CognitiveAristocracy
Detail
Overview / Regions / San Diego

San Diego

US Power #48/162Per-capita #16National view: United States →
Metro Power
54.1
of 100 · #48
MPI
54.1
MCC
62.5
MDI
62.1

Pillar profile

Talent55.9
Capital53.3
Research66.3
Infrastructure75.0
Agentic62.1

Indicators

  • Population (m)3.3
  • GDP ($bn)280
  • GDP per capita ($k)85.4
  • AI investment ($bn)11
  • Tech employment %14
  • AI talent70
  • Research strength85
  • Notable AI orgs24
  • Compute / data centers62
  • Broadband %95
  • Tertiary degree %42
  • Digital skills83
  • Startup ecosystem70
  • Agent adoption64
  • Patents / 100k230

Nearest peers

Metro report · generated from San Diego's indicators

San Diego — metro standing in full

San Diego is the #40 metro by economic size ($280bn) in the panel and ranks #48/162 on absolute Metro Power and #16/162 on per-capita intensity. Its strongest pillar is Research (66.3, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 62.5 vs CC 86.7).

National context: United States scores CC 86.7 per-capita; San Diego sits at MCC 62.5.

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

GDP (metro)
$280bn
#40 of 162
GDP / capita
$85k
Population
3.3M
AI investment
$11.0bn
#15 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 San Diego's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where San Diego sits
MPI Metro Power54.1Strong · #48/162High 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 Coefficient62.5Leading · #16/162High 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 Agentic62.1Leading · #13/162High 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 Talent55.9Strong · #26/162High 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 Capital53.3Strong · #18/162High 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 Research66.3Leading · #11/162High 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 Infrastructure75.0Strong · #34/162High 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 Agentic62.1Leading · #13/162High 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

  • Research (66.3, Leading) — a strong research base feeding a pipeline of ideas and people.
  • Agentic (62.1, Leading) — agents are actively deployed — an early-mover productivity edge.
  • Capital (53.3, Strong) — abundant capital flowing into building cognitive infrastructure.

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.