Women are 3x more likely to lose their jobs to GenAI. Not because they’re underperforming, but because the roles they dominate are being automated first (International Labour Organisation). And no one is redesigning the future with them in mind. That needs to change, starting at the boardroom table, because if we aren’t paying attention, the damage won’t be theoretical, it will be systemic.
At the same time, Harvard studies show women are 25% less likely to be using GenAI at work. Not a capability gap. A visibility, support and inclusion gap.
And what about recruitment? Ask a GenAI tool to generate a picture of a board of directors, and you’ll likely see middle-aged men in suits around a mahogany table. That’s not malicious. That’s machine learning. AI doesn’t invent bias, it learns it from decades of job ads, performance reviews, hiring decisions and leadership profiles.
That’s why:
- AI hiring tools penalise CV gaps, disproportionately affecting women
- LLMs are 4x more likely to link men with leadership and women with caregiving
- Candidates with “non-traditional” names or accents are quietly deprioritised
UNESCO, UN Women, Deloitte, and NYU have all flagged the same thing: AI doesn’t remove human bias. It industrialises it.
The risk to women isn’t because the technology is bad, it’s because we’re not thinking hard enough, or acting quickly enough, on how this AI wave disproportionately impacts female employees. Without governance, we risk embedding outdated hiring norms into algorithmic systems.
What Boards Should Be Thinking About
Strong AI governance isn’t extra red tape. It’s the difference between replicating old patterns and creating something better:
Put GenAI on your agenda - not just under ‘technology’, but under ‘people’ and ‘ethics’. Ask “Who benefits? Who doesn’t?”
Interrogate the data - who is being helped, who is being harmed, and who is missing?
Insist on explainability - from internal teams and external vendors
Roll out inclusive upskilling - so all staff can work with AI, not be sidelined, especially for those in roles most at risk of automation
Track demographic impacts - including gender, ethnicity, and career stage
Final Thought
There’s no question that GenAI will reshape the future of work. But who wins is still open to us. Without deliberate leadership, AI replicates the past and reinforces the inequities we claim to have left behind.
AI will do what it’s taught. And right now, it’s being taught to follow patterns we should have outgrown.
If you’re a board member, chair, or executive, put equity, bias, and transparency on your agenda. Ask tough questions. Insist on explainability. Design for inclusion, not just optimisation.
Because unless we govern with intention, the default will always leave people behind.
The future’s here. Ready?
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