CognitiveAristocracy
Detail
Overview / Regions / Atlanta

Atlanta

US Power #30/162Per-capita #28National view: United States →
Metro Power
59.6
of 100 · #30
MPI
59.6
MCC
58.2
MDI
56.2

Pillar profile

Talent51.6
Capital50.2
Research53.0
Infrastructure80.2
Agentic56.2

Indicators

  • Population (m)6.2
  • GDP ($bn)470
  • GDP per capita ($k)75.6
  • AI investment ($bn)10
  • Tech employment %13
  • AI talent64
  • Research strength80
  • Notable AI orgs20
  • Compute / data centers78
  • Broadband %93
  • Tertiary degree %42
  • Digital skills80
  • Startup ecosystem66
  • Agent adoption60
  • Patents / 100k90

Nearest peers

Metro report · generated from Atlanta's indicators

Atlanta — metro standing in full

Atlanta is the #22 metro by economic size ($470bn) in the panel and ranks #30/162 on absolute Metro Power and #28/162 on per-capita intensity. Its strongest pillar is Infrastructure (80.2, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 58.2 vs CC 86.7).

National context: United States scores CC 86.7 per-capita; Atlanta sits at MCC 58.2.

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

GDP (metro)
$470bn
#22 of 162
GDP / capita
$76k
Population
6.2M
AI investment
$10.0bn
#16 of 162
Notable AI orgs
20

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Atlanta sits
MPI Metro Power59.6Strong · #30/162High 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 Coefficient58.2Strong · #28/162High 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 Agentic56.2Strong · #24/162High 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 Talent51.6Strong · #37/162High 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 Capital50.2Strong · #22/162High 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 Research53.0Strong · #32/162High 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 Infrastructure80.2Leading · #16/162High 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 Agentic56.2Strong · #24/162High 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 (80.2, Leading) — the physical and digital rails to run AI at scale are in place.
  • Capital (50.2, Strong) — abundant capital flowing into building cognitive infrastructure.
  • Agentic (56.2, 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.