41.2% of adults ages 25–34 and 38.2% of those ages 35–44 turning to AI for medical advice. The trend then weakened among Gen X, falling to 28.4% for adults ages 45–54 and 16.1% for those ages 55–64, before bottoming out at just 6.8% among adults 65 and older.

“When healthcare becomes too expensive, AI starts filling a gap it was never meant to replace. The fact that so many younger Americans are turning to AI because they can’t afford to see a doctor shows how rising healthcare costs are changing people’s behavior,” said Max Coupland, CEO at Insuranceopedia.

AI Replacing Doctors isn’t Just a Low-Income Problem

While younger Americans were the most likely to turn to AI, the survey found the trend wasn’t limited to the lowest-income households, meaning age may play a bigger role than income in who turns to AI for medical advice.

In fact, some of the highest rates came from middle-income households. For example, 40% of respondents earning $45,000–$49,999 a year said they had asked an AI chatbot for medical advice because they couldn’t afford to see a doctor, followed by 35.4% of those earning $70,000–$74,999.

Lower-income households also reported high usage, including 32.8% of those earning $20,000–$24,999, 30.9% earning $30,000–$34,999, and 27.5% of respondents earning less than $5,000.

Perhaps even more concerning, four in ten respondents who asked AI a medical question because they couldn’t afford to see a doctor went a step further, saying they had skipped, delayed, or sought treatment based solely on the chatbot’s advice.

Methodology

Insuranceopedia surveyed 1,250 U.S. adults who currently hold health insurance, using the Pollfish online panel, in July 2026. Respondents were screened to confirm active coverage (employer, marketplace/ACA, Medicaid, Medicare, or private), and the sample was balanced to the U.S. adult population on age and gender. The margin of error for the full sample is approximately plus or minus 2.8 percentage points at the 95% confidence level. Results for subgroups, such as individual age or income bands, are based on smaller samples and carry wider margins, so they should be read as directional. Figures are unweighted and percentages are rounded, so totals may not always sum to 100%.