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AI: Jobs, Power & Money
27JUL

Women face double the AI job risk of men

2 min read
10:02UTC

A 135-country study found women hold nearly twice the share of highest-risk AI-exposed jobs globally. In wealthy nations, the gap is almost threefold.

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EconomicAssessed
Key takeaway

Women hold nearly double the share of jobs most exposed to generative AI displacement.

A joint study by the International Labour Organisation and the World Bank, published in March and covering 135 countries and two-thirds of global employment, found that one in four workers holds a job with some generative AI exposure. 1 In the highest-risk category, 4.7% of women are exposed globally, compared with 2.4% of men. In high-income countries the gap widens: 9.6% of women versus 3.5% of men.

Clerical and administrative work is the exposure vector, roles historically concentrated among women. Advanced economies show 34% overall workforce exposure; low-income countries show 11%. 2 Wealth correlates with AI penetration into clerical roles where women are concentrated. Wealth also correlates with the gender disparity.

This dimension has been absent from the displacement debate. CFO surveys, tech layoff trackers, and congressional proposals: none address gendered impact. The 502,000 roles the Atlanta Fed projects will be cut are not distributed evenly. Clerical and administrative roles most exposed to generative AI are held disproportionately by women, and no current policy framework accounts for it.

Deep Analysis

In plain English

A major global study found that women are about twice as likely as men to work in jobs that generative AI is capable of automating. In richer countries the gap is even larger: nearly three times as likely. This is because AI is best at handling text, data, and communication tasks, which are the core of administrative and clerical work. Those roles have historically been held more by women. No current government policy specifically addresses this disparity.

Deep Analysis
Root Causes

The gender exposure gap traces directly to occupational segregation. Administrative, secretarial, and clerical roles, which have been disproportionately held by women in OECD economies since the 1960s, are the roles with the highest generative AI task coverage. This segregation was not caused by AI; it reflects decades of labour market structure that AI is now exploiting.

The high-income country amplification effect (9.6% vs 4.7%) reflects the greater penetration of digital work in wealthy economies. In low-income countries, clerical roles are less computerised and therefore less exposed to generative AI substitution. The paradox is that development increases women's AI exposure risk.

What could happen next?
  • Consequence

    AI-driven displacement will widen the gender pay gap if affected women are absorbed into lower-wage service roles, repeating the 1980s-90s pattern from PC-era clerical displacement.

    Medium term · Medium
  • Risk

    No current legislative proposal in the US, EU, or UK specifically addresses gendered AI exposure, meaning the disparity will compound without deliberate policy intervention.

    Medium term · High
  • Meaning

    The 135-country ILO dataset is the first evidence base capable of grounding gendered AI policy; its publication removes the 'we don't have data' objection to targeted intervention.

    Long term · High
  • Opportunity

    Countries that invest now in reskilling women in AI-adjacent roles have a window before displacement concentrates to capture the productivity benefits on both sides of the transition.

    Medium term · Medium
Sources:International Labour Organization / World Bank
Mentions:World Bank →Prima →International Labour Organisation →
First Reported In

Update #3 · The AI jobs data contradicts itself

International Labour Organization / World Bank· 28 Mar 2026
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Causes and effects
This Event
Women face double the AI job risk of men
The first global dataset on gendered AI displacement reveals a disparity that no current policy framework addresses.
Led to
Goldman counts 25,000 jobs lost monthly
Goldman's finding that 86% of the most vulnerable displaced cohort are women reinforces the ILO-World Bank gender displacement risk finding.
Occurred 6 Apr 2026
Read story →
Different Perspectives
European Commission
European Commission
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Office for National Statistics
Office for National Statistics
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Christian Klein, SAP
Christian Klein, SAP
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Betsey Stevenson, University of Michigan
Betsey Stevenson, University of Michigan
Betsey Stevenson argued that the 187,000 jobless-claims reading describes a market that hires little and fires little, not one AI is emptying. She said the real damage hides in eligibility rules and suppressed job postings, not in the headline layoff counts employers keep denying.
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Stanford's 'We Must Act Now' signatories
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