Rio de Janeiro
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
- Jeddah30.9
- Kolkata30.5
- Amman30.5
- Bangkok31.5
- San Antonio31.6
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 / pillar | Value | Standing | What a high vs low value means — and where Rio de Janeiro sits |
|---|---|---|---|
| MPI Metro Power | 49.0 | Moderate · #66/162 | Mid-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 Coefficient | 30.8 | Developing · #135/162 | Low 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 Agentic | 28.4 | Developing · #134/162 | Low 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 Talent | 29.8 | Developing · #132/162 | Low 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 Capital | 21.1 | Developing · #138/162 | Low 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 Research | 30.0 | Developing · #118/162 | Low 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 Infrastructure | 44.7 | Developing · #138/162 | Low 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 Agentic | 28.4 | Developing · #134/162 | Low 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.
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Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.