Canada’s National AI Strategy, explained
Canada’s National Artificial Intelligence Strategy, titled AI for All, is the federal government’s plan for how the country will use, regulate, and build artificial intelligence. Published by Innovation, Science and Economic Development Canada and last updated 8 June 2026, it organizes policy around three ideas: trust, opportunity, and sovereignty. Adoption sits in the middle. People and firms will only use AI at scale if they trust it, see a clear payoff, and believe the underlying systems are not wholly controlled elsewhere.
The strategy does not invent Canada’s AI sector from scratch. It responds to a specific mix of strengths and gaps: strong research and a large AI business base, weak day-to-day adoption, thin sovereign compute, and public skepticism. It sets numbered targets for literacy, jobs, business uptake, infrastructure, and international partnerships, and it groups work into six pillars plus five priority sectors.
What Canada looks like on AI today
Canada’s digital sector employs about 800,000 people and contributes more than $140 billion to GDP. Roughly 150,000 jobs are tied directly to AI. More than 3,500 Canadian firms build AI models, tools, or applications, and those firms have raised more than CAD$37 billion in venture capital.
Research credentials are concrete. Geoffrey Hinton, Yoshua Bengio, and Richard Sutton did foundational work in Canada. The three national AI institutes (Amii, Mila, and the Vector Institute), plus CIFAR and the Canada CIFAR AI Chairs program, still concentrate talent. Canada also has at least one frontier model company, Cohere, and a safety-focused nonprofit, LawZero, founded by Bengio and incubated at Mila.
Adoption tells a different story. Statistics Canada found that only 12 percent of Canadian businesses used AI to produce goods or services between mid-2024 and mid-2025, with 14.5 percent planning to do so by mid-2026. Among small and medium-sized enterprises, adoption sits near 8 percent, behind Nordic countries (29 to 42 percent), Germany (26 percent), and France (18 percent). Individual diffusion is stronger: Canada ranks 15th globally at 37 percent.
Trust and skills lag further. In the KPMG–University of Melbourne global trust study, Canada ranked 44th of 47 countries on AI training and literacy, and 42nd of 47 on trust in AI systems. Only 24 percent of Canadians report any AI training. Public opinion is split: 34 percent see AI as good for society, 36 percent as harmful, and half view it as a threat to humanity.
Infrastructure is uneven. Canada has companies across applications, models, data centres, hardware, energy, and research. Sovereign compute and cloud capacity remain limited, GPU chip fabrication sits mostly offshore, and the electricity grid, while largely clean, is constrained for large AI buildouts. The strategy treats those dependencies as strategic exposure, not a side issue.
Stated outcomes
The government lists measurable aims rather than a single slogan. Among them:
Raise business AI adoption from 12 percent today to 60 percent by 2034.
Create up to 90,000 AI-related jobs and work placements for young Canadians, SMEs, and nonprofits by 2031, and help create up to 250,000 new jobs through AI adoption by 2031.
Target about a 3 percent GDP lift (nearly $200 billion) from labour productivity gains tied to AI commercialization and use.
Give free AI literacy training at national scale, reach 1 million entry-level post-secondary students, and more than double K-12 teacher training to over 3,000 educators.
Ensure all post-secondary students have access to trusted AI agents.
Launch an AI Missions Program, starting with $200 million for health outcomes.
Build a major public supercomputer and expand sovereign compute by 2031.
Update privacy and online safety law, expand the Canadian AI Safety Institute, and form deeper alliances on sovereign technology.
Those figures are government targets. Whether they hold will depend on budgets, provinces, employers, and execution after 2026.
Priority sectors
Investment is meant to concentrate where Canada already has industrial weight:
- Health and life sciences
- Energy and natural resources
- Transportation
- Agriculture
- Manufacturing and robotics
- Dual-use and defence-aligned applications are also in scope, in line with the Defence Industrial Strategy.
Pillar 1: Protect people and democracy
The first pillar treats safety as a precondition for adoption. The document names risks that are already visible: AI in hiring, lending, healthcare, and public services; deepfakes and synthetic media; election interference; biased systems; and misuse of personal data, including surveillance pricing.
Planned legal work includes modernizing consumer privacy law (including a stated fundamental right to privacy and stronger child protections), introducing online safety rules, and protecting elections from AI-enabled misinformation and foreign interference. A review of the Privacy Act for government use of personal information continues.
Safety capacity gets cash and programs. Canada plans $50 million to expand the Canadian AI Safety Institute for risk tracking, technical research, and model evaluation. Other measures include watermarking and transparency work, a Canada Trusted AI Certification program, renewed Standards Council of Canada AI program funding, and faster applied AI for fraud, extortion, cyber defence, and threat detection with law enforcement and security agencies.
Pillar 2: Skills, work, and culture
Pillar 2 is about literacy, jobs, and whether Canadian languages and cultures show up in the tools people use.
A National AI Literacy Initiative is supposed to offer entry-level training to anyone. Content is meant to reach 1 million entry-level post-secondary students and more than 3,000 classroom educators. Public libraries and community groups are named as delivery partners, especially in rural, remote, and northern regions. Budget 2025 already put $50 million over five years into modernizing the Job Bank with AI matching and an online adult training platform. CanCode gets $30 million for free digital skills for K-12 students and teachers.
On work, the strategy projects up to 90,000 AI-related opportunities: 45,000 through the Student Work Placement Program and Canada Summer Jobs, 35,000 through programs such as Skills for Success, and 10,000 through Mitacs ADOPT and AI+X. It also calls for mid-career upskilling (including trades), use of colleges, CÉGEPs, and polytechnics for applied AI, and tracking of labour-market effects through Statistics Canada’s Artificial Intelligence and Technology Measurement Program.
Culture and inclusion sit here too: tools that protect French, a $50 million Creative Technology Program for creators, promotion of Canada’s accessible AI standard, Gender-Based Analysis Plus across AI policy, and support for Indigenous-led AI (language, land, cultural heritage), building on existing programs at Canadian Heritage, the National Research Council, and Mila.
Pillar 3: Adoption and shared payoff
Pillar 3 attacks the gap between experimenting with chat tools and putting AI into operations. Micro, small, and medium firms are 99 percent of Canadian businesses and employ 14.3 million people. Only about one in eight businesses has formally integrated AI. Statistics Canada reports that 78 percent of non-adopting firms say they do not see how AI helps their goods or services. The strategy frames that as a translation problem: firms want sector-specific uses with a clear return.
Money and programs follow that diagnosis. The Business Development Bank of Canada’s LIFT program is a $500 million financing line for SME AI tools. Another $500 million expands the Regional Artificial Intelligence Initiative through Regional Development Agencies. There are plans for an AI Literacy and Adoption Assessment tool, Small Business and Entrepreneurship Development Program supports, and use of the SR&ED tax credit and the Productivity Super-Deduction from Budget 2025.
National “missions” are the other lever. The first commits $200 million to health outcomes. Sector workforce alliances are planned across six priority areas to line up employers, unions, schools, governments, and Indigenous partners on skills and talent.
Government itself is cast as an early customer: faster federal AI procurement through the Office of Digital Transformation, and a Prime Minister’s Innovation Fellows Program to bring technical talent inside government while keeping humans in the loop on consequential decisions.
Field examples in the strategy are specific rather than abstract. Croptimistic’s soil mapping is used on farms in Canada and abroad. CHARTWatch at St. Michael’s Hospital in Toronto cut unexpected ward deaths by 26 percent after deployment, according to a study in the Canadian Medical Association Journal. Those cases are used to argue for outcome-based spending, not AI for its own sake.
Pillar 4: Compute, data, and talent at home
Sovereignty, in this document, means compute and cloud under Canadian law, usable public and sector data, and researchers who stay (or arrive) in Canada.
On energy and data centres, more than 83 percent of Canada’s electricity already comes from renewable and low-emission sources. The National Electricity Strategy aims to roughly double electricity infrastructure by 2050. Cold climate is treated as a cost advantage for cooling. Analysis cited in the strategy suggests commercial players may need about 5.5 GW of AI compute by 2030. The government says it will keep delivering more than $2 billion already committed to Canadian AI compute, including through the AI Compute Challenge, and pursue partnerships that could provide about 850 MW by 2030, with possible scaling toward 2.3 GW.
Key actions include a public supercomputer for researchers and SMEs; large AI data centres designed to scale to at least 100 MW; more fibre and satellite capacity; stronger chip design and fabrication, including a spin-off of the National Research Council’s Photonics Fabrication Centre; and more secure sovereign cloud and digital systems for government.
On data, $100 million goes to a Health Sector Data Space with the Canadian Institute for Health Information, and another $100 million expands VITAL, a pan-Canadian hospital clinical data platform, into five more provinces. VITAL is already used for projects such as heart disease prediction and sepsis detection, with more than 80 Canadian companies working on health data and AI.
On talent, Canada CIFAR AI Chairs are to rise from 130 to nearly 200. The Global Talent Stream is to speed entry for skilled AI workers, with permanent residency measures aimed at retention, on top of a broader $1.7 billion talent attraction package from Budget 2025.
Pillar 5: Keep scale-ups in Canada
Pillar 5 starts from a blunt problem: Canadian research is strong, but many firms scale elsewhere. Nearly 70 percent of Canadian-led startups end up headquartered outside the country, according to the strategy. Canada ranked fifth globally in AI venture capital with $3.1 billion invested in 2025, yet deal concentration and trade uncertainty still push companies toward U.S. capital and customers.
Responses include a $500 million Canadian Tech Growth Fund that can take equity stakes in promising AI firms; Budget 2026 work on mechanisms so Canadians reinvest tech gains into new Canadian startups; $1.75 billion from Budget 2025 to stimulate private venture capital; and government acting as an anchor buyer under Buy Canadian policy.
For SME commercialization: an extra $700 million in affordable sovereign compute through an expanded Compute Access Fund; $130 million for institute commercialization programs, including Founders-in-Residence; better alignment of existing innovation programs; and $159 million through Elevate IP and IP Assist. The Venture Scientist Fund (US$100 million), launched in January 2026 by Mila and Inovia Capital, is cited as a private-public path from lab research into company creation.
Foundation models are treated as strategic. Cohere is named as an enterprise and government-focused model company. LawZero is named as a nonprofit building safety and oversight tools for powerful systems. The government says it will keep foundation-model capacity anchored in Canada and support safety-first research as a commercial and export trait.
Pillar 6: Alliances and open source
Pillar 6 assumes AI markets are concentrating around a few large providers, and that middle powers need shared infrastructure, standards, and procurement to keep options open.
In February 2026, Canada and Germany launched the Sovereign Technology Alliance on shared models, digital infrastructure, capital, joint research, and evaluation standards. Canada plans to expand that alliance and use the Trade Commissioner Service to sell Canadian AI abroad and attract investment.
Open-source AI is an explicit strand: cheaper deployment, easier local fine-tuning, more transparency, and less lock-in for SMEs, nonprofits, and researchers. Canada says it will lead a multi-country push to fund public-interest open-source AI and build shared inventories of tools that fit Canadian needs, including on-premises use where privacy or security require it.
Recent trade figures in the document are concrete: 20 new economic and defence partnerships in the past year, nearly $100 billion in foreign investment commitments, and 11 of those partnerships with an AI component. Europe (Germany, UK, France, EU, Finland, Norway), the Indo-Pacific (Australia, India, Japan), and the Middle East (UAE, Qatar, Saudi Arabia) are named as focus regions.
How the pieces fit
Read as a whole, AI for All is less a research manifesto than an industrial and civic plan. Trust work (law, safety institute, certifications) is meant to unlock adoption. Literacy and jobs programs are meant to make adoption usable for people, not only vendors. SME finance, missions, and government procurement are meant to turn experiments into productivity. Compute, data spaces, and chairs are meant to keep more of the stack and talent under Canadian control. Capital and alliances are meant to stop the pattern where Canadian IP is invented here and scaled somewhere else.
The strategy also says it will be revised as the technology moves. The fixed parts are the three anchors (trust, opportunity, sovereignty), the focus on adoption, and the six-pillar layout. The movable parts are sequencing, budgets, and which missions follow health.
Source
Government of Canada, Innovation, Science and Economic Development Canada. Canada’s National Artificial Intelligence Strategy:
AI for All. Date modified: 2026-06-08.
