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How people see AI skills and job risk

Source reportMethodology

Overview

Adults are not dismissing AI at work. They are separating the value of AI skills from worry about what AI does to jobs.


About 54% say AI-tool skills are very or extremely important. But 69% say AI in the workplace will lead to fewer job opportunities, and 82% are concerned about AI taking jobs from humans.

Stacked breakdown

54% say AI-tool skills are very or extremely important.

- Skills to understand and use artificial intelligence tools or technology

Extremely important
21.6%
Very important
31.7%
Somewhat important
32.9%
Not too important
9.2%
Not at all important
4.7%

2025 · base n 1,509 · +/- 3.1%

AI Adoption Survey July 2025

View source data

AI skills are treated as important

Adults tend to see AI-tool skills as part of the workplace skill set. About 54% say skills to understand and use AI tools are very or extremely important.

Another 33% call those skills somewhat important, leaving relatively few adults who say they are not too important or not at all important.

Topline

69% expect fewer job opportunities from workplace AI.

In the long run, do you think the use of AI in the workplace will lead to…

  • Fewer job opportunities 68.5%
  • Will not make much difference 19.4%
  • More job opportunities 12.1%

2025 · base n 1,509 · +/- 3.1%

AI Adoption Survey July 2025

View source data

Additional supporting data from this section.

Stacked breakdown

82% are concerned about AI taking jobs from humans.

AI taking away jobs from humans

Extremely concerned
30.1%
Very concerned
22.2%
Somewhat concerned
30.1%
Not at all concerned
13.9%
I’m unfamiliar with this topic
3.8%

2025 · base n 1,509 · +/- 3.1%

AI Adoption Survey July 2025

View source data

The jobs read is much more cautious

The long-run jobs question points in the other direction. About 69% say AI in the workplace will lead to fewer job opportunities.

Concern about job displacement is also broad. Roughly 82% are at least somewhat concerned about AI taking jobs away from humans.

Excitement exists, but it does not settle the story

Adults are almost evenly split on whether they are excited about what AI brings to their work: 33% agree, 33% disagree, and 34% are neutral.

That makes the broader pattern practical rather than simply positive or negative. AI skills matter, but the job-risk concern is still the dominant public signal.

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Population
US adults age 18+
Field dates
2025-07-30 → 2025-08-04
Base (unweighted)
1,509
Margin of error
+/- 3.1%
Module
AI Adoption Survey July 2025
Sponsor
Verasight
Weight variable
weight
Weighting targets
age, race/ethnicity, sex, income, education, region, metropolitan status

Sources

[4]
  • 01
    - Skills to understand and use artificial intelligence tools or technologyShows AI-tool skills are broadly treated as important.reports.verasight.io/reports/ai-adoption-survey-july-2025
  • 02
    In the long run, do you think the use of AI in the workplace will lead to…Captures the strongest job-opportunity concern.reports.verasight.io/reports/ai-adoption-survey-august-2025
  • 03
    How concerned are you about the following issues surrounding AI? - AI taking away jobs from humansAdds the broader concern about AI taking jobs from humans.reports.verasight.io/reports/ai-adoption-survey-august-2025
  • 04
    Please indicate how much you agree or disagree with the following: - I’m excited about the possibilities AI brings to my workShows excitement at work is present but not dominant.reports.verasight.io/reports/ai-adoption-survey-august-2025

Citation

AI Adoption Survey July 2025, fielded July 30-August 4, 2025, N=1,509 US adults age 18+, +/- 3.1%.

https://reports.verasight.io/reports/ai-adoption-survey-july-2025#skills-to-understand-and-use-artificial-intelligence-tools-or-technology

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.