For women, GenAI exposure is rising. Opportunity must too

Women in Vietnam are more likely than men to work in occupations exposed to generative AI. But rather than asking whether AI will replace these jobs, it's more important to consider whether women will have equal access to the new skills and opportunities that AI creates.

The International Labour Organization (ILO) in 2026 estimated that around 11.5 million workers in Vietnam – about one in five – are in occupations where some tasks could be affected by generative AI (GenAI). Notably, exposure is higher for women, at 24.1%, compared with 17.8% for men.

The trend is not unique to Vietnam. Across 84 countries, ILO research found that female-dominated occupations are almost twice as likely to be exposed to GenAI as male-dominated occupations. This is partly because women are more concentrated in clerical, administrative and business-support roles, where AI can readily assist with tasks such as drafting documents, responding to customers or processing routine records.

At first glance, this may sound like bad news for women. But according to Dr Diem Vo, a lecturer in Digital Economy at RMIT University Vietnam, exposure does not automatically mean replacement.

“Generative AI impacts the task level first, not the job level. An administrative worker may use GenAI to draft emails or summarise meetings, but still needs to understand the context, communicate and take responsibility,” she said.

“As GenAI raises productivity, an important consideration is who will be equipped to take on higher-value work as tasks change,” she said.

For many women, that consideration matters more than whether AI automates individual tasks. Women are among the workers most likely to see their day-to-day work reshaped by AI tools, yet they remain underrepresented in many of the roles designing, implementing and managing these technologies.

“Without deliberate action, there is a risk that women experience the disruption brought by AI without enjoying an equal share of the opportunities it creates,” Dr Diem said.

The gap from exposure to opportunity

Dr Diem proposes that workers and organisations should think about GenAI’s impact on jobs in three stages.

Exposure asks which tasks are changing. Capability asks who gets the tools, training and confidence to use AI safely and effectively. Benefit asks whether higher productivity becomes higher-value work, better pay, promotion, greater autonomy or better job quality.

“The gaps between these stages are where new inequalities can emerge,” Dr Diem said.

Two employees may be equally exposed to AI, but their outcomes can be very different. The one who receives training and develops new AI-related capabilities may progress much faster. The other may see parts of their work automated without receiving the same opportunities for development.

For businesses, especially in finance, insurance, retail and professional services, this is both a gender-equality issue and a productivity and workforce-management issue.

“AI performance should not be measured only by licences, usage rates or cost savings. Firms should monitor who receives AI training, which tasks are automated or augmented, who moves into higher-value work, and how pay, promotion and autonomy change for women and men,” Dr Diem said.

From basic digital skills to AI capability and better jobs

Vietnam’s 2026-2030 Digital Economy and Digital Society Development Program provides an important foundation to reduce inequality in accessing opportunities from new technologies. The program aims to deliver basic digital-skills training to at least 10 million working-age participants and support at least 500,000 small and medium-sized enterprises in digital transformation.

But basic digital literacy is only the starting point. Dr Diem believes workers also need to know when AI output can be trusted, how to verify it, how to protect confidential data and when a human must remain responsible for the final decision.

For women in particular, access to these capabilities could increasingly shape career opportunities in AI-enabled workplaces.

This matters because the ILO continues to identify occupational segregation, earnings gaps and barriers to women’s career progression in Vietnam.

“Women’s higher exposure to GenAI is neither automatically bad news nor automatically an opportunity. The outcome will depend on how firms redesign jobs, expand access to AI tools and training, share productivity gains, and support workers as roles change,” Dr Diem pointed out.

“The goal should not simply be faster AI adoption, but to turn exposure into capability, and capability into better opportunities.”

For Vietnam, the more useful question is therefore not “Will AI take women’s jobs?” but “Will women have an equal chance to shape and benefit from the jobs that AI transforms?”.