Canada sees AI as critical infrastructure: middle powers compete for a “sovereign AI” path

Canada Sees AI as Critical Infrastructure: Medium Powers Compete for a “Sovereign AI” Path

The latest AI strategy released by the Canadian federal government sends a clear signal: artificial intelligence in Canada is no longer just a tool for industrial promotion, but has been incorporated into a national capability-building framework, alongside energy and national defense, as critical infrastructure. This means Ottawa is trying to answer a bigger question: in the global AI race dominated by the United States and China, can medium powers still preserve technological autonomy, industrial competitiveness, and room for governance?

What happened

The strategy, titled “AI for All,” has three core directions.

First, Canada wants to reduce its dependence on U.S. tech giants and promote a more independent path for AI development.

Second, the government stresses that it cannot go it alone, but must advance AI capability building in coordination with international partners. The document names a number of partners with shared demands for AI independence, including Germany, the United Kingdom, France, Finland, Norway, and the EU, while also bringing Japan, Australia, India, and the UAE into its cooperation horizon.

Third, Canada is focusing AI deployment on several specific industries: healthcare and life sciences, energy and natural resources, transportation, agriculture, and manufacturing and robotics. At the same time, the government also proposes to bring AI more deeply into the classroom and provide support for businesses adopting AI and taking part in international competition.

In parallel, there are also policy signals in governance and infrastructure: modernizing federal privacy laws, advancing legislation on online safety for children, continuing to address AI deepfakes and other online harms, and expanding Canada’s domestic data center, cloud infrastructure, and semiconductor capacity. Previously, the federal government had also announced plans to build a supercomputer scheduled for completion in 2031.

Why this is happening

Behind this policy shift is, first of all, a structural change in geopolitical and technological competition.

AI competition is no longer just a contest over model performance, but a comprehensive competition involving computing power, data, cloud platforms, chips, application ecosystems, and regulatory rules. For a medium power like Canada, overreliance on foreign platforms and infrastructure would leave industrial upgrading constrained by external technology stacks, and in the long run could put it in a passive position across data, cloud services, chips, and enterprise AI applications.

Second is the issue of public trust.

The real challenge for Canada in AI and digital governance is not simply whether AI can be used, but whether the public is willing to use it. The policy document emphasizes that Canadian society still lacks sufficient trust in AI. Over the past year, Minister of Artificial Intelligence Evan Solomon has repeatedly stressed that technological innovation is advancing quickly, but the pace of adoption depends on trust. That is also why updates to privacy law, online protection for children, and deepfake governance are being placed in the same policy framework as industrial policy.

Third is competitive pressure in industry.Canada does not lack research capacity or talent reserves, but it has long faced a structural problem of “strong research, weak industrial chains” when it comes to turning scientific research into commercial scale and expanding local innovation into global competitiveness. The strategy specifically emphasizes helping small and medium-sized enterprises gain AI capabilities, which shows that the government has already realized this: if AI remains confined to a small number of large companies or laboratories, there will be no national productivity gains or industrial diffusion.

Finally, there is also a push at the level of value narratives.

Canadian Prime Minister Mark Carney discussed the responsible use of AI with Pope Leo XIV, emphasizing that technology must serve humanity and protect individuals. This kind of statement is not merely a moral posture, but rather an effort to build an international identity for Canada’s AI path that is “trustworthy, responsible, and governable.” For a middle power that hopes to have a voice in shaping global AI rules, governance ideas themselves can also become a competitive asset.

What this means for Canadian industry

From an industrial perspective, the most important change in this strategy is not “encouraging more people to use AI,” but elevating AI into a matter of infrastructure and industrial-system restructuring.

1. AI infrastructure will become a new national priority in competition

Localizing data centers, cloud, and semiconductor capabilities means Canada is trying to fill in the most critical foundation of the AI era. The threshold for future AI competition will no longer be just algorithms and applications, but the availability of compute, data sovereignty, the cost of training and inference, and the controllability of key supply chains. For Canada, this will directly affect the cost and bargaining power of AI use for local startups, research institutions, the public sector, and large enterprises.

2. Industry deployment will determine the strategy’s success or failure

Concentrating investment in healthcare, energy, transportation, agriculture, manufacturing, and robotics shows that Canada hopes AI will first be translated into productivity gains in the real economy, rather than merely chasing trends in consumer internet or general office software. This choice fits Canada’s industrial structure, and it is more likely to create synergies with its resources, manufacturing base, healthcare system, and engineering capabilities.

3. Small and medium-sized enterprises will be key to diffusion efficiency

The strategy specifically mentions supporting SMEs in using AI. This detail matters because Canada’s economic structure includes a large number of SMEs, but they often lack the ability to build models in-house, purchase cloud compute, or assemble AI teams. If policy tools truly lower the adoption threshold, AI could become one of the few levers Canada has for improving total factor productivity; otherwise, the AI dividend will still remain concentrated in a small number of leading firms.

4. Regulation and commercialization will be tied together

The simultaneous advancement of privacy, online child safety, deepfake governance, and AI industrial policy means Canada will not take the path of “open up first, fix later.” For entrepreneurs and capital, this may raise compliance costs, but it may also increase market trust, especially benefiting AI commercialization in high-trust sectors such as healthcare, finance, education, and public services.## What this means for global tech competition

Canada’s move reflects a broader global trend: AI is shifting from “platform competition” to “sovereignty competition.”

The United States and China remain the two poles of the global AI race, but more and more countries are unwilling to fully accept a landscape in which technological direction, data flows, and infrastructure dependence are determined by a small number of super-platforms. Germany, France, the UK, the EU, as well as Japan, Australia, and India, which Canada views as partners, indicate that a “middle power alliance” is forming new networks of cooperation around AI autonomy.

The significance of such networks is not in replicating an American-style AI ecosystem, but in building more distributed capabilities: local cloud and computing power, regionalized regulation, trusted data governance, cross-border R&D collaboration, and standards for industrial deployment. In other words, global AI competition is expanding from “who has the strongest model” to “who can embed models into broader industrial, legal, and social systems.”

Within this framework, Canada’s role may not be that of the world’s largest AI producer, but rather a key participant in rules and infrastructure: it must both maintain its connection to the U.S. tech system and avoid being fully locked into it; it must attract international talent and capital while retaining local data, computing power, and industrial control.

What changes may happen over the next 3–10 years

If this strategy continues to move forward, Canada’s tech industry could see several directional changes:

• Rising investment in AI infrastructure: domestic data centers, cloud resources, computing capacity, and semiconductor-related initiatives will continue to be a focus of policy and capital.
• Faster deployment of sector-specific AI: healthcare, energy, agriculture, manufacturing, and other fields are more likely to become the main battleground for AI commercialization in Canada.
• A more systematized regulatory framework: issues such as privacy, online safety, deepfakes, and child protection will gradually be incorporated into a unified digital governance framework.
• More global talent competition: Canada will more actively compete for AI research, engineering, and productization talent, especially people who can connect research and industry.
• Stronger cooperation among middle powers: Canada’s ties with Europe and Indo-Pacific partners around AI rules, computing power, and industrial collaboration may deepen.

Long-term trend: what Canada really needs to pay attention to

What is truly worth watching is not how many slogans this strategy puts forward, but whether Canada can connect three things into a closed loop:

1. Turn AI into controllable national infrastructure; 2. Turn research into scalable industrial capability; 3. Turn governance and trust into an international competitive advantage.

If these three elements can form a positive feedback loop, Canada will be more than just a “country that uses AI”; it may become one of the few middle powers capable of competing simultaneously in technology, rules, and industrial standards.If these three elements can form a positive feedback loop, Canada will not merely be a “country that uses AI,” but could become one of the few middle powers capable of competing simultaneously in technology, rules, and industrial standards. For Canada’s future technology industry, the strategic significance of this lies in the fact that it will determine whether Canada continues to rely on external AI ecosystems or gradually builds its own sustainable digital sovereignty and industrial resilience.