Lima
Latin America
Power #101/162Per-capita #154
Metro Power
39.0
of 100 · #101
MPI
39.0
MCC
19.5
MDI
18.0
Pillar profile
Talent20.0
Capital12.6
Research15.4
Infrastructure31.3
Agentic18.0
Indicators
- Population (m)10.9
- GDP ($bn)110
- GDP per capita ($k)10.1
- AI investment ($bn)0.3
- Tech employment %3.2
- AI talent36
- Research strength38
- Notable AI orgs7
- Compute / data centers44
- Broadband %68
- Tertiary degree %28
- Digital skills42
- Startup ecosystem40
- Agent adoption26
- Patents / 100k3
Nearest peers
Metro report · generated from Lima's indicators
Lima, metro standing in full
Lima is the #108 metro by economic size ($110bn) in the panel and ranks #101/162 on absolute Metro Power and #154/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is capital.
Economic & scale context curated v1 estimate
GDP (metro)
$110bn
#108 of 162
GDP / capita
$10k
Population
10.9M
AI investment
$0.3bn
#147 of 162
Notable AI orgs
7
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Lima's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Lima sits |
|---|---|---|---|
| MPI Metro Power | 39.0 | Moderate · #101/162 | 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 | 19.5 | Lagging · #154/162 | 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 | 18.0 | Lagging · #153/162 | 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 | 20.0 | Lagging · #153/162 | 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 | 12.6 | Lagging · #154/162 | 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 | 15.4 | Lagging · #152/162 | 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 | 31.3 | Lagging · #151/162 | 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 | 18.0 | Lagging · #153/162 | 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 12.6 (#154/162, 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.