Research series
Canada's Data Centre Race
An 11-part research series on the physical foundations of the AI buildout in Canada: data centres, power, fibre, water, sovereignty, jobs, capital, and the alternatives. Grounded in primary sources, with every figure cited.
The competitive frontier of artificial intelligence has moved from models and chips to physical infrastructure: power, land, fibre, water, and capital. Canada has the raw ingredient the rest of the world wants, an abundant and largely clean electricity supply, but converting that into a strategic advantage runs into constraints the marketing rarely mentions.
This series works through those constraints one at a time, grounded in a primary-source research dataset rather than press releases. A few threads run through all eleven chapters: power interconnection, not land or money, is the real bottleneck; where the clean grid is capped, developers are quietly falling back on natural gas; foreign hyperscalers still control most of the capacity; and the same megawatts could often do more for the economy somewhere else.
Every figure is cited. Where the data is partial, estimated, or disputed, we say so rather than paper over it.
Updated August 23, 2026.The series has been revised against CBRE’s H2 2025 data-centre research, which reports Toronto and Montreal on the same basis as the U.S. markets for the first time. Toronto (315.0 MW) and Montreal (229.5 MW) now carry tracked colocation inventory rather than estimates, Northern Virginia is stated as dated figures rather than a range, the tracked project set is 20 rather than 18, and the metro figures are explicitly distinguished from the federal 337 MW AI-specific estimate. Revised chapters carry a dated update note at the end.
Chapters
- 1
The infrastructure race
The competitive frontier of AI has shifted from models and chips to power, land, fibre, and capital. Where that leaves Canada.
- 2
Canada vs. the U.S.
Clean grids, cool climate, and water on one side; speed, scale, and cloud regions on the other. A head-to-head scorecard.
- 3
The map of the boom
Where the projects are, what stage they are really at, and the gap between announced gigawatts and operating megawatts.
- 4
Data centres and power
The scarce input isn't land, capital, or chips. It's a grid connection: Alberta's 21 GW queue, a 1,200 MW door, and the gas workaround.
- 5
Fibre and bandwidth
Real interconnection lives in Toronto and Montreal; everywhere else is thin. What that means for where AI compute can sit.
- 6
Data centres and water
No Canadian project publishes measured water use, and three-quarters of planned Alberta sites sit in high water-stress basins.
- 7
Data centres and sovereignty
Funded compute, missing cloud. Why a Canadian-located data centre does not make the data it holds Canadian-controlled.
- 8
Jobs and economics
Data centres deliver construction booms and tax base but few permanent jobs. The honest metric is jobs per megawatt.
- 9
The capital
Canadian pension and infrastructure money (CPPIB, CDPQ, Brookfield) is deep in AI infrastructure, much of it abroad.
- 10
Alternative uses
The same 100 MW could go to housing, batteries, steel, or ports, often with far more jobs per megawatt. The opportunity cost.
- 11
The strategy
The ingredients without the coordination. What a real Canadian AI infrastructure strategy would need to look like.
How this series is built
The underlying research is a structured dataset of Canadian data-centre projects, provincial power systems, fibre and interconnection, water use, capital and financing, sovereignty policy, and public controversies, each row carrying source URLs and a confidence flag. Primary sources are prioritized: IESO, AESO, Hydro-Québec, BC Hydro, the Canada Energy Regulator, ISED, Alberta Major Projects, the federal Impact Assessment Agency, and named investigative reporting.
New chapters publish daily over the run of the series. All chapters are live. Related reading: Canada’s AI Compute Landscape.