Brasilia
Metro Power
36.0
of 100 · #114
MPI
36.0
MCC
29.8
MDI
28.1
Pillar profile
Talent30.6
Capital15.3
Research25.8
Infrastructure49.0
Agentic28.1
Indicators
- Population (m)4.8
- GDP ($bn)95
- GDP per capita ($k)19.8
- AI investment ($bn)0.3
- Tech employment %4.6
- AI talent46
- Research strength50
- Notable AI orgs11
- Compute / data centers53
- Broadband %82
- Tertiary degree %36
- Digital skills53
- Startup ecosystem45
- Agent adoption33
- Patents / 100k6
Nearest peers
- Ho Chi Minh City29.4
- Cape Town29.4
- Johannesburg29.3
- Kolkata30.5
- Amman30.5
Metro report · generated from Brasilia's indicators
Brasilia — metro standing in full
Brasilia is the #119 metro by economic size ($95bn) in the panel and ranks #114/162 on absolute Metro Power and #138/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is capital. Locally it runs below the Brazil national average (MCC 29.8 vs CC 41.1).
National context: Brazil scores CC 41.1 per-capita; Brasilia sits at MCC 29.8.
Economic & scale context curated v1 estimate
GDP (metro)
$95bn
#119 of 162
GDP / capita
$20k
Population
4.8M
AI investment
$0.3bn
#151 of 162
Notable AI orgs
11
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Brasilia's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Brasilia sits |
|---|---|---|---|
| MPI Metro Power | 36.0 | Developing · #114/162 | Low here — 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 | 29.8 | Developing · #138/162 | 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 | 28.1 | Developing · #135/162 | 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 | 30.6 | Developing · #129/162 | 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 | 15.3 | Lagging · #148/162 | 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 | 25.8 | Developing · #133/162 | 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 | 49.0 | Developing · #131/162 | 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 | 28.1 | Developing · #135/162 | 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 — Capital 15.3 (#148/162, Lagging): thin investment — good ideas struggle to scale locally.
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Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.