AI May Disrupt Women-Dominated Jobs More Severely, With 29% Facing High Exposure Risk

Women Workers Face Disproportionate AI Job Disruption Risk

New research reveals a stark gender divide in how generative AI will reshape the workforce, with women workers facing significantly higher exposure to job disruption than their male counterparts. According to a study by the International Labour Organization, approximately 29% of women-dominated occupations face exposure to generative AI, compared to only 16% of male-dominated jobs across 88% of countries analyzed 1

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. This disparity signals that the AI impact on women will be far more severe than previously anticipated, particularly as companies like Amazon, Meta, and Oracle accelerate their investments in automation while simultaneously implementing widespread job cuts.

High-Risk Automation Categories Hit Women Hardest

The gap widens dramatically when examining high-risk automation categories in wealthy nations. The International Labour Organization found that 9.6% of women's employment falls into these high-risk zones, compared to just 3.5% for men 1

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. This disproportionate impact of AI on women workers stems largely from the nature of roles women predominantly occupy. Administrative assistants, payroll staff, receptionists, and customer support workers handle repetitive tasks that AI tools can increasingly perform with minimal human oversight. Data from the Brookings Institution estimates that over 85% of workers in highly exposed clerical and administrative roles are women 1

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Millions of Women Face Major Workplace Changes

Research conducted by the National Partnership for Women & Families in the United States underscores the scale of this challenge. While women make up nearly half of the US workforce, they represent a large majority of workers employed in occupations considered highly vulnerable to AI-driven disruption 2

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. The researchers estimate that millions of women currently work in positions that will see major changes because of AI adoption, with many having fewer resources or opportunities to adapt quickly to changing workplace demands. Women are more likely to lose their jobs in sectors where automation is rapidly improving, including office clerks, secretaries, and insurance-related positions.

Care Sector Jobs Not Immune to AI Influence

While some industries with large numbers of female workers—including healthcare, childcare, and caregiving—are less likely to be completely automated due to their dependence on human interaction and emotional skills, AI may still reshape these roles through workplace surveillance and automated management systems 2

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. This means even sectors traditionally considered safe from automation will experience significant transformation as AI tools become more sophisticated.

Underrepresentation of Women in AI Development Compounds Risk

A critical concern highlighted in the research is the underrepresentation of women in AI development and leadership positions. This imbalance may reduce women's influence over how AI systems are built and implemented, even as these systems increasingly affect their professional lives 2

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. The report cited examples of bias in AI systems, including an experiment where OpenAI's ChatGPT allegedly portrayed female candidates as less experienced than male candidates with similar profiles. Such biases embedded in AI tools could further disadvantage women in hiring and career advancement.

Workplace Policies Will Determine Future Outcomes

Despite these challenges, the study noted that women's use of AI tools has steadily increased in recent years. The ultimate impact on women workers will be largely determined by workplace policies, regulations, and how responsibly companies deploy these technologies 2

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. As AI continues to evolve, organizations must prioritize responsible AI deployment that considers gender disparities and implements safeguards to protect vulnerable workers. The coming years will test whether policymakers and business leaders can create frameworks that distribute AI's benefits more equitably while mitigating its most harmful effects on women-dominated occupations.