New research from Concordia University, led by Erkan Yönder in partnership with private equity firm Equiton, offers developers a data-driven lens into Canada’s housing supply challenges. Using neural network AI to analyze public data from CMHC, Statistics Canada, and federal forecasts, the study reveals that if current trends persist, median home prices could soar to $1.8 million in Toronto, $2.8 million in Vancouver, and $800,000 in Montreal by 2032. The research identifies regulatory inefficiencies and approval delays as key bottlenecks, showing that streamlining these processes could boost housing completions by up to 10 per cent.

“This research validates what housing advocates have long known—that minimizing policy barriers and lowering construction costs is crucial to addressing the housing crisis,” says Christopher Wein, Chief Operating Officer of Equiton Developments, Equiton’s in-house development division. “For the first time, we can actually see the impact of these obstacles quantified in real terms. That’s the kind of data stakeholders need to confidently start shifting policy in the right direction.”

The AI model also examined how input costs—such as tariffs, taxes, and labour—impact supply, finding that a 10 per cent increase in these costs could slash completions by as much as 35 per cent, disproportionately affecting apartment-style housing. Regional findings underscore the complexity of Canada’s housing landscape: while doubling completions in Toronto and Vancouver could modestly temper price growth, Montreal’s supply remains too far behind demand to meaningfully impact affordability. Calgary’s market, meanwhile, is more sensitive to demographic shifts than supply levels.

For developers, the takeaway moving forward is that regulatory reform and intergovernmental collaboration are essential to unlocking new opportunities. That said, Yönder cautions that even with streamlined approvals and stabilized costs, challenges like skilled labour shortages and rising expenses persist.