Report · AI & Tech

68% of Americans expect AI to cause widespread job losses within the next decade

Reading

Americans broadly expect AI to take a heavy toll on employment: more than two-thirds (68%) agree it will cause widespread job losses for American workers within the next ten years, including 26% who agree strongly.

One-in-five (21%) stay neutral, while just 11% disagree, including 1% who strongly disagree, according to a June 2026 Verasight survey.

Topline

response scale

Topline scale

68% of Americans expect AI to cause widespread job losses within the next decade.

Please indicate the extent to which you agree or disagree the following statement: In the next ten years, AI will cause widespread job losses for American workers.

  • Agree 42.1%
  • Strongly agree 26.1%
  • Neither agree nor disagree 21.0%
  • Disagree 9.4%
  • Strongly disagree 1.3%

2026 · base n 1,000 · +/- 3.2%

3

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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
2026-06-21 → 2026-06-21
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
3

Source

Citation

Verasight MPSA Omnibus Survey #2026-050, fielded June 21-21, 2026, N=1,000 US adults age 18+, +/- 3.2%.

https://reports.verasight.io/r/mpsa26

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.