Report · AI & Tech

Turning to AI when distressed remains unlikely

Reading

In a Verasight survey of 1,519 U.S. adults conducted Sept. 3 to 8, 2025, 75% of Americans said they would be unlikely to consult an AI assistant before reaching out to a human if they felt significantly distressed. Including 55% who said not at all likely and another 20% who said not very likely.

About one in five said they are at least somewhat likely to turn to AI first (18%), with 13% who said somewhat likely and another 5% who said very likely. Another 7% said they are not sure.

Topline

response scale

Topline scale

75% of Americans say they would not turn to AI when distressed.

If you felt significantly distressed tonight, how likely is it that you would consult an AI assistant before reaching out to a human?

  • Not at all likely 55.2%
  • Not very likely 20.2%
  • Somewhat likely 13.3%
  • Not sure 6.6%
  • Very likely 4.8%

2025 · base n 1,519 · +/- 3.3%

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)
1,519
Margin of error
+/- 3.3%
Module
AI Adoption Survey August 2025

Source

  • 01
    Turning to AI when distressed remains unlikelyreports.verasight.io/reports/ai-adoption-survey-august-2025

Citation

AI Adoption Survey August 2025, fielded September 3-8, 2025, N=1,519 United States adults, +/- 3.3%.

https://reports.verasight.io/reports/ai-adoption-survey-august-2025#if-you-felt-significantly-distressed-tonight-how-likely-is-it-that-you-would-consult-an-ai-assistant-before-reaching-out-to-a-human

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. Each wave's specific field dates, sample sizes, and module breakdown are listed in that wave's 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
Every wave is published as a standalone report at verasight.io/reports with full instrument and methodology.
Transparency
AAPOR transparency standards.

Wave-specific methodology, full weighting variable lists, and verbatim instrument text live in each report at verasight.io/reports.