Canada has earned a reputation as one of the world's premier artificial intelligence hubs — rich in research talent, academic infrastructure, and government ambition. But a critical blind spot is emerging at the heart of the country's AI boom: the workers most vulnerable to being displaced by AI are overwhelmingly women, while the people building those systems are overwhelmingly not.
That disconnect, according to April Hicke, founder and CEO of Toast, a tech recruitment platform focused on gender diversity, represents more than a fairness problem. It is, she argues, a structural failure with real consequences for Canada's economic competitiveness.
The Numbers Are Hard to Ignore
The International Labour Organization's most recent research brief on AI and labour markets found that women-dominated occupations are nearly twice as likely to be exposed to generative AI disruption as male-dominated ones. Twenty-nine per cent of women's jobs are considered at risk, compared to 16 per cent of men's jobs.
A separate Anthropic report tracking real-world labour market impacts reached similar conclusions. At the highest automation-risk levels, 16 per cent of female-dominated roles fall into the most exposed categories — against just three per cent of male-dominated roles. In high-income countries like Canada specifically, the ILO found 9.6 per cent of women are in the highest AI-exposure category, compared to 3.5 per cent of men.
In practical terms, Canadian women are nearly three times more likely to see their livelihoods disrupted by AI than their male counterparts.
Why Women Are in the Crosshairs
The vulnerability is structural, not coincidental. Women in Canada are heavily concentrated in clerical, administrative, and business support roles — secretaries, receptionists, payroll clerks, and accounting assistants. These positions involve routine, codifiable tasks that are precisely what AI systems are designed to absorb. Meanwhile, men dominate construction, manufacturing, and the skilled trades, where physical labour remains far more difficult to automate.
At the same time, women make up just 22 per cent of the global AI workforce, and fewer than two per cent of venture capital funding flowing into AI-driven startups reaches women-led ventures.
That absence from the design table carries measurable consequences. Amazon famously scrapped an internal recruiting AI after discovering it systematically downgraded women's résumés — because the system had been trained on a decade of male-dominated hiring data. Medical AI tools have shown reduced accuracy for women due to skewed training datasets. When the people building AI systems do not reflect the full population that will be affected by them, those gaps become embedded in the technology itself.
The Training Gap Is Happening Right Now
A 2024 survey of more than 5,800 Canadians by the Future Skills Centre found that 53 per cent of men described themselves as somewhat or very familiar with AI tools used in the workplace, compared to 47 per cent of women. More men than women also reported receiving AI guidance from their employers.
This means the disparity is not only a pipeline problem for the next generation — it is happening inside Canadian workplaces today, to women already employed and already at risk. When employers invest in AI literacy unevenly, they are not simply reflecting existing inequality. They are deepening it.
"The women most at risk of being displaced by AI are also the least likely to be equipped to work alongside it." — April Hicke, CEO, Toast
Canada currently sits in a paradoxical position: one of the world's leading AI research and development ecosystems, yet a country where fewer than four per cent of firms have adopted AI in their operations. The country is funding acceleration without ensuring equity, building a talent pipeline without asking who gets access to it.
What Canada Can Do
Women-owned businesses contribute an estimated $150 billion to Canada's GDP and employ 1.5 million people. Without deliberate policy action, AI risks becoming an amplifier of the existing gender pay gap rather than a tool that narrows it.
Hicke and researchers in the field point to three immediate steps Canada should take — with particular urgency for women who face compounding barriers related to race, disability, or immigration status, where data gaps are widest and the stakes are highest.
Mandate gender-disaggregated impact assessments before any AI tools affecting workforce decisions — hiring, performance evaluation, promotion, or compensation — are deployed at scale. If a company cannot demonstrate how its AI performs across gender lines, it should not be rolling it out broadly.
Fund women's access to AI upskilling at the same rate and with the same urgency as AI research and development investment. For every dollar Canada invests in AI acceleration, there must be a corresponding commitment to equitable access to the skills those investments create.
Require meaningful women's representation on AI governance bodies, ethics boards, and federal AI advisory panels — not as a checkbox, but as a genuine condition of participation. The decisions made in those rooms will shape the economy that all Canadians, including those typically excluded from them, will inherit.
As the ILO itself notes, the impact of AI on women's employment is not predetermined. Canada has built something rare: a world-class AI ecosystem paired with values and institutional capacity that could allow it to lead responsibly. The architecture of that economy is still being designed. The question now is whether Canada will design it for everyone — or leave half its talent behind.
This article is based on analysis and commentary originally published by BetaKit. The views expressed reflect those of the original author, April Hicke, and do not necessarily represent the position of WestNet News.