Report · AI & Tech

Most Americans who use AI for mental health feel little attachment to it

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Even Americans who have turned to AI for emotional support mostly keep it at arm's length. In a September 2025 Verasight survey, 56% of U.S. adults who have used an AI tool for mental health or emotional support say they feel little or no attachment to the AI they use most, including 40% who feel none at all.

Nearly a quarter (24%) say they feel somewhat attached, and 16% feel very or extremely attached, including 3% who say they are extremely attached. Another 5% say they don't use an AI assistant.

Topline

single choice

Topline distribution

Most Americans who use AI for mental health feel little attachment to it.

Thinking about any AI you use most often, how emotionally attached do you feel to it?

  • Not at all 39.8%
  • Somewhat 23.5%
  • A little 16.4%
  • Very 12.1%
  • I don’t use an AI assistant 4.7%
  • Extremely 3.5%

2025 · base n 353 · +/- 6.8%

AI Adoption Survey August 2025

View source

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2025-09-03 → 2025-09-08
Base (unweighted)
353
Margin of error
+/- 6.8%
Module
AI Adoption Survey August 2025

Source

Citation

AI Adoption Survey August 2025, fielded September 3-8, 2025, N=353 United States adults, +/- 6.8%.

https://reports.verasight.io/r/august-ai-survey-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.