Report · AI & Tech

At home, people mostly use AI for writing and recommendations

Reading

Writing tasks anchor Americans' personal AI use: 45% of U.S. adults use AI for writing or editing personal messages, emails, or social media posts, and four-in-ten (40%) use it for recommendations on things like movies, restaurants, or gifts, according to a Verasight survey conducted July 30-Aug. 4, 2025.

Roughly a third each use AI for personal organization or for advice on health and fitness (32% each), and 28% turn to it for entertainment such as storytelling, games, or music. Smaller shares use it to plan a trip (20%) or manage their calendar (19%), another 14% cite other tasks, and one-in-ten (10%) say they do not use AI in their personal lives.

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Selected responses

At home, people mostly use AI for writing and recommendations.

When it comes to your personal life, what types of tasks do you use AI for?

  • Writing or editing personal messages, emails, or social media posts 45.1%
  • Getting recommendations (e.g., movies, restaurants, gifts) 40.0%
  • Personal organization 32.2%
  • Getting advice on health and fitness 32.1%
  • Entertainment (e.g., storytelling, games, music) 28.2%
  • Planning a trip 19.9%
  • Managing your calendar and scheduling 18.6%
  • Other (please specify): 13.8%
  • I do not use AI for my personal life 10.4%

2025 · base n 993 · +/- 3.8%

AI Adoption Survey July 2025

Source report pending

Methodology

Source report pending
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2025-07-30 → 2025-08-04
Base (unweighted)
993
Margin of error
+/- 3.8%
Module
AI Adoption Survey July 2025

Source

  • 01
    Source report pending

Citation

AI Adoption Survey July 2025, fielded July 30-August 4, 2025, N=993 US adults age 18+, +/- 3.8%.

Source report pending

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.