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People use AI tools because they can save time or help with a task, even when they doubt the tools’ accuracy, privacy, or broader effects. Using AI is not the same as trusting every answer: someone may welcome help drafting or summarising while keeping control of consequential decisions.
Use and trust are different measures
Use describes whether, how recently, or how often someone turns to an AI tool. Trust can mean confidence in its answers, willingness to rely on its output, belief that it handles information safely, or readiness to share data so it can work. A person can use a tool without granting it all of those forms of trust.
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The University of Melbourne and KPMG’s 2025 global study illustrates the gap: 66% of respondents reported intentional regular AI use for personal, work, or study purposes, while 46% were willing to trust AI systems. In that study, trust covered willingness to rely on outputs or share information to enable a system to work. These figures describe different measures, not a contradiction or proof that distrust causes use.
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People often turn to AI for bounded, practical help: getting a first draft, generating ideas, summarising material, or explaining information. These uses can be worthwhile even if the user plans to check the result. The tool can reduce effort without becoming the final authority.
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In the UK Department for Science, Innovation and Technology’s 2025/2026 survey, 59% of UK adults said they had used generative AI in the previous three months. Among identified users who answered the online questionnaire, 65% said they used it to save time, 55% for ideas or inspiration, and 48% to summarise or explain something. The motivation figures apply to that online questionnaire, not the full paper-and-online sample.
That kind of use has a lower commitment than handing over a decision. A person can ask for possible wording, compare suggestions with other information, and discard an answer that seems wrong. In practical terms, the expected benefit may be immediate while the user retains the option to verify or ignore the output.
Concern and perceived benefit can coexist
Having reservations does not mean someone sees no value. In the University of Melbourne and KPMG’s 2025 global study, 73% reported some benefits from AI use in society, while 79% were concerned about negative outcomes. In the UK DSIT survey, 74% of UK adults perceived inaccurate information as an AI risk and 69% perceived privacy or security as a risk.
Concern can shape how someone uses a tool rather than stop use altogether. A user might avoid entering sensitive details, check factual claims, or limit AI to low-stakes tasks. Survey findings describe reported attitudes and behavior; they do not establish one cause for any individual’s choices.
Willingness depends on the task and its stakes
Trust is often conditional. A suggestion for a routine email or a summary to review is different from advice that could affect someone’s health or finances. The cost of an error, the ability to verify the result, and the amount of personal information involved can all matter to a user’s decision about whether to rely on AI.
A Bank for International Settlements bulletin based on a representative U.S. household survey reports: “Nonetheless, all groups trust gen AI less than humans, especially in the provision of financial and medical services.” This supports a distinction between everyday assistance and consequential services; it does not mean every person draws the boundary in the same way.
Pew Research Center’s survey of 5,023 U.S. adults, conducted 9–15 June 2025, found that nearly three-quarters would be willing to let AI assist at least a little with day-to-day tasks. At the same time, half were more concerned than excited about AI’s increased use in daily life, and about six in ten wanted more control over how AI is used in their own lives. The results show that limited assistance can be acceptable alongside concern and a desire for oversight.
What the surveys can—and cannot—tell us
These findings come from different countries, samples, field dates, survey modes, and question wording. “Regular use,” use in the previous three months, willingness to receive assistance, and willingness to trust are not interchangeable measures. They should not be read as a single trend line or as a direct comparison of national attitudes.
The University of Melbourne and KPMG’s 2025 study also reports higher regular use and trust in its emerging-economy group than in advanced economies. That is a study finding, not a universal rule, and it does not by itself explain why the groups differ. More broadly, survey results capture stated use, motivations, trust, and concern; they do not establish a single psychological mechanism behind the coexistence of use and distrust.
Quick Recap
- The University of Melbourne and KPMG, “Trust, attitudes and use of artificial intelligence: A global study 2025”
- Pew Research Center, “How Americans View AI and Its Impact on Human Abilities, Society”
- UK Department for Science, Innovation and Technology, “DSIT Public Engagement Survey 2025/2026”
- Bank for International Settlements, “Survey evidence on gen AI and households: job prospects amid trust concerns”
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