Budget 2025’s AI Bet: $1 Billion for Infrastructure, Zero for the Women It Will Displace

“This measure will primarily benefit highly educated men.” 

That’s not commentary. It’s a direct quote from the federal government’s Gender-Based Analysis of its $925.6 million investment in AI infrastructure in Budget 2025.​

The same budget that outlines nearly a billion in infrastructure spending offers no workforce funding for the people AI is most likely to replace—women.

We’ve watched women come through our programs and transform their careers. They’re not learning to code. They’re learning the practical digital skills that employers are actually hiring for: growth strategy, AI adoption, and marketing analytics. On average, our graduates increase their salaries by 40% within 6 months. That’s not anecdotal. That’s what happens when you give people the tools they need to compete.

So when I read the budget, I was looking for two things: investment in the infrastructure that will shape Canada’s role in AI, and investment in the people who risk being left behind as it rolls out. The first part is there. The second isn’t.

A Billion Dollars for Men. Nothing for the Women Most at Risk.

Canada is making a smart bet on AI infrastructure: building national compute capacity, research ecosystems, and cloud systems at scale. This kind of sovereign capability matters. We need it.

But here’s what the government’s own analysis reveals about who benefits and who doesn’t.

In the budget’s Gender-Based Analysis, the assessment of “Seizing the Full Potential of Artificial Intelligence” states plainly:

“This measure will primarily benefit highly educated men in the regions of British Columbia, Alberta, Ontario, and Québec, where the majority of the AI ecosystem is concentrated. Approximately 70 per cent of AI workers are men with tertiary/advanced degrees. Around 50 per cent of AI jobs are classified as well-paying with annual salaries in the range of $82,000 or more.”​

Now consider that research from the United Nations International Labour Organization tells us that women are nearly three times more likely than men to lose their jobs to AI. 

The roles most exposed to AI, like administration, data entry, and customer service, have historically been held by women.

So the government is investing a billion dollars in AI infrastructure that it acknowledges will primarily benefit affluent men. But the people who that technology will most impact receive nothing. 

That’s not a blind spot. That’s a policy choice, documented in the government’s own analysis.

What Our Research Found

Earlier this year, Growclass partnered with Angus Reid to survey over 1,000 Canadian workers about AI adoption in the workplace. Only 12% of Canadians have received formal AI training. Women, lower-income earners, and younger workers were the least likely to feel prepared for the introduction of these tools.​

But when asked if they would take training if it were offered, the majority said yes. The interest is there. The infrastructure to support them isn’t.

We’re building the future without the people most affected by it.​

Why a Platform Isn’t Enough

In this budget, the government proposes a digital job-matching platform as its response.

But here’s what research actually shows: 87% of Canadian employers rely on referrals as their top recruiting channel to fill jobs. When someone refers you, you’re four to five times more likely to get hired. A platform doesn’t close that gap. It doesn’t build your network. It doesn’t put your name in front of a hiring manager who trusts the person recommending you.​

For workers without existing networks in high-growth fields, a job-matching platform won’t help them get hired.

That’s why community-based training programs work differently. They don’t just build skills. They build access.

What’s Actually Working

Last year, Growclass partnered with The Forum and Camp Tech to run a pilot funded by Canada’s DIGITAL Supercluster, training 250 women entrepreneurs in values-based AI adoption. The demand was overwhelming. Confidence in deploying AI tools rose by 90%, and 80% of our graduates have already meaningfully deployed AI in their organizations.

But the real value came in the network. They shared resources and helped each other build. That’s the kind of infrastructure that actually drives economic growth. That’s what actually changes outcomes.

Now we need to scale proven models out to Canada’s workforce.

The Real Choice

Canada must remain ambitious and be willing to invest in the future. But I am asking for infrastructure investments to be matched with equal ambition for workforce equity.

The pilots are proving the model works. The demand is there. Women want to learn. Women want to compete and succeed in an AI-driven economy. What’s missing is the decision to fund these programs at scale.

Here’s what that would look like:

Create a dedicated AI reskilling fund for workers most at risk, with explicit targets for women and underrepresented professionals. This isn’t a new idea. It’s the same approach the budget uses for manufacturing workers. Apply it here.

Invest in training programs that build professional networks, not just job boards. Fund community-based models that create mentorship, connection, and access to the hidden job market where most opportunities actually exist.

Scale what’s already working. Pilots like ours are proving the model. They need investment to reach more Canadians—across regions, industries, and demographics.

Require recipients of AI infrastructure funding to report on workforce inclusion. Not just research outputs or technical milestones, but actual data on who is benefiting from these investments and who is being left behind.

The Budget’s Honest Admission

Canada is placing a billion-dollar bet on AI. That’s a smart move. The infrastructure matters. We need it.

But infrastructure alone doesn’t create prosperity. People do. And right now, the GPA analysis of the budget acknowledges that it will benefit a privileged few.​

The question is whether the next budget will acknowledge something else: that this gap is a choice, and that it can be fixed.

The pilots are proving the model works. The data shows the need. The demand is real. What’s missing is the commitment to invest in it at scale—to ensure that when Canada wins in AI, it’s not just a privileged few, but all of us.