As the United States and China race to dominate artificial intelligence (AI), countries like Canada face a critical choice: remain a passive consumer of systems built elsewhere or forge a third path through strategic international collaboration.

Canada cannot afford to be a downstream user of opaque, black-box models developed abroad. Yet much of the current debate frames this as a binary between dependence and technological nationalism or even isolation. As Canadian institutions increasingly rely on AI systems developed and hosted by firms such as Microsoft, much of this infrastructure remains subject to U.S. legal frameworks like the CLOUD Act, leaving core data, model governance, and system oversight outside Canadian jurisdiction.

However, a credible alternative already exists. The Public AI network’s inference layer, built on top of Switzerland’s Apertus large language model, demonstrates what a middle power coalition could build. It offers a practical example of how AI infrastructure can be developed collectively rather than controlled by a handful of firms or states.

No single government can compete against the massive AI investments of US Big Tech and China. This challenge is not new as it is the logic that gave rise to Airbus and the European Organization for Nuclear Research (CERN). Instead of a purely domestic “made-in-Canada” model, Canada is well positioned to convene an international AI consortium like Airbus or CERN. By pooling resources across compute, software, and data with a group of strong democracies such as Japan, Germany, Taiwan, South Korea, the United Kingdom, and Australia, Canada can achieve the scale necessary to present a meaningful alternative to existing models.

We call this solution digital sovereignty through collaboration: pooling resources with like-minded governments, companies, academia, civil........

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