Gen Z Expresses Growing Skepticism Toward AI

A national survey led by Gallup in partnership with the Walton Family Foundation and GSV Ventures finds that Generation Z is becoming measurably more negative about artificial intelligence even as adoption remains stable. The poll of 1,572 U.S. respondents aged 14 to 29, fielded Feb. 24-March 4, 2026 using the Gallup Panel, reports that 51% use generative AI at least weekly. Emotional responses shifted sharply year over year: anger rose to 31% (+9 points), excitement fell to 22% (-14 points), and hopefulness dropped to 18% (-9 points), while anxiety stayed near 42%.

The survey is probability-based with a margin of sampling error of ±3.6 percentage points for the full sample, and larger margins for subgroups. The report segments respondents by age, education status, and usage frequency; even daily users showed declines in favorable emotions. The findings cite controlled experimental and neurocognitive work from the MIT Media Lab and other studies linking heavy reliance on chatbots to reduced exploratory thinking and learning engagement. Key quantified shifts:

• •Excitement: down 14 points to 22%
• •Hopefulness: down 9 points to 18%
• •Anger: up 9 points to 31%
• •Anxiety: roughly stable near 42%

The authors highlight subgroup variation: older Gen Z (mid-20s) report the highest anger, and users who enter the workforce are more likely to see risks outweighing benefits.

Generation Z will disproportionately shape the labor market and education strategies over the next decade. The survey surfaces three operational risks for AI adoption: declining trust, perceived harm to learning and creativity, and pronounced concern about entry-level job displacement. These are not purely affective trends; they map to behavioral and policy vectors: reduced enthusiasm can slow voluntary adoption, increase pressure on regulators and institutions to mandate transparency and guardrails, and prompt employers to rethink task design and reskilling. The credibility gap noted by the survey echoes qualitative signals from higher-education and workforce studies that show friction when tools automate early-career tasks.

Why the methodology matters: The Gallup Panel sampling and margin-of-error reporting make these shifts statistically meaningful for national-level planning. That said, sentiment polls capture perceptions that can be amplified by headlines about high-profile incidents, so practitioners should triangulate with longitudinal behavioral metrics such as platform retention, product engagement, and hiring patterns.

Expect pressure from students, educators, and entry-level workers for greater transparency, usage controls, and pedagogical safeguards. Employers may face demands to replace blunt automation with hybrid workflows that preserve learning opportunities. Researchers and product teams should prioritize longitudinal studies that link specific AI interactions to measurable learning outcomes and early-career job tasks. As Zach Hrynowski, senior education researcher at Gallup, put it, "Even if it makes me anxious, even if I think it's potentially harming my cognition, it's here to stay. It's being integrated into my schools, it's being integrated into my workplaces, and I'm going to need to know how to use it."