CognitiveAristocracy
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Overview / Regions / Chicago

Chicago

US Power #21/162Per-capita #19National view: United States →
Metro Power
66.2
of 100 · #21
MPI
66.2
MCC
60.3
MDI
58.7

Pillar profile

Talent51.7
Capital53.9
Research57.0
Infrastructure80.3
Agentic58.7

Indicators

  • Population (m)9.4
  • GDP ($bn)770
  • GDP per capita ($k)81.6
  • AI investment ($bn)13
  • Tech employment %12
  • AI talent66
  • Research strength84
  • Notable AI orgs24
  • Compute / data centers76
  • Broadband %94
  • Tertiary degree %42
  • Digital skills81
  • Startup ecosystem68
  • Agent adoption62
  • Patents / 100k95

Nearest peers

Metro report · generated from Chicago's indicators

Chicago — metro standing in full

Chicago is the #7 metro by economic size ($770bn) in the panel and ranks #21/162 on absolute Metro Power and #19/162 on per-capita intensity. Its strongest pillar is Infrastructure (80.3, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 60.3 vs CC 86.7).

National context: United States scores CC 86.7 per-capita; Chicago sits at MCC 60.3.

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

GDP (metro)
$770bn
#7 of 162
GDP / capita
$82k
Population
9.4M
AI investment
$13.0bn
#14 of 162
Notable AI orgs
24

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Chicago sits
MPI Metro Power66.2Strong · #21/162High 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 Coefficient60.3Strong · #19/162High 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 Agentic58.7Strong · #18/162High 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 Talent51.7Strong · #36/162High 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 Capital53.9Leading · #16/162High 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 Research57.0Strong · #28/162High 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 Infrastructure80.3Leading · #14/162High 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 Agentic58.7Strong · #18/162High 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

  • Infrastructure (80.3, Leading) — the physical and digital rails to run AI at scale are in place.
  • Capital (53.9, Leading) — abundant capital flowing into building cognitive infrastructure.
  • Agentic (58.7, 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.