How Is Generative AI Reshaping Gender Inequalities at Work?

The International Labour Organization’s new report shows that generative AI will not affect men and women equally. By applying a novel ILO exposure index across 84 countries, researchers found that occupations dominated by women are almost twice as likely to be automated—29 % versus 16 % for male‑dominated jobs. Moreover, women face higher automation risk in 88 % of the surveyed economies. Typical roles such as payroll clerks, receptionists, data‑entry operators and translators are especially vulnerable because they consist of routine, codifiable tasks that AI can replicate quickly.

These disparities stem from deep‑rooted structural drivers. Social norms and gender stereotypes steer women toward caring and administrative positions while channeling men into senior, technical roles. Globally, women shoulder three‑quarters of unpaid care work, limiting their ability to pursue higher‑skill jobs or full‑time hours. When AI systems are trained on historical data that reflects these inequities, they reproduce bias—evident in recruitment tools that favor male‑sounding names or salary‑setting algorithms that perpetuate pay gaps. Intersectional discrimination compounds the problem for women of color, older workers, and migrants.

Policymakers, employers and trade unions can shape a more equitable AI future. The ILO urges embedding gender equality into AI design, using unbiased, high‑quality data sets and ensuring women have access to AI‑related jobs and decision‑making roles. Governments must enact transparent regulations, data‑protection standards and non‑discrimination safeguards, while also reforming care and labor‑market policies to reduce women’s unpaid workload. Companies should adopt AI strategies that include ethical risk assessments, skilling programmes and tools that flag biased job ads or pay structures. When AI is built responsibly, it can help close gender gaps rather than widen them.