AI Why Canada Needs an Equity Centered National Artificial Intelligence Strategy Mohamed Hamad AI 6 mins read February 9, 2026 » Blog » Why Canada Needs an Equity Centered National Artificial Intelligence Strategy Why Canada Needs an Equity Centered National Artificial Intelligence Strategy - Table of Contents A look at our current federal strategy Why this matters for Black Canadians right now Turning inclusive ideas into real results Where the policy has some blind spots A better path for our national strategy Some simple truths about digital equity We can build a fairer future together Black History Month in Canada is always a special time to honour the incredible things Black communities have built, but it’s also a moment to get real about the hurdles that still exist. As our federal government moves faster with the Pan-Canadian AI Strategy, we need to shift our focus from just hitting technical goals to building a system that’s actually fair for everyone. Historically, economic systems haven’t always been open to Black Canadians. Now, we’re at a point where we have to decide if our national approach to artificial intelligence will help fix those old gaps or just automate them. Inclusive AI development is the simple idea that we should intentionally include Black perspectives in how technology is designed and managed. For Black Canadians, a policy that only looks at how well the code works isn’t enough. It needs to be built with social and economic equity in mind, backed by clear rules and community input. A look at our current federal strategy The Pan-Canadian AI Strategy is basically Canada’s game plan for leading the world in tech. The first part of the plan was all about finding and training great researchers. Now, the second phase is moving into making AI a business reality and setting safety standards through the Canadian AI Safety Institute (CAISI). On paper, the strategy is a huge engine for innovation. However, a lot of the talk about “responsible AI” is still pretty vague. Civil society organizations have expressed urgent concern that without a specific focus on racial equity, the strategy might just repeat the same old mistakes by choosing speed over making sure the tech works for everyone. Why this matters for Black Canadians right now Artificial intelligence isn’t just a neutral tool because it usually reflects the views of the people who make it. Research from KM4S and McKinsey shows that Black Canadians are in a unique spot during this big tech shift. We don’t have nearly enough Black Canadians in the roles that actually build and manage AI systems, which leads to issues like linguistic inequality and dialect bias in AI models. Many Black workers are currently in roles that are more likely to be automated, potentially widening the wealth gap by tens of billions of dollars if we don’t intervene. It’s still significantly harder for Black entrepreneurs to get the funding they need to start their own AI companies and compete in a market with trillions in economic potential. Black History Month reminds us that old unfairness can easily show up in new tech. AI is just the latest place where we need to step up and make things right. Turning inclusive ideas into real results Moving from a nice idea to real results takes specific steps. We need to make sure Black communities are part of the process, not just people who are affected by it. StrategyActionCommunity ImpactDiverse TeamsHiring Black leaders and researchers in AI labsHelps catch bias early in the design phaseCommunity InputAsking Black communities to review new systemsStops harm in areas like hiring or credit scoresFair DataChecking data for gaps or racial biasMakes sure AI is accurate for every personClear AuditsSharing public reports on how AI affects peopleBuilds trust and keeps things transparent Where the policy has some blind spots Right now, the national strategy is mostly focused on being competitive on the global stage. That’s important, but it doesn’t say enough about how we’ll tackle systemic racism. We’re looking at two big risks if we don’t put equity first. First, automation could take away jobs from Black workers without giving them a path into new ones. Second, algorithmic bias in AI used for hiring or public services could make it even harder for people to get ahead financially. A better path for our national strategy Canada has a real chance to show the world how to do tech right. A better version of our national strategy would include a few key things: We need specific money set aside for Black led AI research and programs that help people learn digital skills. Any group getting federal money for AI should have to show how their work affects different racial groups through equity checks. We should set clear targets for Black representation in the tech jobs our tax dollars are supporting. Our AI plans should be linked directly to Canada’s Anti-Racism Strategy and the Black Justice Strategy to ensure better teamwork. Some simple truths about digital equity Tech isn’t neutral because it always carries the values of the people who built it. Being inclusive is a choice, which means we have to plan for fair results from the start. Data needs context because without looking at race, it often just reinforces the way things used to be. We can build a fairer future together Remembering our history means we can’t let another economic shift leave Black Canadians on the sidelines. Building inclusive AI isn’t just a technical goal, it’s the right thing to do. The Pan-Canadian AI Strategy is a powerful tool, but it’s not quite doing enough for Black communities just yet. Policymakers have a responsibility to make equity a requirement for any AI funding, while industry leaders need to invest in Black talent and build things with the community, not just for them. As readers and community members, we can play our part by supporting the organizations already doing the work. This includes groups like CILAR, which works to empower Black and Indigenous communities through tech innovation, and projects like the IBET PhD Project that aim to increase representation in academic leadership. We can even look to Canadian pioneers like Knockri, who are proving that AI can actually be used to reduce bias in hiring when it’s built with the right intentions. At the end of the day, inclusive AI development isn’t just about writing better code. It’s about building a better, fairer Canada for all of us. 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