2024 was a milestone year for Canadian AI, highlighted by British-Canadian computer scientist Geoffrey Hinton receiving the Nobel Prize in Physics for his groundbreaking work in artificial intelligence (AI).
This achievement underscored Canada’s robust tradition of AI research and talent. However, despite its strong foundations, Canada struggled to position itself in the highly competitive and capital-intensive global AI race.
Canada’s AI Strengths and Opportunities
Canada was one of the first nations to adopt a national AI strategy in 2017, establishing itself as a leader in AI research. This year, Canadian AI startups showed significant promise:
- Tenstorrent raised $700 million USD.
- Cohere, a leader in large-language models, secured $500 million USD.
- Waabi, an autonomous driving startup, raised $275 million CAD.
- Ideogram, focused on text-to-image generation, closed an $80 million USD funding round.
Canada also boasts a deep generative AI talent pool, with 670 AI startups and 30 generative AI firms, ranking fourth globally in generative AI companies per capita.
Investors like Radical Ventures raised $800 million USD for an AI growth fund, while firms such as Intrepid Growth Partners and Defined Capital emerged to capitalize on the growing sector. Additionally, Canadian organizations have begun outspending global peers in AI investments, while the federal government has committed billions to enhance AI research, adoption, and computing capacity.nced regional connectivity, setting a new standard for sustainable aviation at competitive prices.”
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The Challenges: Outspent and Unfocused
Despite these strengths, two key challenges hinder Canada’s ability to compete globally:
- Limited Financial Resources:
- The global AI race is dominated by nations and corporations investing enormous sums. Goldman Sachs estimates that $1 trillion USD will be spent on AI over the next five years.In comparison, Canadian AI startups collectively raised $2.2 billion CAD in 2023—less than one-quarter of the $8 billion USD invested by Amazon into Anthropic, an LLM developer.
- Lack of a Clear Strategy:
- Critics argue Canada is spreading resources too thin by funding too many projects without clear priorities. While the first phase of Canada’s Pan-Canadian AI Strategy focused on research, and the second on commercialization, the government has yet to articulate a focused “Phase Three” strategy aligned with current global AI advancements.
- Federal initiatives, such as funding for Cohere’s data center, have been criticized for favoring US technology providers like Nvidia rather than fostering Canadian-built solutions.
Calls for Focused Leadership
Experts have emphasized that Canada must focus on niche areas where it can lead globally. According to Ben Bergen, President of the Canadian Council of Innovators:
“The government has to pick a few critical areas and work closely with companies in those spaces. Trying to do everything leads to no clear strategy.”
Former Scale AI COO Clément Bourgogne echoed these sentiments, suggesting Canada should identify specific roles in the AI ecosystem rather than attempting to dominate the field.
Canada’s Path Forward
As global competition accelerates, Canada’s ability to convert its research leadership and funding into measurable economic and societal impact remains uncertain. Industry leaders like Mappedin CEO Hongwei Liu stress the need for strategic, rather than reactive, investments.
While Canada has the talent, infrastructure, and ambition, 2024 highlighted the critical need for sharper focus, stronger financial backing, and a cohesive national AI strategy to compete effectively on the global stage. Whether Canada can translate its Nobel-winning AI legacy into tangible growth remains an open question as the race for AI dominance continues.
