AI is widening gender gaps at work - unless HR steps in
AI is creating new roles and redefining old ones, but the gains are not shared evenly. Women remain concentrated in administrative and service jobs most exposed to automation, while men dominate AI-heavy growth roles. That split threatens future leadership pipelines across APAC.
New research from Singapore-based advocacy group NINEby9, AI and the Future of Women in the Workplace, lays out nine hard truths HR leaders can't ignore. The takeaway: inclusion has to be built in from day one, or the bias we have today gets baked into tomorrow's systems.
What the research shows
- Women over-index in roles at risk. Across Singapore and Australia, women hold roughly 10% more jobs in occupations most disrupted by AI compared with men.
- An AI participation gap is forming. Men cluster in AI-enabled growth areas; women remain in functions more likely to be automated. In 2024, women held 24.4% of managerial roles globally and just 12.2% of C-suite roles in STEM fields.
- Adoption style affects visibility. Many women adopt AI more deliberately, prioritising clarity, fairness and competence. Yet visibility often goes to early, flashy experimentation. About 59% of women said they're waiting for clear organisational AI policies before using AI tools.
- Tech-first rollouts risk bias. Nearly half of APAC companies say AI adoption is driven mainly by IT. Meanwhile, 42% of employees report receiving no AI training or guidelines from their employer.
- External hiring beats internal growth. Job ads asking for AI experience have tripled since 2020, but fewer than 15% are filled internally. Without structured internal pathways, women in adjacent roles get sidelined.
- Self-paced learning models miss many women. Optional, after-hours courses penalise those with higher care loads. Women make up about one-third of AI course enrolments and are more likely to stick to beginner tracks.
- Entry pathways for Gen Z women are shrinking. Automation hits junior roles first, and entry-level postings in high-growth sectors have fallen since early 2024. Fewer training opportunities deepen long-term risk.
- HR optimism is ahead of readiness. Many HR leaders see the upside of AI for L&D and workforce planning but report insufficient expertise to lead the change.
- HR-Tech collaboration is thin. Fewer than 1% of APAC organisations have a responsible AI framework with a long-term, systemic approach.
These points were reinforced by leaders from Dell Technologies, HSBC, LinkedIn and Bain & Company at the NINEby9 event, underscoring a cross-industry concern: if HR doesn't lead, AI will mirror old patterns at scale.
What this means for HR
Inclusion can't be retrofitted. It has to be designed into how you set strategy, build skills, and move people into AI-augmented work.
- Create joint AI governance with Tech. Define shared ownership, human oversight, risk review, and decision rights. Put DEI outcomes on the scorecard from day one.
- Map exposure and opportunity by role. Identify women-heavy functions with high automation risk. Build targeted pathways into AI-augmented roles with clear skill bridges.
- Set internal mobility targets for AI roles. Commit a percentage of AI job fills to internal candidates. Use skills adjacency, not past titles, to select and place.
- Make learning accessible on company time. Provide paid learning hours, cohort-based programs, manager-backed plans, and stackable credentials. Track enrolment and completion by gender and level.
- Protect entry points for Gen Z. Launch apprenticeships, rotations and supervised AI projects. Drop degree-only filters; sponsor certification exams.
- Reward responsible AI use, not just experimentation. Recognise outcomes, fairness checks and good documentation. Share case studies that show impact and safe practice.
- Upskill HR. Build baseline AI literacy, data confidence and prompt proficiency. Give HR safe sandboxes and office hours with Tech.
- Equip people managers. Train for quality prompting, bias checks, and coaching on AI-enabled workflows.
- Measure what matters. Monthly dashboard by gender: training hours, internal moves into AI roles, promotion rates, pay changes, attrition in at-risk roles.
- Raise the bar for vendors. Require bias testing, explainability, privacy standards, and DEI reporting in every RFP and renewal.
A 90-day plan to get moving
- Days 0-30: Stand up an AI + Work council (HR, Tech, Legal, Risk, Business). Publish a first AI use policy. Baseline role exposure. Run listening sessions with women in at-risk functions. Secure L&D budget and paid learning time.
- Days 31-60: Launch two reskilling pilots (e.g., admin to AI-enabled operations; service to analytics). Open an internal AI job board. Add gender and internal mobility KPIs to executive scorecards.
- Days 61-90: Convert pilots into a standing internal pipeline. Update job architecture with AI skills and levels. Adopt a responsible AI framework and publish a short transparency report.
Numbers to watch
- % of women in AI-augmented roles vs. high-risk roles
- % of AI roles filled internally (and by gender)
- Training access and completion parity by level and function
- Promotion velocity into AI-influenced leadership tracks
- Entry-level openings in high-growth teams and participation of Gen Z women
- HR AI capability index (policy, skills, tooling, vendor standards)
Why this has to be shared work
"The C-Suite, including HR and technology leaders, must be aligned, collaborate with one another and communicate with stakeholders to unlock the full potential of people, process and technology to benefit the business," said Christine Fellowes, Co-Founder and Chairperson, NINEby9. That alignment is the difference between AI that scales bias and AI that expands opportunity.
Sources and further reading
NINEby9's research draws on LinkedIn, the World Economic Forum, Coursera, BCG, Accenture, Workday Research, Randstad, Australia's Department of Employment and Workplace Relations, Harvard Business Review and Cegos.
Practical training options
If you need structured, job-focused programs your teams can take during work hours, see curated AI courses by job role and a shortlist of recent AI courses. Use them to build the internal pathways your hiring plans require.
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