CognitiveAristocracy
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Overview / Regions / Guadalajara

Guadalajara

Latin America Power #86/162Per-capita #124National view: Mexico →
Metro Power
42.8
of 100 · #86
MPI
42.8
MCC
35.2
MDI
33.7

Pillar profile

Talent37.2
Capital23.5
Research31.0
Infrastructure50.7
Agentic33.7

Indicators

  • Population (m)5.4
  • GDP ($bn)115
  • GDP per capita ($k)21.3
  • AI investment ($bn)0.6
  • Tech employment %6.8
  • AI talent54
  • Research strength52
  • Notable AI orgs18
  • Compute / data centers57
  • Broadband %80
  • Tertiary degree %36
  • Digital skills55
  • Startup ecosystem56
  • Agent adoption35
  • Patents / 100k8

Nearest peers

Metro report · generated from Guadalajara's indicators

Guadalajara — metro standing in full

Guadalajara is the #103 metro by economic size ($115bn) in the panel and ranks #86/162 on absolute Metro Power and #124/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is capital. Locally it runs above the Mexico national average (MCC 35.2 vs CC 35.1).

National context: Mexico scores CC 35.1 per-capita; Guadalajara sits at MCC 35.2.

Economic & scale context curated v1 estimate

GDP (metro)
$115bn
#103 of 162
GDP / capita
$21k
Population
5.4M
AI investment
$0.6bn
#143 of 162
Notable AI orgs
18

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Guadalajara sits
MPI Metro Power42.8Moderate · #86/162Mid-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 Coefficient35.2Developing · #124/162Low here — thin intensity per resident — capability is sparse relative to the population.
▲ high: deep capability per resident — a concentrated, high-intensity ecosystem  ·  ▼ low: thin intensity per resident — capability is sparse relative to the population
MDI Metro Agentic33.7Developing · #119/162Low here — agentic deployment is shallow — the local agent lever is under-used.
▲ high: agents are widely deployed locally — a near-term productivity multiplier  ·  ▼ low: agentic deployment is shallow — the local agent lever is under-used
Talent Talent37.2Developing · #107/162Low here — a shallow talent base that constrains how much can be built locally.
▲ 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 Capital23.5Developing · #134/162Low here — 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 Research31.0Developing · #116/162Low here — 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 Infrastructure50.7Developing · #126/162Low here — 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 Agentic33.7Developing · #119/162Low here — little agentic deployment — the near-term lever is unused.
▲ high: agents are actively deployed — an early-mover productivity edge  ·  ▼ low: little agentic deployment — the near-term lever is unused

Strengths to build on

  • No pillar stands out as a clear strength yet.

Risk factors

  • Binding weakness — Capital 23.5 (#134/162, Developing): thin investment — good ideas struggle to scale locally.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.