A new poll shows only one-third of American workers expect AI to improve their jobs, with a sharp divide by income: 40% of those earning $100,000 or more are optimistic, versus 19% of those earning under $50,000.
The survey also found that white-collar workers are more likely to use AI and that Black workers are more likely than white workers to fear job replacement, highlighting what one progressive group calls an emerging class divide around AI's economic effects.
What happened
A new poll from Groundwork Collaborative and Ipsos found that only one-third of American workers expect AI to improve their jobs. The survey revealed stark disparities: four in 10 workers earning $100,000 or more expect AI to make their jobs better, compared with just 19% of those earning under $50,000. White-collar workers are more likely than blue-collar workers to use AI at work, and Black workers are more likely than white workers to predict AI will replace their job.
Why it matters
The findings underscore what Groundwork's Alex Jacquez calls "yet another class divide for the American public." Workers with lower incomes and in manual labor face greater anxiety about AI's economic impact, while higher earners show more optimism. This inequality in expectations may reflect real differences in how AI is being deployed and who stands to benefit from automation.
What to watch
Groundwork is proposing one possible policy response: a public stake in AI firms, an idea advanced by Sen. Bernie Sanders. Jacquez dismissed universal basic income as a sole solution, suggesting that ownership structures in the AI sector could be part of addressing the technology's economic impacts.
Groundwork Collaborative and Ipsos released polling data that paints a stark picture of diverging expectations around artificial intelligence in the American workforce. The headline finding is sobering: only one-third of American workers believe AI will improve their jobs. But the deeper story lies in the divisions that emerge when the data is broken down by demographic and economic factors. Workers making $100,000 or more annually show notably higher confidence, with four in 10 expecting AI to make their jobs better. That optimism drops sharply for lower-wage workers: only 19% of those earning under $50,000 expect improvement. The survey also found structural differences in AI adoption and anxiety. White-collar workers report higher rates of AI use in their current work compared with blue-collar workers, suggesting the technology is being deployed unevenly across occupational categories. When asked about the risk of replacement, racial disparities emerge: Black workers are more likely than white workers to predict that AI will replace their job. Alex Jacquez, from Groundwork Collaborative, framed these findings as evidence of a new layer in America's economic divide. He was explicit in rejecting one commonly discussed remedy—universal basic income—as insufficient. Instead, he pointed to a proposal from Sen. Bernie Sanders, I-Vt., for public ownership or a public stake in AI firms. The idea, though not elaborated in detail in Jacquez's comments, suggests redirecting how the wealth and control generated by AI systems are distributed, moving beyond income support toward structural ownership reform.
The poll data reveals a bifurcated landscape in how Americans view AI's economic future, one that maps closely onto existing inequalities in income and work type. The 21-percentage-point gap between high and low earners (40% versus 19%) suggests that workers in better-paid roles—typically those with more education and discretionary power over their workflow—see AI as a tool that can augment their productivity and value. By contrast, lower-wage workers, who often occupy roles more vulnerable to automation, view the technology with skepticism or fear. The disparity between white-collar and blue-collar workers, and the higher anxiety among Black workers, point to a pattern: those whose labor is easiest to automate or most exposed to wage competition are least optimistic about AI's impact on their prospects. Groundwork frames this as a structural problem requiring policy intervention. The group's endorsement of a public stake in AI firms—rather than redistribution measures like universal basic income—suggests a preference for reshaping ownership and returns on AI capital itself, positioning it as a remedy that could align incentives between workers and the companies building these systems.
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