Canadian Science Policy Magazine

Canada’s National AI Strategy, “AI For All” [1], presents an ambitious vision to foster trust, opportunity, and sovereignty across the socio-techno-economic value chain for the Canadian AI sector. The strategy treats AI infrastructure and energy requirements as strategic assets, rather than afterthoughts. This is in contrast to the 2025 America’s AI Action Plan [2] and the European Commission’s approach to AI [3], where both lacked a vision for supporting AI infrastructure.

Canada’s new AI strategy is ambitious in its main goal: increase public trust so that more Canadians will adopt AI across the country. Among other commitments, the strategy pledges free AI literacy training for 1 million entry-level post-secondary students, access to trusted AI agents, and 90,000 jobs and placements for young Canadians. These are lofty goals.

Canada’s National Artificial Intelligence Strategy: AI for All is a strategic and timely investment in the country’s future. The identification of health and life sciences as a priority sector in AI for All is further reinforced by the targeted multi-billion-dollar investment in the new AI Missions Program to improve “health outcomes for Canadians” (Innovation, Science and Economic Development Canada, 2026).

In May, a Toronto man decided to sell his car back to the dealership he had bought it from. He submitted an online inquiry. Someone named Quinn texted back, offered him $27,162.79, agreed to take his counteroffer to the manager, and booked a time to close the deal. Then a human sales consultant called informing him that the offer was void. Quinn was a chatbot which made the offer an error, and the real number was closer to $20,000.

In June 2026, Canada released a national AI strategy assembled largely without the humanities and social sciences in the room. That same season, everywhere else, those disciplines were being summoned. The frontier AI laboratories were hiring philosophers at pace; the press was declaring the revenge of the humanities graduate; and the Pope’s first encyclical, a document on artificial intelligence, drew its deepest arguments from precisely the traditions our policy process had left in the lobby.

The International AI Safety Report (2025) identifies algorithmic bias, unequal access, and lack of representation as major risks that may prevent AI systems from delivering equitable societal benefits. Similarly, the African Union Continental Artificial Intelligence Strategy (2024) highlights the importance of inclusive AI development, responsible innovation, and reducing inequalities caused by emerging AI technologies.

Canada is becoming a super-aged nation this year with 20% of its population over the age of 65. At the same time, Canada is seeking to translate its research leadership in AI into broad social and economic benefits through its new AI for All strategy. We have a tremendous responsibility, but also a remarkable opportunity, to support AI prosperity by considering these societal transformations in tandem.

Canada’s new National AI Strategy declares that trust is its north star. On this, the government is right: nothing else in the document works without it. AI for All is candid about the problem. Canadians rank 42nd of 47 countries on trust in AI systems and 44th on AI literacy, and business adoption sits at 12 percent. The strategy’s response is a causal chain stated with unusual clarity: for Canadians to benefit from AI, they must use it; to use it, they must trust it. Read that sequence again.

There is an opportunity to shape the new “AI for All” strategy into something truly Canadian by embracing diversity and setting a new standard of inclusion. While modern AI modeling techniques continue to drive incredible progress, they increasingly require energy, water, and scaling to continue development at the current pace. The Canadian government and investors must expand their focus beyond established academic and technology centers.

Long before artificial intelligence (AI) could deliver the mysteries of the universe on a platter or double as a digital confidante, I built my understanding of the world the hard way. As a teenager, I’d spend hours crouched over a boombox, rewinding songs to transcribe the lyrics on looseleaf paper, then staring at the ceiling trying to decipher their meaning. Afterward, I’d lie on my bedroom floor writing diary entries, scaffolding my big emotions onto those song structures.