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Young adults can use AI frequently and still worry about what it is doing to society, whether online content is genuine, and how scammers may exploit it. The evidence points to possible personal and social costs—not a single measurable “trust gap” or a proven economy-wide price tag.
Do young adults trust AI?
There is no single, standardized measure of an “AI trust gap” in the available surveys. Some studies ask whether people use chatbots, others ask what effects they expect from AI, and still others ask about scam exposure or whether online material seems authentic. Those answers describe different things and should not be combined into one trust score.
In a Pew Research Center survey fielded February 17–23, 2026, 66% of U.S. adults ages 18–29 said they had ever used AI chatbots. In the same age group, 48% expected AI to have a negative effect on society over the next 20 years, while 14% expected a positive effect. Those are expectations about future impact, not direct answers to whether respondents trust AI. Pew Research Center’s age analysis reports the findings.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesA separate Pew analysis found that the share of U.S. adults ages 18–34 who were more concerned than excited about AI increased from 40% in 2024 to 55% in 2026. Its cross-national reporting draws on surveys of 42,151 adults in 36 countries fielded February 8 to May 13, 2026, alongside separate U.S. data; its youth analysis is described as covering 37 countries. The age groups and country samples vary, so these results should not be treated as one globally uniform youth measure. Pew’s international analysis provides the scope and comparisons.
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Why do young people use AI if they are worried about it?
Use and concern can coexist. A person may find a chatbot convenient for tasks while remaining uneasy about AI’s broader effects, reliability, privacy implications, or misuse by others. The Pew figures show that chatbot use is common among surveyed U.S. adults ages 18–29 even as many in that age group expect a negative societal effect; they do not establish why any individual uses a chatbot or what trade-offs that person accepts.
It is also important to distinguish a broad outlook from a reported experience. Pew asks about use and expected effects; a survey published by Malwarebytes asks about experiences such as scam exposure and encountering misleading AI-generated information. The different questions and methods mean the findings are complementary context, not a contradiction or a trend line.
Are AI scams targeting young adults?
Malwarebytes reported that 70% of surveyed adults ages 18–22 across the United States, United Kingdom, Germany, Austria, and Switzerland said they had experienced an AI-related scam in the past year. Its company-described survey included 1,500 respondents and was fielded in March 2026. This is a self-reported result from a vendor-published survey, not an independently replicated estimate of all young adults or proof that AI alone caused each scam. Malwarebytes’ account of the survey gives its findings and context.
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The figure signals a concern worth taking seriously, but it does not show how many respondents lost money, what kinds of scams were involved, or whether the scams would have been impossible without AI. Malwarebytes Head of Consumer Mark Beare said, “The problem is that scammers are embracing it, too.” His comment reflects the company’s perspective, not an independent consensus statement.
How can I tell whether something online is AI-generated?
There is no reliable visual shortcut that proves a post, image, voice message, or video is AI-generated—or genuine. Instead, treat authenticity as a verification problem, especially when a message asks for money, credentials, urgent action, or personal information.
- Check the source. Find the original account, publication, organization, or creator rather than relying on a repost or screenshot.
- Verify consequential claims elsewhere. Look for confirmation from independent, reputable sources. A polished image or confident explanation is not evidence by itself.
- Confirm urgent requests through another channel. Contact the person or organization using a number, address, or app you already know, not the details in the suspicious message.
- Pause before clicking or paying. Be especially cautious with unexpected links, unfamiliar retailers, requests for gift cards or transfers, and pressure to act immediately.
- Protect accounts and devices. Use unique passwords, enable two-factor authentication, install software updates, and review social-account privacy settings and followers.
Malwarebytes’ malware research engineer Liz Wigglesworth described the burden of ongoing vigilance this way: “Remembering to opt out of new features that may not preserve my privacy and fact checking everything can be exhausting.” That is a vendor-affiliated observation, not a measured finding about all users. The practical steps above reduce avoidable exposure, but no checklist can guarantee that content is authentic or prevent every scam.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What could the high cost be—and what is not yet established?
The evidence supports examining potential costs to individuals and communities: time spent verifying content, exposure to scams, uncertainty about whether information is authentic, and the possibility that people may rely on consequential advice from systems whose limits they do not understand. These are plausible areas of harm, not a quantified total attributable to declining trust.
Malwarebytes reported that 44% of its surveyed adults ages 18–22 said they had encountered AI-generated information they later found to be false or misleading. That is a self-reported survey result; it does not establish the scale of downstream harm or show that AI generated all misleading content respondents encountered. Neither this result nor the Pew surveys calculate an aggregate economic cost caused by an AI trust gap, prove that AI alone caused reported harms, or show that every young adult distrusts AI.
The European Commission Joint Research Centre announced in July 2026 that it was conducting research aimed at chatbot users ages 13–25. The planned survey covers use, perceptions, trust, emotional support, life advice, and possible effects on child-parent relationships. The announcement describes research in progress, not results, so it cannot yet establish young users’ trust levels or effects on families. The JRC announcement sets out the study’s stated scope.
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