Headline: As Americans Get More Familiar With AI, They Grow More Skeptical — What That Means for Crypto A new Gallup report out Tuesday finds that Americans’ knowledge of artificial intelligence is rising — but so is public wariness. For crypto companies building AI tools, tokenizing AI services, or competing for talent, the survey spotlights a trust gap and job-concern dynamics that could shape adoption, regulation, and hiring. Key findings - Familiarity is up: 70% of Americans now say they’re somewhat or extremely knowledgeable about AI, up from 64% in 2024. - Growing skepticism: 39% say AI does more harm than good, up from 31% in 2025. Just 9% believe AI does more good than harm; 52% say it does equal amounts of harm and good. - Young adults lead the shift: Among 18–29 year-olds, nearly half now say AI does more harm than good (up from 36% last year). Younger adults also showed the biggest increases in skepticism about AI’s overall impact, businesses’ use of the tech, and its effect on jobs. - Trust in businesses falls: Only 27% of Americans say they trust businesses at least “some” to use AI responsibly, down from 31% in 2025. Trust among 18–29 year-olds dropped from 30% to 20%, while those expressing no trust at all rose from 29% to 41%. - Job fears intensify: 79% of Americans expect AI will reduce the number of U.S. jobs over the next decade (up from 73% in 2025). The largest jumps were among 18–29 year-olds (62% → 75%) and 45–59 year-olds (75% → 84%). - Performance perceptions: Americans increasingly say AI performs about as well as people on tasks like driving and offering financial or medical advice, but humans still score higher across every measured category — including hiring decisions, creative work, and tutoring students. Larger context — Americans remain uneasy Gallup’s findings echo other recent surveys showing a mixed relationship with AI. An NBC News poll in March found 56% of Americans had recently used AI tools (ChatGPT, Microsoft Copilot, Google Gemini) but 57% said AI’s risks outweigh the benefits. In June, Anthropic’s survey of nearly 52,000 U.S. adults found job losses were the top concern everywhere and only 15% trust AI companies to decide how the technology is developed and used. Why this matters to the crypto sector - Trust and governance: Declining trust in businesses to use AI responsibly suggests a potential opening for decentralized governance models, transparent on-chain audits, and token-based incentives that promise accountability. - Talent and labor: Widespread fear of job losses could intensify competition for skilled engineers and data scientists as both legacy tech and crypto firms pivot to AI — and influence public support for policies affecting hiring, automation, and retraining. - Product adoption: Crypto projects integrating AI-driven features (e.g., trading bots, on-chain oracles, AI-native DAOs) may face a more skeptical user base and higher scrutiny from regulators and community stakeholders. Clear communication about safety, limitations, and incentives will matter more. - Regulatory risk: Rising public concern about harm and job disruption increases political pressure for AI oversight — a risk for crypto firms that use or sell AI capabilities without robust guardrails. Bottom line Americans are getting smarter about AI — and more worried. For crypto builders and investors, that trend means reputational and regulatory risks but also opportunities: projects that prioritize transparency, accountable governance, and worker protections may win public trust where opaque corporate deployments fail.
Gallup Survey Shows Rising AI Skepticism in U.S., Implications for Crypto Sector
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A Gallup survey highlights rising AI skepticism in the U.S., with 39% of Americans now believing AI causes more harm than good, up from 31% in 2025. Concerns over job displacement and corporate trust could affect crypto projects using AI tools. Young adults show the most distrust, with 41% doubting responsible AI use by firms. Crypto projects emphasizing transparency may benefit, especially under MiCA and CFT frameworks.
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