Canada is entering one of the highest-stakes economic negotiations in its history. Sitting across the table from the world's largest economy, the instinct will be to protect market share, preserve access and maintain stability. Those instincts are right, but it is only half the equation. The other half is diversification, and that cannot be negotiated; it has to be built.
Building Leverage Through Capability
The best way to create leverage in any negotiation is to invest in your capabilities. Prime Minister Mark Carney has done that and continues to do so by building new trade alliances, creating new agencies, such as the Defence Investment Agency and the Major Projects Office, and launching new initiatives, including the sovereign wealth fund.
Canada can, and should, maintain deep integration with the United States in traditional industries, such as automobiles, energy, lumber and agriculture, while building the industries that will define the future. That last part requires intention.
Historical Patterns of Missed Opportunity
Canada has done this before. In our history, we have had moments of real conviction when we invested in talent, engineering and national capability. But we also have had moments when we step back too early, withdraw support or fail to scale what we have started. The result is a recurring pattern in which we create the frontier and watch others industrialize it.
The story of Avro Canada is a case in point. The cancellation of the CF-105 Avro Arrow program not only ended an aircraft, but also dismantled a world-class aerospace ecosystem. Engineers moved south and became foundational contributors to the National Aeronautics and Space Administration's Apollo program, helping build the early U.S. space program.
Bob Gilruth, the first director of NASA's Manned Spacecraft Center, said Canadian engineers were a "godsend" to the Apollo mission. He was right: 12 of NASA's engineers were Canadian at the time, leaving Avro to work on Project Mercury. Canada invested in that, and then exited.
The AI Parallel
The same pattern has emerged in artificial intelligence half a century later. Researchers such as Geoffrey Hinton at the University of Toronto helped define modern deep learning, but Canada once again led the science while the companies, computing and commercial scale accrued elsewhere.
What makes this episode in Canada's history more striking is the context. During the AI winters of the 1970s and 1990s, when AI research contracted and neural networks were dismissed as fringe, institutions like the Canadian Institute for Advanced Research continued its funding even as others had moved on.
Hinton moved from Carnegie Mellon to the University of Toronto to pursue research on neural networks. Richard Sutton left AT&T Labs for the University of Alberta to develop reinforcement learning. In hindsight, the two dominant paradigms of modern AI emerged from that bet, reinforcing a familiar pattern. Canada sees the future early, but too often fails to capture it at scale.
