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AI sovereignty / AI architecture

Canada’s AI sovereignty: what do we need to own?

Canada faces the same AI question as every company: what do you rent, and what do you own? Sovereignty starts with deciding which layers matter most.

Canada is about to wrestle with the same AI question every company is wrestling with: what do you rent, and what do you own?

Today, Prime Minister Mark Carney announced a new National Council on Artificial Intelligence, with a mandate that includes accelerating AI adoption, building Canadian AI companies, and strengthening sovereign AI infrastructure.

That sounds a lot like the conversation companies are already having about AI agents.

At the company level, I’ve argued that you probably don’t need to own the model. Models will change constantly. What matters more is owning what compounds over time: memory, context, workflows, institutional knowledge, permissions, and the rules governing what AI is allowed to do.

At the national level, the questions are similar: Where does Canadian data live? Who controls the compute? Can Canadian institutions switch models without rebuilding everything underneath them? Do we retain the IP, talent and capabilities created here?

AI sovereignty cannot mean building everything ourselves. It should mean being deliberate about which layers are too important to become dependent on someone else for.

Which brings me back to the same principle. Rent the model. Own the memory. Govern what has authority. For companies, and Canada, that’s an architecture question.

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About the author

Omri Tintpulver is Chief Operating and AI Officer at Zoomer / Curiocity Media Group and founder of Factor2, his independent AI advisory and speaking practice.

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