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AI: Jobs, Power & Money
8JUN

Women face double the AI job risk of men

2 min read
11:04UTC

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.

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
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.
Different Perspectives
European workers and regulators
European workers and regulators
NBER working paper w34995 found European workers use generative AI at 32% versus 43% of US workers, a gap driven by management practice rather than regulation. The EU AI Act's high-risk employment deadline stays at December 2027, leaving European workers facing the same displacement curve two to four years behind the US.
AI industry (Leading the Future PAC, OpenAI, Andreessen Horowitz)
AI industry (Leading the Future PAC, OpenAI, Andreessen Horowitz)
Leading the Future committed over $100 million to the 2026 midterms and targeted regulation-minded candidates in the 2 June primaries; its counter-fund Public First formed at $50 million. The PAC runs advertising on healthcare and jobs without naming AI, mirroring the 1994 insurance industry campaign that defeated the Clinton health plan.
UK youth entering the labour market
UK youth entering the labour market
UK youth unemployment reached 14.7% in January-March 2026, the highest since 2014, with 22.7% of young jobseekers out of work more than a year. The ONS publishes no AI-exposure breakdown, so policy is being set blind to the channel doing the damage.
US displaced workers (tech and finance)
US displaced workers (tech and finance)
Tech workers face median reemployment times of 4.7 months, up 47% from 2024, with a hiring pool contracting faster than AI-specialist openings can absorb them. Finance operations workers are the next cohort: 52% of their employers now run agentic AI in the exact functions where most of them work.
TSMC and Taiwan chip supply chain
TSMC and Taiwan chip supply chain
Nvidia's 17% headcount growth to 42,000 on $81.6 billion in quarterly revenue depends on TSMC's CoWoS advanced packaging capacity constraining H100 and B200 supply, sustaining margins above 70%. The AI build-out's sole headcount-growth story runs through a Taiwan supply chain that has no parallel in downstream software.
Displaced tech workers globally
Displaced tech workers globally
CrowdStrike's SEC disclosure puts AI attribution on a material regulatory record for the first time, but Oracle's Massachusetts WARN clock expired unfiled after up to 14 workers were logged as remote despite office proximity. The legal apparatus cannot enforce what it cannot see: hybrid reclassification, GCC transfers, and hires never made.