Beyond Code: Powering AI; Canada’s Moment?

The rise of artificial intelligence (AI) is no longer just about algorithms, data, and software. Once confined to the minds of computer scientists, AI now depends on massive physical infrastructure: expanded electricity generation, resilient transmission and distribution grids, and high-performance data centres, supported by advanced semiconductors, critical minerals, and complex global supply chains. As AI penetrates every sector, from defense1 to finance2, it is driving surging demand for reliable, affordable, low-carbon power; leading-edge hardware manufacturing; and the construction and modernization of digital infrastructure.

This shift creates material challenges as well as opportunities, particularly for resource-rich countries such as Canada. This article first outlines AI’s infrastructure requirements and then examines how Canada could position itself as a key player by leveraging its energy and critical-mineral endowments, while identifying critical blind spots in current strategy.

Infrastructures Required for AI

The Need for Stable Energy

The electricity demand driven by the expansion of data centres and AI applications is surging. The International Energy Agency (IEA) estimates that data centres consumed approximately 415 terawatt-hours (TWh) in 2024, roughly 1.5% of global electricity consumption. This figure could more than double by 20303, to roughly 945 TWh, with AI a primary growth driver. In some economies, data centres could represent more than 20% of electricity demand growth by 2030, while in the United States, demand could grow more than thirtyfold by 2035, to 123 gigawatts, from 4 gigawatts in 20244.

Meeting this rising demand requires new generation capacity. Building renewable, nuclear, or gas-fired plants poses significant regulatory, environmental, and logistical challenges. Renewables face land-use constraints, and wind and solar intermittency is at odds with AI’s round-the-clock power requirements. Nuclear entails high upfront costs, licensing and safety requirements, and long lead times. Several recent data centre and AI infrastructure projects, including those led by xAI5, Oracle6, and Meta7 have turned to natural gas generation, citing its speed of deployment and ability to bypass grid interconnection delays.

The IEA emphasizes that accelerating deployment of clean generation is essential to meet AI-driven demand and climate commitments. In practice, countries must balance the urgency of capacity expansion with decarbonization targets, an increasingly complex policy challenge.

The stability and scalability of AI infrastructure also depend on grid modernization and the strategic siting of data centres. The IEA emphasizes that “a sole focus on increasing electricity generation won’t be enough […] countries must also think about their infrastructure.” Deloitte similarly notes that “the AI ambitions of the [U.S.] government and industry come up against the grid’s capacity to power or even interconnect data centers, as there is currently a seven-year wait for some requests to connect to the grid.”

Material Needs for AI Infrastructure

Beyond energy, AI relies on a wide range of materials: to build data centres (concrete, steel, copper, cooling systems) and to equip them (semiconductors and specialized chips, cabling, rare earths, and high-purity metals). The IEA warns that AI-driven growth will add pressure to critical-mineral supply chains—especially for copper and aluminium8, but also nickel, gallium, and silicon.

This pressure is not unique to AI: the global shift to electrification already fuels intense competition for the same scarce resources. The IEA’s Global Critical Minerals Outlook 20259 projects that demand for copper, lithium, and nickel could double or even triple by 2030, while supply remains concentrated in a few regions and vulnerable to geopolitical shocks.

In short, AI rests on heavy physical infrastructure underpinned by a finite, geopolitically sensitive mineral base. The growing overlap between AI and the broader energy transition underscores a key point: the sustainability and scalability of AI hinge as much on resource management and industrial policy as on innovation.

Canada as a Potential Key Player

Energy: Nuclear Development and Hydro-Québec’s Ambitions

Canada is a major energy producer, generating approximately 639 TWh of electricity in 2022, roughly 70% from renewables10. This baseline gives Canada a comparative advantage in powering energy-intensive digital infrastructure, such as AI data centres.

Building on this foundation, Canada is expanding its nuclear capacity. In 2023, Ontario Power Generation announced plans to build up to four small modular reactors (SMRs) at its Darlington site, together totalling about 1,200 megawatts (MW) of clean electricity11. These developments form part of a national effort to deploy next-generation nuclear technology12 that will provide stable, low-carbon baseload power to support industrial electrification and the growth of AI infrastructure.

Meanwhile, in Québec, Hydro-Québec is investing heavily to modernize and expand renewable capacity. Its Action Plan 2035 outlines $90–110 billion to add 8,000–9,000 MW of new capacity by 2035, primarily through hydro and wind. The plan also calls for approximately 5,000 km of high-voltage transmission lines to connect new generation and improve reliability across the province13.

Canada’s cold climate offers an operational advantage: data centres can significantly reduce cooling costs by using free-cooling techniques. For example, a Winnipeg data centre leverages ambient winter air to reduce energy use and costs14.

This cold climate, together with hydroelectric and nuclear capacity and Canada’s endowment of critical minerals required to build AI infrastructure, gives Canada strong prospects for AI-related investment.

The Blind Spots in Canada’s Strategy

Canada was the first G7 country to launch a national AI strategy in 2017: the Pan-Canadian Artificial Intelligence Strategy. The strategy aims to position Canada as a global AI leader by fostering research excellence, developing talent, and promoting commercialization. However, it focuses heavily on intellectual leadership and policy principles, with limited measures to address the physical requirements of large-scale AI deployment, including data centre capacity, digital infrastructure, and energy integration15.

Building on this framework, the federal government announced the AI Strategy Task Force on September 26, 202516. The initiative will address safe AI, public trust, and infrastructure. The task force, comprising experts from academia, industry, and civil society, will provide recommendations. Nonetheless, details on specific measures remain limited.

A major structural challenge is weak coordination among federal, provincial, and local authorities, as well as with Indigenous and community stakeholders17. While the federal government sets broad ambitions for AI, the energy transition, and digital sovereignty, implementation depends on provincial jurisdiction over energy, land use, and industrial planning. This fragmented governance results in inconsistent priorities and delays. The Wonder Valley data centre in northern Alberta, announced as a US$70 billion initiative to build one of the world’s largest AI computing hubs, illustrates these tensions18. Despite support from the provincial government, the project faced strong opposition from the Sturgeon Lake Cree Nation, citing inadequate early consultation and environmental and treaty-rights concerns. The controversy reflects a broader issue of social acceptability, a recurring barrier to large-scale industrial and digital infrastructure projects across Canada.

Overlapping regulations and permitting delays significantly hamper Canada’s ability to develop large-scale infrastructure. The Business Council of Canada describes the permitting system for major projects as “overly complex, time-consuming and a major impediment to attracting investment,” 19 noting that projects may face decades of approvals before construction begins. This maze of federal-provincial rules introduces uncertainty and cost escalation, especially problematic for high-capital, rapidly evolving sectors such as AI infrastructure.

In Québec, two strategic challenges stand out. First, the province has long reserved large blocks of electricity capacity for traditional energy-intensive industries, especially metallurgical and mining operations, while deprioritizing data centres. Hydro-Québec explicitly stated in 2022 that it “is in no way working to attract data centers,” reflecting hesitancy to dedicate scarce energy resources to sectors perceived as offering limited employment or local value creation. This cautious approach has left numerous projects, including major initiatives by Google in Beauharnois, waiting years for approval or grid connection. The provincial stance prioritizes long-term industrial diversification and resource-based manufacturing over rapid digital infrastructure expansion20.

Second, Québec’s Action Plan 2035 emphasizes wind and solar as complements to hydroelectricity, but their intermittency challenges the continuous power required by AI data centres. While this policy aligns with decarbonization goals, it may make Québec less attractive to hyperscale data centre operators, many of whom now favour regions with stable nuclear or natural gas baseload generation, such as Ontario or certain U.S. states.

Taken together, these challenges reveal a structural gap between Canada’s ambition to lead in AI and its capacity to provide the physical and regulatory foundations needed to sustain it. A recent partnership between the U.S. government, Westinghouse Electric Company, Brookfield Asset Management, and Cameco Corporation to deploy at least US$80 billion in new nuclear capacity—explicitly linked to AI data centres and compute—shows the global race to build AI’s physical backbone is already underway21.

Conclusion

The emergence of artificial intelligence marks a profound transformation in the global economy, one that is as material and infrastructural as it is digital and cognitive. Data centers, energy systems, and supply chains for critical minerals have become the true arteries of the AI age. As such, the countries that succeed in this new era will not be those that simply pioneer algorithms, but those that can secure, scale, and sustain the physical foundations of intelligence itself.

For Canada, the path forward hinges on bridging the gap between its research excellence and its industrial capabilities. With abundant clean energy, critical minerals, and a strong technological ecosystem, Canada holds the ingredients to become a champion of sustainable AI infrastructure. Yet, without a coherent, long-term coordination between federal and provincial levels and a streamlined regulatory environment, it risks remaining on the periphery of the next technological revolution.

Original article: https://emagazine.renewcanada.net/?pid=ODk8923274&v=3.10&p=31

  1. Ministère des Armées et des Anciens combattants (2025). Comprendre l’IA de défense. https://www.defense.gouv.fr/actualites/comprendre-lia-defense
  2. KPMG (2025). L’IA dans la fonction finance.
  3. International Energy Agency (2025). Energy and AI. https://iea.blob.core.windows.net/assets/601eaec9-ba91-4623-819b-4ded331ec9e8/EnergyandAI.pdf
  4. Deloitte (2025). Can US infrastructure keep up with the AI economy?. https://www.deloitte.com/us/en/insights/industry/power-and-utilities/data-center-infrastructure-artificial-intelligence.html
  5. Data Centers Going Off-Grid With Natural Gas to ‘Find Any Way to Get Power’ https://www.naturalgasintel.com/news/data-centers-going-off-grid-with-natural-gas-to-find-any-way-to-get-power/
  6. 'Go Where The Gas Is': Data Centers Follow Fracking In Search For Power https://www.bisnow.com/national/news/data-center-power/go-where-the-gas-is-data-centers-follow-the-fracking-in-search-for-power-131552
  7. Ibid.
  8. See 3
  9. International Energy Agency (2025). Global Critical Minerals Outlook 2025. https://iea.blob.core.windows.net/assets/ef5e9b70-3374-4caa-ba9d-19c72253bfc4/GlobalCriticalMineralsOutlook2025.pdf
  10. Government of Canada (2025). Energy Fact Book, 2024-2025: Clean power and low carbon fuels. https://energy-information.canada.ca/en/energy-facts/clean-power-low-carbon-fuels
  11. Government of Ontario (2023). Ontario Building More Small Modular Reactors to Power Province’s Growth. https://news.ontario.ca/en/release/1003248/ontario-building-more-small-modular-reactors-to-power-provinces-growth
  12. Governement of Canada (2024). Canada’s Small Modular Reactor Action Plan. https://natural-resources.canada.ca/energy-sources/nuclear-energy-uranium/canada-s-small-modular-reactor-action-plan
  13. Government of Québec (2023). Vers un Québec décarboné et prospère, Plan d’action 2025. https://www.hydroquebec.com/data/a-propos/pdf/plan-action-2035.pdf
  14. Economic Development Winnipeg. (n.d). Winnipeg’s cold climate means big savings for MTS Data Centres’ clients. https://www.winnipegedt.com/newsroom/read,post/596/winnipeg-s-cold-climate-means-big-savings-for-mts-data-centres-clients?dismiss=day
  15. Government of Canada (2025). Pan-Canadian Artificial Intelligence Strategy. https://ised-isde.canada.ca/site/ai-strategy/en
  16. Government of Canada (2025). Government of Canada launches AI Strategy Task Force and public engagement on the development of the next AI strategy. https://www.canada.ca/en/innovation-science-economic-development/news/2025/09/government-of-canada-launches-ai-strategy-task-force-and-public-engagement-on-the-development-of-the-next-ai-strategy.html
  17. The Dais (2024). From Potential to Performance: Roundtable Report on Canada’s Investment in AI Compute Infrastructure. https://dais.ca/wp-content/uploads/2024/10/AI-Roundtable-Summary-Report_V4.pdf
  18. E. Rubayita (2025). Alberta First Nation voices 'grave concern' over Kevin O'Leary's proposed $70B AI data centre. CBC. https://www.cbc.ca/news/canada/edmonton/alberta-first-nation-voices-grave-concern-over-kevin-o-leary-s-proposed-70b-ai-data-centre-1.7431550
  19. Business Council of Canada (2025). Stifled by red tape. https://www.thebusinesscouncil.ca/report/stifled-by-red-tape/
  20. L. Arbour and S. Mayer (2025). Les centres de données au Québec. Bibliothèque de l’Assemblée Nationale. https://premierelecture.bibliotheque.assnat.qc.ca/2025/02/10/les-centres-de-donnees-au-quebec/
  21. Brookfield (2025). United States Government, Brookfield and Cameco Announce Transformational Partnership to Deliver Long-term Value Using Westinghouse Nuclear Reactor Technology. https://bam.brookfield.com/press-releases/united-states-government-brookfield-and-cameco-announce-transformational-partnership
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