Jobs held predominantly by women are more exposed to AI-driven automation than male-dominated roles, according to an analysis of data from Australian government agency Jobs and Skills Australia. The finding challenges assumptions that female-heavy sectors like care work are shielded from the technology's impact.
The agency's automation exposure score measures how much of each occupation's tasks could be performed by AI. Clerical and administrative jobs rank among the highest for exposure, and that sector is more than 70% female. It provides almost one in five jobs for women in the Australian workforce.
Female-dominated roles lead the risk list
Of the 20 occupations most at risk of automation, 15 are female-dominated. Five of those are at least 80% female. Secretaries, receptionists, bookkeepers, and accounting, human resources and payroll clerks all appear on the list. Only one of the top 20 - financial dealers - is moderately male-dominated. The remaining four are gender-balanced.
By contrast, 17 of the 20 occupations least exposed to automation are male-dominated. Female-concentrated jobs make up just three of the roles most sheltered from AI displacement.
"Unless we intentionally apply a gender lens, we could end up ignoring gender patterns in AI's effects," the analysis warns. The Australian government already requires all new policy proposals to conduct a gender analysis, and the authors argue this should extend to decisions by the newly established Office of AI.
Vacancy data shows early signs of impact
Internet job vacancy data from Jobs and Skills Australia suggests the effects may already be showing. Vacancies for personal assistants and bookkeepers in June 2026 were around 22% lower than a year earlier. General clerk openings were down about 9%. Total workforce vacancies fell only 1.7% over the same period.
Less exposed occupations are faring better. Concreter vacancies were up 5.5% and electrician openings rose 14%. These hands-on trades still require human judgement and dexterity for physical conditions that vary significantly.
Detecting these patterns early allows for proactive policy design rather than reactive fixes. For example, systems could be set up to recognise transferable skills in clerical and administrative workers and adapt them to new needs, including emerging AI-related jobs and human-centred roles the technology can't replace directly.
Why this matters for HR professionals
HR teams face a workforce where the jobs most vulnerable to automation are disproportionately held by women. That makes reskilling and redeployment a gender equity issue as much as a technology issue. For practical guidance on supporting affected staff, see AI for Human Resources. For teams with clerical and administrative workers, the AI Learning Path for Administrative Assistants offers a starting point for building skills that transfer to new roles.
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