AI & Machine Learning

• Machine learning models and platforms
• Computer vision systems
• Natural language processing services
• AI-powered analytics
• Autonomous systems software

1. 1

   Invest in sovereign compute infrastructure (Canadian-based GPU clusters)

2. 2

   Strengthen IP retention frameworks to prevent AI talent and company acquisition drain

3. 3

   Develop responsible AI governance frameworks as a competitive differentiator

4. 4

   Build AI applications for critical sectors (mining, agriculture, healthcare) with domain expertise

5. 5

   Pursue bilateral AI cooperation agreements for research data sharing

AI services and software are protected by CUSMA's digital trade provisions prohibiting customs duties on electronic transmissions. However, emerging US AI regulatory frameworks and export controls on advanced AI capabilities could create non-tariff barriers for Canadian AI firms. CUSMA's IP provisions may affect AI training data usage and model ownership across borders.

Canadian AI firms depend on US-controlled cloud GPU infrastructure for model training and deployment. NVIDIA and AMD GPU export restrictions, while primarily targeting China, demonstrate how compute supply can be weaponized as a policy tool. Talent mobility between Canadian research labs and US tech companies creates knowledge transfer and retention challenges.

Canada's AI ecosystem benefits from foundational research leadership (Bengio, Hinton legacy in Montreal and Toronto). MILA, Vector Institute, and Amii provide world-class research infrastructure. Competition from US Big Tech for AI talent and acquisition of Canadian AI startups creates a persistent brain drain dynamic.