Manila
Metro Power
53.9
of 100 · #49
MPI
53.9
MCC
34.3
MDI
35.0
Pillar profile
Talent34.7
Capital27.0
Research27.8
Infrastructure47.1
Agentic35.0
Indicators
- Population (m)14.4
- GDP ($bn)260
- GDP per capita ($k)18
- AI investment ($bn)1.2
- Tech employment %6.5
- AI talent50
- Research strength48
- Notable AI orgs16
- Compute / data centers58
- Broadband %72
- Tertiary degree %36
- Digital skills56
- Startup ecosystem56
- Agent adoption40
- Patents / 100k8
Nearest peers
- Mexico City34.0
- Istanbul34.6
- Montevideo33.6
- Guadalajara35.2
- Cincinnati35.4
Metro report · generated from Manila's indicators
Manila — metro standing in full
Manila is the #46 metro by economic size ($260bn) in the panel and ranks #49/162 on absolute Metro Power and #126/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure. Locally it runs above the Philippines national average (MCC 34.3 vs CC 26.8).
National context: Philippines scores CC 26.8 per-capita; Manila sits at MCC 34.3.
Economic & scale context curated v1 estimate
GDP (metro)
$260bn
#46 of 162
GDP / capita
$18k
Population
14.4M
AI investment
$1.2bn
#122 of 162
Notable AI orgs
16
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Manila's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Manila sits |
|---|---|---|---|
| MPI Metro Power | 53.9 | Moderate · #49/162 | 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 | 34.3 | Developing · #126/162 | 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 | 35.0 | Developing · #113/162 | 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 | 34.7 | Developing · #114/162 | 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 | 27.0 | Developing · #119/162 | 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 | 27.8 | Developing · #126/162 | 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 | 47.1 | Developing · #134/162 | 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 | 35.0 | Developing · #113/162 | 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 47.1 (#134/162, 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.