Taipei
Metro Power
57.4
of 100 · #37
MPI
57.4
MCC
56.1
MDI
47.9
Pillar profile
Talent54.1
Capital36.0
Research65.4
Infrastructure77.0
Agentic47.9
Indicators
- Population (m)7
- GDP ($bn)340
- GDP per capita ($k)49
- AI investment ($bn)3.5
- Tech employment %11
- AI talent64
- Research strength72
- Notable AI orgs30
- Compute / data centers74
- Broadband %94
- Tertiary degree %52
- Digital skills76
- Startup ecosystem58
- Agent adoption48
- Patents / 100k300
Nearest peers
Metro report · generated from Taipei's indicators
Taipei — metro standing in full
Taipei is the #32 metro by economic size ($340bn) in the panel and ranks #37/162 on absolute Metro Power and #31/162 on per-capita intensity. Its strongest pillar is Research (65.4, Leading); no single pillar is a binding weakness. Locally it runs below the Taiwan national average (MCC 56.1 vs CC 65.6).
National context: Taiwan scores CC 65.6 per-capita; Taipei sits at MCC 56.1.
Economic & scale context curated v1 estimate
GDP (metro)
$340bn
#32 of 162
GDP / capita
$49k
Population
7.0M
AI investment
$3.5bn
#59 of 162
Notable AI orgs
30
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Taipei's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Taipei sits |
|---|---|---|---|
| MPI Metro Power | 57.4 | Strong · #37/162 | High here — a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem. ▲ 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 | 56.1 | Strong · #31/162 | High here — deep capability per resident — a concentrated, high-intensity ecosystem. ▲ 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 | 47.9 | Strong · #48/162 | High here — agents are widely deployed locally — a near-term productivity multiplier. ▲ 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 | 54.1 | Strong · #31/162 | High here — a deep talent pool — the scarcest input to building AI. ▲ 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 | 36.0 | Moderate · #67/162 | Mid-pack. High would mean abundant capital flowing into building cognitive infrastructure; low would mean 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 | 65.4 | Leading · #15/162 | High here — a strong research base feeding a pipeline of ideas and people. ▲ 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 | 77.0 | Strong · #26/162 | High here — the physical and digital rails to run AI at scale are in place. ▲ 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 | 47.9 | Strong · #48/162 | High here — agents are actively deployed — an early-mover productivity edge. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- Research (65.4, Leading) — a strong research base feeding a pipeline of ideas and people.
- Infrastructure (77.0, Strong) — the physical and digital rails to run AI at scale are in place.
- Talent (54.1, Strong) — a deep talent pool — the scarcest input to building AI.
Risk factors
- No acute structural gaps stand out across the metro pillars.
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Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.