Report · AI & Tech

Workers often see AI as useful in their line of work

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Nearly four-in-ten Americans (38%) think AI is useful in their profession, more than express any other reaction to it, according to an October 2024 Verasight survey.

Smaller shares have ethical concerns about using AI for their job or want to learn more about it for their profession (17% each), while 10% are scared it might take their job. Nearly a third (31%) say none of these fits how they see it.

Topline

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Selected responses

Workers often see AI as useful in their line of work.

How do you see AI in relation to your profession?

  • I think AI is useful 37.7%
  • None of the above 30.6%
  • I have ethical concerns using AI for my job 17.4%
  • I want to learn more about AI for my profession 16.7%
  • I’m scared that AI might take my job 10.5%

2024 · base n 1,000 · +/- 3.4%

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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
2024-10-01 → 2024-10-11
Base (unweighted)
1,000
Margin of error
+/- 3.4%
Module
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Source

Citation

Verasight APSA Omnibus Survey #2024-103, fielded October 1-11, 2024, N=1,000 US adults age 18+, +/- 3.4%.

https://verasight-apsa-2024.tiiny.co

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.