New YouGov data punctures a comfortable assumption: if people use AI, they must trust it. The numbers tell a different story. 89% of U.S. adults hold at least one concern about AI, yet 55% still use AI tools at least weekly. That gap is now the marketing problem to plan around.
As MIT Technology Review’s Will Douglas Heaven framed it, around the world a “love/hate attitude toward AI” is the prevailing vibe.
The numbers show ambivalence, not rejection
Among the 11% of U.S. adults with no AI concerns, 61% use AI weekly. Among the 89% who do have concerns, usage is still 55%. Concern does not predict avoidance, and use does not equal approval.
The worries are specific enough to act on:
- 63% cite privacy and data security
- 53% worry about over-reliance on AI
- 48% distrust AI companies
- 46% question the reliability or accuracy of AI outputs
Pew Research Center’s June 2026 survey adds context: 52% of U.S. adults are more concerned than excited about AI in daily life, while 37% feel both ways equally and only 9% are more excited. The concern figure has hovered near 52% since 2023, so this is not a passing panic.
Usage frequency splits your audience into camps
The sharpest divide is by how often people use AI. 52% of weekly users say AI’s impact on society has been positive, against 22% negative. Below monthly use, positivity drops to 10%; among people who never use AI, it falls to 6%. But as YouGov’s Rishad Dsouza notes, “concern about the technology and willingness to use it can coexist.”
That means you cannot treat AI usage as a vote of confidence. It is a segmentation signal. A landing page built for a daily user will miss someone who has never opened a chatbot.
What to change in your content plan
First, add a usage-frequency question to your next survey and cut every result by it. Weekly users and non-users are not the same audience, so one averaged message will be wrong for both.
Second, answer the concerns actually on the table. You cannot fix distrust of AI companies with a blog post, but you can address privacy and accuracy directly: link the primary source for each statistic, name the author, date the data, and say plainly what happens to user data in any AI feature you offer.
Third, test candor. Heaven’s closing hope was for “Clarity about what AI can and cannot do.” Run a landing page that states your product’s limits against one that promises everything. Measure qualified leads and sales conversations, not just click-through. The plainer page may well win with an audience where 89% already carry a worry.
The gap between use and trust has held steady since 2023. Marketers who treat it as a structural condition rather than a glitch will build content that survives AI-mediated discovery.
Source: Search Engine Journal
