Montreal
Metro Power
55.7
of 100 · #43
MPI
55.7
MCC
59.3
MDI
58.3
Pillar profile
Talent62.6
Capital42.4
Research59.8
Infrastructure73.4
Agentic58.3
Indicators
- Population (m)4.3
- GDP ($bn)230
- GDP per capita ($k)53
- AI investment ($bn)5
- Tech employment %10
- AI talent76
- Research strength82
- Notable AI orgs45
- Compute / data centers66
- Broadband %93
- Tertiary degree %58
- Digital skills78
- Startup ecosystem64
- Agent adoption54
- Patents / 100k75
Nearest peers
- Ann Arbor59.0
- Tokyo58.9
- Paris59.8
- Raleigh-Durham60.0
- Cambridge UK60.0
Metro report · generated from Montreal's indicators
Montreal — metro standing in full
Montreal is the #55 metro by economic size ($230bn) in the panel and ranks #43/162 on absolute Metro Power and #23/162 on per-capita intensity. Its strongest pillar is Talent (62.6, Leading); no single pillar is a binding weakness. Locally it runs below the Canada national average (MCC 59.3 vs CC 65.3).
National context: Canada scores CC 65.3 per-capita; Montreal sits at MCC 59.3.
Economic & scale context curated v1 estimate
GDP (metro)
$230bn
#55 of 162
GDP / capita
$53k
Population
4.3M
AI investment
$5.0bn
#45 of 162
Notable AI orgs
45
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Montreal's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Montreal sits |
|---|---|---|---|
| MPI Metro Power | 55.7 | Strong · #43/162 | High here — a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem. ▲ high: a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem · ▼ low: limited absolute weight — a smaller node that leans on capacity built in larger hubs |
| MCC Metro Coefficient | 59.3 | Strong · #23/162 | High here — deep capability per resident — a concentrated, high-intensity ecosystem. ▲ high: deep capability per resident — a concentrated, high-intensity ecosystem · ▼ low: thin intensity per resident — capability is sparse relative to the population |
| MDI Metro Agentic | 58.3 | Strong · #21/162 | High here — agents are widely deployed locally — a near-term productivity multiplier. ▲ high: agents are widely deployed locally — a near-term productivity multiplier · ▼ low: agentic deployment is shallow — the local agent lever is under-used |
| Talent Talent | 62.6 | Leading · #13/162 | High here — a deep talent pool — the scarcest input to building AI. ▲ high: a deep talent pool — the scarcest input to building AI · ▼ low: a shallow talent base that constrains how much can be built locally |
| Capital Capital | 42.4 | Strong · #43/162 | High here — abundant capital flowing into building cognitive infrastructure. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment — good ideas struggle to scale locally |
| Research Research | 59.8 | Strong · #24/162 | High here — a strong research base feeding a pipeline of ideas and people. ▲ high: a strong research base feeding a pipeline of ideas and people · ▼ low: a weak research base — fewer home-grown breakthroughs and spinouts |
| Infrastructure Infrastructure | 73.4 | Strong · #44/162 | High here — the physical and digital rails to run AI at scale are in place. ▲ high: the physical and digital rails to run AI at scale are in place · ▼ low: infrastructure gaps cap how much AI can actually be run locally |
| Agentic Agentic | 58.3 | Strong · #21/162 | High here — agents are actively deployed — an early-mover productivity edge. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- Talent (62.6, Leading) — a deep talent pool — the scarcest input to building AI.
- Agentic (58.3, Strong) — agents are actively deployed — an early-mover productivity edge.
- Research (59.8, Strong) — a strong research base feeding a pipeline of ideas and people.
Risk factors
- No acute structural gaps stand out across the metro pillars.
▲
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.