CognitiveAristocracy
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Overview / Regions / Vancouver

Vancouver

US Power #77/162Per-capita #48National view: Canada →
Metro Power
45.1
of 100 · #77
MPI
45.1
MCC
52.5
MDI
50.7

Pillar profile

Talent56.8
Capital36.9
Research46.7
Infrastructure71.5
Agentic50.7

Indicators

  • Population (m)2.7
  • GDP ($bn)160
  • GDP per capita ($k)59
  • AI investment ($bn)3
  • Tech employment %10
  • AI talent64
  • Research strength68
  • Notable AI orgs25
  • Compute / data centers62
  • Broadband %93
  • Tertiary degree %60
  • Digital skills78
  • Startup ecosystem62
  • Agent adoption52
  • Patents / 100k70

Nearest peers

Metro report · generated from Vancouver's indicators

Vancouver — metro standing in full

Vancouver is the #85 metro by economic size ($160bn) in the panel and ranks #77/162 on absolute Metro Power and #48/162 on per-capita intensity. Its strongest pillar is Talent (56.8, Strong); no single pillar is a binding weakness. Locally it runs below the Canada national average (MCC 52.5 vs CC 65.3).

National context: Canada scores CC 65.3 per-capita; Vancouver sits at MCC 52.5.

Economic & scale context curated v1 estimate

GDP (metro)
$160bn
#85 of 162
GDP / capita
$59k
Population
2.7M
AI investment
$3.0bn
#70 of 162
Notable AI orgs
25

Index & pillar read

For each metro index and pillar: what it means when high (the value) versus low (the gap), and Vancouver's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where Vancouver sits
MPI Metro Power45.1Moderate · #77/162Mid-pack. High would mean a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem; low would mean 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 Coefficient52.5Strong · #48/162High 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 Agentic50.7Strong · #35/162High 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 Talent56.8Strong · #22/162High 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 Capital36.9Moderate · #64/162Mid-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 Research46.7Moderate · #60/162Mid-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 Infrastructure71.5Moderate · #53/162Mid-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 Agentic50.7Strong · #35/162High 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 (56.8, Strong) — a deep talent pool — the scarcest input to building AI.
  • Agentic (50.7, Strong) — agents are actively deployed — an early-mover productivity edge.

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.