Canada releases "AI for All" strategy: a difficult leap from leading in scientific research to sovereign applications.

Event: Canada Releases "AI for All" National Strategy

In 2025, the Canadian government officially unveiled the new "National Artificial Intelligence Strategy: AI for All." The strategy document, published by Innovation, Science and Economic Development (ISED), puts forward three core values—"trust, opportunity, sovereignty"—and promotes the widespread application of AI in Canadian society through six pillars. The goal is clear: let AI serve all Canadians, not the other way around.

The six pillars include: protecting Canadians and democracy, ensuring AI empowers Canadians, driving AI adoption for shared prosperity, building a sovereign AI foundation for Canada, scaling up Canadian champion companies, and establishing trusted partnerships and global alliances. These pillars are not designed in isolation but follow a logical chain: trust makes adoption possible, while opportunity and sovereignty ensure adoption delivers long-term benefits.

The ministerial address specifically highlighted several application scenarios: a pediatric cardiologist in Halifax uses AI to diagnose heart murmurs in newborns; Canadian company Croptimistic helps farmers precisely map soil to reduce fertilizer use and increase yields; AI also helps advanced manufacturing, auto parts, and mining companies remain competitive amid global trade disruptions. These examples seek to show that AI is not an abstract concept—it is already improving Canadians' lives.

Deeper Causes: The "Fault Line" Between Innovation and Adoption

Canada is widely recognized as an AI research powerhouse. Nobel laureate Geoffrey Hinton, Turing Award winners Yoshua Bengio and Richard Sutton—three "godfathers of AI"—are all Canadian researchers. Canada has world-leading university programs and national AI institutes, and even one of the few frontier model companies. Yet innovation advantages have not automatically translated into economic advantages.

The data reveal a stark reality: from mid-2024 to mid-2025, only 12% of Canadian businesses used AI to produce goods or services, and only 14.5% planned to do so by 2026. Small and medium-sized enterprises fare even worse, with just 8% adopting AI, far behind Nordic countries (29% to 42%), Germany (26%), and France (18%). At the individual level, the diffusion rate is 37%, ranking 15th globally, but still behind countries such as the UAE, Singapore, and Norway.

The deeper issue lies in trust and skills. According to the global trust study by KPMG and the University of Melbourne, Canada ranks 44th in AI training and literacy and 42nd in trust out of 47 countries. Only 24% of Canadians have received any AI training, fewer than 40% say they have some understanding of AI, and less than half believe they can effectively use AI tools. Public sentiment even leans negative: 34% think AI is beneficial to society, 36% think it is harmful, and half believe AI poses a threat to humanity.This disconnect between strong innovation and weak adoption is the fundamental reason behind the strategy. What Canada lacks is not technology, but the social infrastructure needed to truly put it into practice—including skills training, public trust, and sovereign digital infrastructure.

Industry Impact: From Laboratory to Factory

The "AI for All" strategy explicitly treats adoption as the core driver of value. This means future policy resources will tilt toward the application side, rather than merely supporting research. For Canadian industry, this will bring several consequences:

First, small and medium-sized enterprises will become a key focus of support. Given that SME AI adoption is only 8%, the strategy is likely to introduce targeted incentives, training programs, and low-barrier tools to help them achieve digital upgrading. Priority sectors such as advanced manufacturing, agriculture, healthcare, and clean energy will benefit first.

Second, the building of sovereign AI infrastructure will drive new capital expenditure. Canada's sovereign computing capacity is still in its infancy, relying on foreign suppliers for cloud services and chips. The strategy's proposal to "build a Canadian sovereign AI foundation" implies that the government may invest in domestic computing centers, chip supply chains, and energy infrastructure. Given that Canada's power grid is among the cleanest in the world, the low-cost, low-carbon electricity that clean energy provides for AI will become a key competitive advantage.

Third, the entrepreneurial and investment environment in AI may become more vibrant. Canadian AI companies have already accumulated over CAD 37 billion in venture capital and count more than 3,500 active AI enterprises. The strategy's pillar of "expanding Canadian champion companies" could help these firms go from domestic to global through government procurement, export support, and global partnerships.

Significance for Canada: Sovereign AI and the Export of Values

The strategic significance of this plan goes far beyond the economic dimension. Amid intensifying global geopolitical competition, Canada has explicitly made "sovereignty" a core pillar. This means Canada will not only use AI, but also maintain autonomy over AI infrastructure, technical standards, and governance models, reducing dependence on other countries' technology systems.

Canada's dilemma is this: across the AI value chain—from energy and chips to computing, models, and applications—Canada has a presence at every level, yet there are critical dependencies. GPU chip manufacturing is almost entirely overseas, and sovereign computing capacity is insufficient. The strategy's emphasis on "sovereign AI" is essentially about building a self-controllable technology ecosystem that aligns with Canadian values.

Meanwhile, placing "protecting democracy" and "protecting Canadians" at the very front of the strategy reflects concerns about disinformation, privacy violations, and the security of democratic institutions. In AI governance, Canada has chosen a middle path—different from the U.S. laissez-faire approach and Europe's strict regulation—by emphasizing "responsible, safe, sovereign" AI and building long-term competitiveness through trust.This positioning could make Canada a global representative of "trust-based AI." If the strategy succeeds, Canada will not only export AI technologies and products, but may also export a trust-based AI governance paradigm that other countries can use as a model.

Global Trend: The AI Race Enters a "Trust-First" Stage

"AI for All" is not an isolated domestic policy, but a signal that the global AI race has entered a new phase. Over the past decade, countries have competed for leadership in AI research; over the next decade, competition will shift to adoption speed, governance quality, and infrastructure sovereignty.

Canada's strategy reflects a global consensus: competitive advantage in AI depends not only on model capabilities, but also on whether society can trust and widely use AI. Societies with low trust and low literacy, no matter how advanced their technology, cannot turn innovation into productivity. This is precisely the bottleneck Canada hopes to break.

Moreover, the construction of sovereign AI infrastructure is becoming a new focus of great-power competition. Economies such as the EU, Japan, and India are all investing in domestic computing power, and Canada is no exception. Whoever can build autonomous and controllable AI infrastructure earlier will secure a more advantageous position in the global trade landscape.

Long-Term Perspective: What Deserves Sustained Attention

What truly deserves long-term attention is whether Canada can bridge the gap between "leading in research" and "lagging in adoption." Over the past decade, Canada has proven it can produce world-class research; over the next decade, it must prove it can turn that research into widely used products and services. This requires collaborative efforts from government, businesses, educational institutions, and the public, as well as sustained investment and institutional innovation.

Another strategic focal point is the pace of investment in sovereign AI infrastructure. Canada has clean energy, political stability, and an open economy—all favorable conditions for building AI data centers. If Canada can deeply integrate clean energy with AI computing, it is entirely possible for it to become a major global supplier of AI computing power, thereby changing its current passive reliance on external infrastructure.

Ultimately, the strategic significance of "AI for All" lies in its attempt to make AI a cornerstone of Canada's economic prosperity and social well-being, rather than a tool for a small elite or multinational corporations. Whether this succeeds will determine Canada's international standing in the AI era and provide other countries with an experimental sample of "how to develop AI on the foundation of trust."

---

Reference source: Canada’s National Artificial Intelligence Strategy: AI for All