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AI: Jobs, Power & Money
6NOV

Women face double the AI job risk of men

2 min read
11:10UTC

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·International Labour Organization / World Bank
Mentions:World Bank →International Labour Organisation →
First Reported In

Update #3 · The AI jobs data contradicts itself

International Labour Organization / World Bank· 28 Mar 2026
Read original →
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
Korea's four largest banks, as reported by News1
Korea's four largest banks, as reported by News1
KB Kookmin, Shinhan, Hana and Woori rehired 1,013 retirees last year, equal to 79.1% of their graduate intake, according to News1. Graduates face a smaller entry intake while returners take fixed-term credit-screening roles at lower pay, News1 reports.
High Court of Justice of Madrid
High Court of Justice of Madrid
The court's employment chamber ruled in judgment 864/2026, dated 8 October and made public in early November, that introducing AI is not on its own a ground for dismissal. Employers must prove AI's effect through the four causes the Workers' Statute already lists.
Singapore Ministry of Manpower
Singapore Ministry of Manpower
The Singapore Ministry of Manpower put third-quarter retrenchments at 4,800, concentrated in information and communications, financial services and manufacturing, with business reorganisation the main driver. Its release does not mention AI.
Challenger, Gray & Christmas
Challenger, Gray & Christmas
Challenger reported on 5 November that market and economic conditions overtook AI as the leading stated reason for 2026's US job cuts, at 130,531 against 121,401. AI was cited for 1,265 cuts in October, its lowest month of the year.
Office for Budget Responsibility
Office for Budget Responsibility
The OBR's 28 October outlook showed output per worker in information and communication growing 7.6% a year, yet kept AI's boost to UK productivity at 0.2 percentage points a year. It does not attribute the faster growth to AI.
Central Bank of Ireland
Central Bank of Ireland
Governor Gabriel Makhlouf said on 2 November that AI investment has supported Irish activity and flagged the debt financing behind it as a financial-stability risk. On jobs, he named skills bottlenecks and mismatches, not job losses.

Written with AI from Lowdown's published reporting. Not individually reviewed by an editor. Editorial standards.