CognitiveAristocracy
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Overview / Regions / Rio de Janeiro

Rio de Janeiro

Latin America Power #66/162Per-capita #135National view: Brazil →
Metro Power
49.0
of 100 · #66
MPI
49.0
MCC
30.8
MDI
28.4

Pillar profile

Talent29.8
Capital21.1
Research30.0
Infrastructure44.7
Agentic28.4

Indicators

  • Population (m)12.6
  • GDP ($bn)185
  • GDP per capita ($k)14.7
  • AI investment ($bn)0.9
  • Tech employment %4.5
  • AI talent48
  • Research strength54
  • Notable AI orgs14
  • Compute / data centers52
  • Broadband %78
  • Tertiary degree %32
  • Digital skills50
  • Startup ecosystem48
  • Agent adoption32
  • Patents / 100k7

Nearest peers

Metro report · generated from Rio de Janeiro's indicators

Rio de Janeiro — metro standing in full

Rio de Janeiro is the #67 metro by economic size ($185bn) in the panel and ranks #66/162 on absolute Metro Power and #135/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure. Locally it runs below the Brazil national average (MCC 30.8 vs CC 41.1).

National context: Brazil scores CC 41.1 per-capita; Rio de Janeiro sits at MCC 30.8.

Economic & scale context curated v1 estimate

GDP (metro)
$185bn
#67 of 162
GDP / capita
$15k
Population
12.6M
AI investment
$0.9bn
#137 of 162
Notable AI orgs
14

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Rio de Janeiro sits
MPI Metro Power49.0Moderate · #66/162Mid-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 Coefficient30.8Developing · #135/162Low 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 Agentic28.4Developing · #134/162Low 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 Talent29.8Developing · #132/162Low 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 Capital21.1Developing · #138/162Low 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 Research30.0Developing · #118/162Low 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 Infrastructure44.7Developing · #138/162Low 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 Agentic28.4Developing · #134/162Low 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 — Infrastructure 44.7 (#138/162, Developing): infrastructure gaps cap how much AI can actually be run locally.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.