Report · AI & Tech

People worry most about young people leaning on AI too much

Reading

Dependence sits at the top of Americans' concerns about students using AI in K-12 education. A November 2025 Verasight survey finds 53% worry that students will become dependent on the technology.

Concerns that AI has limitations and can return inaccurate results follow at 42%, and 40% believe students will learn less if AI is used. Roughly three-in-ten point to the policies surrounding AI use in education (31%) or to risks for teachers' careers (28%), while 20% cite environmental damage and 19% say they do not have enough information on the topic.

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Selected responses

People worry most about young people leaning on AI too much.

What concerns do you have surrounding youth artificial intelligence (AI) use in K-12 education?

  • Over reliance on AI: I believe that they will become dependent on AI. 53.5%
  • Accuracy concerns: I believe that AI has limitations and can provide inaccurate results 41.7%
  • Reducing their potential: I believe that they will learn less if AI is being used. 39.7%
  • Policy concerns: I have concerns regarding the policies surrounding AI use in education 31.0%
  • Teacher career: I believe that the careers of teachers can be at-risk if AI is used in education. 28.0%
  • Environmental damage: I believe that the damage to the environment when using AI is greater than the reward surrounding 20.3%
  • Lack of knowledge on the topic: I believe that I do not have enough information on the topic 19.2%

2025 · base n 1,000 · +/- 3.2%

Module 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
2025-11-14 → 2025-11-20
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
Module 3

Source

Citation

Verasight APHA Omnibus Survey #2025-148, fielded November 14-20, 2025, N=1,000 US adults age 18+, +/- 3.2%.

https://reports.verasight.io/r/verasight-apha-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
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Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

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