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RBC Thought Leadership AI, Technology and Innovation Canada’s AI potential: On sovereignty, safety and regulation
AI, Technology and Innovation
AI, Technology and Innovation

Canada's AI potential: On sovereignty, safety and regulation

Featuring Dave McKay, Aidan Gomez, and Evan Solomon in this episode of Disruptors

Listen on Apple Podcasts, Spotify or Simplecast

With questions swirling around AI sovereignty, safety and regulation, we bring you an important conversation this week.

Recorded at the Milken Institute Global Dialogues in Toronto, Cohere co-founder Aidan Gomez, RBC President and CEO Dave McKay, and Evan Solomon, Canada’s Minister of Artificial Intelligence and Digital Innovation, discuss who should write the rules for frontier AI, why access to the most advanced tools is uneven, and whether Canada can support a global champion.

FAQs

Aidan Gomez is co-founder and CEO of Cohere, a Toronto-headquartered enterprise AI company founded in 2019 with Nick Frosst and Ivan Zhang. He was one of eight authors of the 2017 paper “Attention Is All You Need,” which introduced the transformer architecture used in modern large language models. He holds a degree from the University of Toronto and a PhD from Oxford.

Cohere is a Canadian AI company building large language models and AI products for regulated industries including finance, healthcare, energy and the public sector, along with government. It is headquartered in Toronto with offices internationally.

Whether Canada can convert its role in inventing modern AI into lasting economic and strategic advantage, and who should be setting the rules for frontier AI systems.

The panel argues Canada has the research base, the talent and a frontier-model company, but has been slower to capitalize on deployment. The question raised is whether capital, access to advanced tooling and policy can align before the window closes.

McKay describes product development cycles compressing sharply, with work that previously took years now measured in months. He argues the effect on work is reallocation and retraining rather than straightforward elimination.

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