Report · AI & Tech

Most working Americans use little or no AI on the job

Reading

Nearly half of Americans (45%) have a job in which AI barely figures, combining the 26% who use no AI at all in their work with the 19% who use a little, according to an August 2025 Verasight survey.

A smaller share (24%) use it more heavily, including 13% who use AI for some of their tasks, 9% for a lot of them, and 2% for everything they do. Another 31% don't currently have a job.

Topline

single choice

Topline distribution

Most working Americans use little or no AI on the job.

Thinking of the tasks you do in your job, how much do you use AI in your work?

  • I don't currently have a job 31.3%
  • None 25.5%
  • A Little 19.2%
  • Some 13.4%
  • A lot 8.7%
  • Everything 1.8%

2025 · base n 1,000 · +/- 3.1%

ASA Omnibus Survey

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
2025-08-20 → 2025-08-25
Base (unweighted)
1,000
Margin of error
+/- 3.1%
Module
ASA Omnibus Survey

Source

Citation

ASA Omnibus Survey, fielded August 20-25, 2025, N=1,000 United States adults, +/- 3.1%.

https://reports.verasight.io/r/asa-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.