CognitiveAristocracy
Detail
Overview / Regions / New York

New York

US Power #1/162Per-capita #4National view: United States →
Metro Power
87.1
of 100 · #1
MPI
87.1
MCC
75.9
MDI
79.5

Pillar profile

Talent67.2
Capital79.4
Research67.3
Infrastructure86.1
Agentic79.5

Indicators

  • Population (m)19.6
  • GDP ($bn)2,050
  • GDP per capita ($k)104.5
  • AI investment ($bn)52
  • Tech employment %16
  • AI talent82
  • Research strength90
  • Notable AI orgs55
  • Compute / data centers80
  • Broadband %95
  • Tertiary degree %48
  • Digital skills88
  • Startup ecosystem88
  • Agent adoption80
  • Patents / 100k95

Nearest peers

Metro report · generated from New York's indicators

New York — metro standing in full

New York is the #1 metro by economic size ($2,050bn) in the panel and ranks #1/162 on absolute Metro Power and #4/162 on per-capita intensity. Its strongest pillar is Capital (79.4, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 75.9 vs CC 86.7).

National context: United States scores CC 86.7 per-capita; New York sits at MCC 75.9.

Economic & scale context ● US Census ACS-1 2022 (population); GDP curated

GDP (metro)
$2,050bn
#1 of 162
GDP / capita
$104k
Population
19.6M
AI investment
$52.0bn
#2 of 162
Notable AI orgs
55

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where New York sits
MPI Metro Power87.1Leading · #1/162High 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 Coefficient75.9Leading · #4/162High 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 Agentic79.5Leading · #4/162High 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 Talent67.2Leading · #8/162High 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 Capital79.4Leading · #2/162High 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 Research67.3Leading · #10/162High 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 Infrastructure86.1Leading · #5/162High 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 Agentic79.5Leading · #4/162High 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

  • Capital (79.4, Leading) — abundant capital flowing into building cognitive infrastructure.
  • Agentic (79.5, Leading) — agents are actively deployed — an early-mover productivity edge.
  • Infrastructure (86.1, Leading) — the physical and digital rails to run AI at scale are in place.

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.