AI Layoffs: Why women face greater risks as AI reshapes jobs? Could your job become obsolete? Explained

Artificial intelligence is reshaping the future of work, but its employment risks are unlikely to be distributed evenly. Women could face disproportionate disruption as AI automates administrative, clerical and routine office tasks that have historically employed millions of female workers. Previous technological revolutions offer a warning: while new industries can create opportunities, workers whose skills become obsolete may struggle to find jobs offering comparable pay and security.

Research by the International Labour Organization (ILO) published in March found that nearly one in 10 women in high-income countries works in an occupation at the highest risk of AI exposure.

The findings highlight a growing concern for policymakers and employers: technological progress may create new economic opportunities while leaving some groups of workers more exposed to displacement than others.

The history of telephone operators, office workers and the personal computer offers clues to how the AI transition could unfold.

AI automation puts women in clerical jobs at greater risk

Women remain heavily represented in occupations involving administration, record-keeping and routine information processing, making these roles particularly exposed to AI-driven automation.

“AI is focused on routine tasks and numbers and finding patterns, and those types of jobs are the clerical, administrative jobs that a lot of women hold,” said Ariane Hegewisch, a senior research fellow at the Institute for Women’s Policy Research.

“It’s still 90% of secretaries and clerical workers who are women.”

The risk extends beyond outright redundancies. When technology eliminates established roles, displaced employees may have to accept lower-paid work or leave the labour market altogether.

What the disappearance of telephone operators reveals about AI layoffs

The experience of American telephone operators illustrates the potential consequences of large-scale automation.

As Hegewisch warned: “AI can learn.”