Ottawa
Metro Power
33.9
of 100 · #122
MPI
33.9
MCC
46.8
MDI
43.4
Pillar profile
Talent50.2
Capital31.0
Research39.6
Infrastructure69.6
Agentic43.4
Indicators
- Population (m)1.5
- GDP ($bn)95
- GDP per capita ($k)63
- AI investment ($bn)1.6
- Tech employment %9
- AI talent58
- Research strength66
- Notable AI orgs16
- Compute / data centers64
- Broadband %93
- Tertiary degree %55
- Digital skills72
- Startup ecosystem60
- Agent adoption46
- Patents / 100k34
Nearest peers
Metro report · generated from Ottawa's indicators
Ottawa — metro standing in full
Ottawa is the #116 metro by economic size ($95bn) in the panel and ranks #122/162 on absolute Metro Power and #71/162 on per-capita intensity. Its strongest pillar is Talent (50.2, Strong); no single pillar is a binding weakness. Locally it runs below the Canada national average (MCC 46.8 vs CC 65.3).
National context: Canada scores CC 65.3 per-capita; Ottawa sits at MCC 46.8.
Economic & scale context curated v1 estimate
GDP (metro)
$95bn
#116 of 162
GDP / capita
$63k
Population
1.5M
AI investment
$1.6bn
#103 of 162
Notable AI orgs
16
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Ottawa's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Ottawa sits |
|---|---|---|---|
| MPI Metro Power | 33.9 | Developing · #122/162 | Low here — limited absolute weight — a smaller node that leans on capacity built in larger hubs. ▲ 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 | 46.8 | Moderate · #71/162 | Mid-pack. High would mean deep capability per resident — a concentrated, high-intensity ecosystem; low would mean thin intensity per resident — capability is sparse relative to the population. ▲ 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 | 43.4 | Moderate · #76/162 | Mid-pack. High would mean agents are widely deployed locally — a near-term productivity multiplier; low would mean agentic deployment is shallow — the local agent lever is under-used. ▲ 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 | 50.2 | Strong · #42/162 | 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 | 31.0 | Moderate · #92/162 | Mid-pack. High would mean abundant capital flowing into building cognitive infrastructure; low would mean thin investment — good ideas struggle to scale locally. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment — good ideas struggle to scale locally |
| Research Research | 39.6 | Moderate · #88/162 | Mid-pack. High would mean a strong research base feeding a pipeline of ideas and people; low would mean a weak research base — fewer home-grown breakthroughs and spinouts. ▲ 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 | 69.6 | Moderate · #62/162 | Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean infrastructure gaps cap how much AI can actually be run locally. ▲ 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 | 43.4 | Moderate · #76/162 | Mid-pack. High would mean agents are actively deployed — an early-mover productivity edge; low would mean little agentic deployment — the near-term lever is unused. ▲ 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 (50.2, Strong) — a deep talent pool — the scarcest input to building AI.
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.