Report · AI & Tech

Americans only somewhat trust AI health advice

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Americans keep their guard up when AI offers health guidance. Just 14% of U.S. adults place high trust in recommendations from large language models such as ChatGPT, Gemini and Grok for lifestyle changes to improve their health, including 4% who say they trust them extremely, according to an August 2025 Verasight survey.

Cooler responses dominate: 32% trust these tools moderately, 26% only slightly and 25% not at all, while 3% prefer not to answer.

Topline

single choice

Topline distribution

Americans only somewhat trust AI health advice.

How much do you trust AI (Large Language Models such as ChatGPT, Gemini, and Grok) when it comes to its recommendations for lifestyle changes to improve your overall health?

  • Moderately 31.9%
  • Slightly 26.5%
  • Not at all 24.7%
  • Very 10.0%
  • Extremely 4.4%
  • Prefer not to answer 2.5%

2025 · base n 1,000 · +/- 3.1%

Verasight JSM Omnibus Survey

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Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2025-08-13 → 2025-08-18
Base (unweighted)
1,000
Margin of error
+/- 3.1%
Module
Verasight JSM Omnibus Survey

Source

Citation

Verasight JSM Omnibus Survey, fielded August 13-18, 2025, N=1,000 United States adults, +/- 3.1%.

https://reports.verasight.io/r/jsm-2025

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. When a wave report is published, its field dates, sample sizes, and module breakdown are listed in that report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
The canonical report hub is reports.verasight.io. Verified legacy reports remain on their original hosts, and unpublished reports are marked pending.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

The canonical report hub is reports.verasight.io; older reports may remain on verified legacy hosts.