Report · AI & Tech

AI disruption of entry-level office jobs seems likely to most Americans

Reading

In a Verasight survey of 1,000 U.S. adults conducted Dec. 3 to 8, 2025, 76% of Americans said they expect artificial intelligence to disrupt entry-level white-collar jobs at least a moderate amount in the next 5 years. Including 30% who said a moderate amount, 24% who said a lot, and 22% who said a great deal.

About one in seven said they expect a little or no disruption (15%), with 12% who said a little and 3% who said no disruption at all. Another 9% said they were not sure.

Topline

response scale

Topline scale

76% of Americans expect AI to disrupt entry-level white-collar jobs at least a moderate amount.

How much do you think artificial intelligence (AI) will disrupt entry-level white-collar jobs in the next 5 years?

  • A moderate amount of disruption 29.6%
  • A lot of disruption 24.5%
  • A great deal of disruption 22.2%
  • A little disruption 11.8%
  • I'm not sure 8.8%
  • No disruption at all 3.2%

2025 · base n 1,000 · +/- 3.2%

tech_behavior

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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
2025-12-03 → 2025-12-08
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
tech_behavior

Source

  • 01
    AI disruption of entry-level office jobs seems likely to most Americansreports.verasight.io/reports/verasight-human-llm-comparison-survey-2025-172

Citation

Verasight Human/LLM Comparison Survey #2025-172, fielded December 3-8, 2025, N=1,000 US adults age 18+, +/- 3.2%.

https://reports.verasight.io/reports/verasight-human-llm-comparison-survey-2025-172#how-much-do-you-think-artificial-intelligence-ai-will-disrupt-entry-level-white-collar-jobs-in-the-next-5-years

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.