As Canada awaits its national AI strategy, policymakers face a pivotal choice: to focus narrowly on frontier  model research and development or seize a larger economic opportunity by centering AI adoption as a priority.  

Despite being a global leader in AI research, the Canadian economy lags on adoption. Canada urgently needs to broaden its ambition to also become a leader in the adoption of AI. A Statistics Canada analysis in 2025 found that the firm-level adoption rate of 12 per cent places Canada behind other countries — including  India, Singapore and the UAE — all of whom command adoption rates near or above 50 per cent. 

“We have pioneering frontier AI research, and we have some of the best companies in the world, but  Canadians and Canadian companies are lagging on adoption,” Minister of Artificial Intelligence and Digital Innovation Evan Solomon told BNN Bloomberg last year. 

The evidence is clear: countries that benefit most from AI are not necessarily those that invent it first, but  those that diffuse it the fastest across sectors and public services. A successful AI strategy for Canada should not only be judged by how quickly the country develops the latest technology or how many research grants it awards, but by whether it helps companies, workers, and governments use AI to solve  practical problems and increase productivity. 

The AI Adoption Initiative recommends Canada’s strategy focus on five key priorities: 

First, investment in applied AI skills. Productivity gains come when workers across health care, manufacturing, energy, and public services can combine domain expertise with accessible AI tools.  Canada needs applied training pathways through colleges, vocational programs, and on-the-job upskilling focusing on small and medium-sized businesses that consistently lag on adoption. To fully harness the opportunities from AI, Canada should deploy a comprehensive talent strategy that differentiates the needs of research talent like PhD-level scientists and applied talent like engineers, developers, and domain  experts with AI skills.  

One of the most significant shifts since Canada published the world’s first national AI strategy in 2017 is how AI has gone from something that a few thousand individuals with PhDs could unlock benefits from, to something that now billions of everyday workers can use ‘out-of-the-box’ and that millions of Information and Communications Technology (ICT) workers, equipped with the right data engineering skills, can tailor for domain-specific tasks. For example, this is especially useful for high-pressure fields like healthcare,  where domain-specific AI is providing a second pair of eyes for medical imaging specialists to quickly and  accurately identify abnormalities in patient scans. For Canada, this means ensuring that it must not only have some of the world’s most elite AI talent, but also the world’s most ‘AI-ready’ workforce. 

Second, the strategy should emphasize supporting adoption through applied research. This means ensuring access to the same state-of-the-art infrastructure as world-class industry labs, incentivising engagement in cross-disciplinary R&D in line with local specialization and industry strengths, and  ensuring access to purpose-built, domain-specific datasets that can fine-tune applied AI models. The  government should prioritize targeted investments in digital infrastructure, expand access for industry, and  reduce regulatory barriers to innovation and adoption.

Third, Ottawa should continue to lead through public sector AI adoption. Governments are among the  largest potential buyers of AI-enabled services. Strategic procurement, clear departmental adoption  roadmaps, and leadership can both improve service delivery and stimulate private-sector demand. 

Fourth, Canada should modernize and expand incentive frameworks to support applied AI rather than just  research. Investments in fine-tuning, integration, and deployment are where productivity gains are  realized. Expanding on existing programs to facilitate adoption of AI across economic sectors, including  SMEs, academic institutions, and public and private sector entities.  

Finally, Canada should pursue targeted, interoperable regulation that enables adoption rather than  hindering it. Regulatory clarity, alignment with international standards, and sector-specific approaches for SMEs can build trust while avoiding fragmentation that raises costs for adopters. 

When governments pursue bold, forward-looking AI adoption; there is a possibility to drive broad sectoral  transformation. Canada’s AI strategy can serve both inventors and adopters. AI is a general-purpose  technology, like electricity or the internet. Its economic impact will come from the often-overlooked  process of diffusion across the economy. If the Canadian government prioritizes adoption in its upcoming national AI strategy, and gets it right, it will translate AI leadership into productivity growth, better public services, and shared economic prosperity.  

Nicole Foster is the co-founder of the AI Adoption Initiative (AIAI), a global community of policy experts dedicated to accelerating the  responsible adoption of artificial intelligence across the economy. Partner organizations include Amazon Web Services, the Canadian  Chamber of Commerce, the U.S. Chamber of Commerce, SeedAI, Computer and Communications  Industry Association, Fundación País Digital, CENIA and others.

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