Women Perceive AI as Riskier than Men Do, Study Finds

Why It Matters

Women’s heightened AI risk perception may slow adoption in sectors where gender diversity is already low, potentially widening existing labor market inequities. Companies that ignore these attitudes risk missing talent and facing reputational challenges.

Key Takeaways

• Women view AI as riskier than men, per 3,049 respondents.
• Higher risk aversion drives women's greater AI skepticism.
• Greater exposure to AI job displacement amplifies women's concerns.
• Skepticism leads women to support AI adoption less as benefits shrink.
• Gender gap may deepen occupational segregation as AI diffuses.

Pulse Analysis

The recent survey published in PNAS Nexus adds a nuanced layer to the conversation about AI adoption by highlighting gendered risk perceptions. Researchers surveyed a representative panel from the United States and Canada, measuring individual risk tolerance, exposure to technological change, and attitudes toward AI. Women consistently rated AI as more hazardous, a pattern driven by both intrinsic risk aversion and heightened awareness of potential job displacement. The experimental component, which varied the projected net benefit of generative AI for a workforce, showed women’s support eroding faster than men’s as optimism waned, underscoring the psychological underpinnings of technology acceptance.

For businesses, these findings signal a strategic imperative to address gender-specific concerns when rolling out AI solutions. Companies that deploy AI without considering the skepticism of a sizable portion of their female workforce risk lower engagement, reduced adoption rates, and potential pushback on ethical grounds. Tailored communication that transparently outlines risk mitigation, offers reskilling pathways, and demonstrates tangible benefits can help bridge the perception gap. Moreover, inclusive design practices that involve diverse employee voices early in the development cycle can preempt bias and foster broader trust across gender lines.

Looking ahead, the gender divide in AI perception could shape labor market dynamics as automation accelerates. If women remain more cautious, they may gravitate toward roles less affected by AI, reinforcing occupational segregation and limiting career advancement in high‑growth tech sectors. Policymakers and corporate leaders should therefore prioritize gender‑responsive AI governance, investing in education, mentorship, and equitable access to AI‑related upskilling. By proactively aligning AI strategy with the concerns of all employees, firms can unlock the technology’s full productivity potential while mitigating the risk of deepening existing inequities.