Tokyo
Metro Power
80.3
of 100 · #5
MPI
80.3
MCC
58.9
MDI
51.7
Pillar profile
Talent53.7
Capital44.5
Research65.5
Infrastructure78.9
Agentic51.7
Indicators
- Population (m)37
- GDP ($bn)2,000
- GDP per capita ($k)54
- AI investment ($bn)7
- Tech employment %8
- AI talent66
- Research strength80
- Notable AI orgs45
- Compute / data centers80
- Broadband %94
- Tertiary degree %55
- Digital skills74
- Startup ecosystem62
- Agent adoption52
- Patents / 100k180
Nearest peers
- Ann Arbor59.0
- Montreal59.3
- Pittsburgh58.3
- Denver58.2
- Atlanta58.2
Metro report · generated from Tokyo's indicators
Tokyo — metro standing in full
Tokyo is the #2 metro by economic size ($2,000bn) in the panel and ranks #5/162 on absolute Metro Power and #25/162 on per-capita intensity. Its strongest pillar is Research (65.5, Leading); no single pillar is a binding weakness. Locally it runs below the Japan national average (MCC 58.9 vs CC 64.4).
National context: Japan scores CC 64.4 per-capita; Tokyo sits at MCC 58.9.
Economic & scale context curated v1 estimate
GDP (metro)
$2,000bn
#2 of 162
GDP / capita
$54k
Population
37.0M
AI investment
$7.0bn
#27 of 162
Notable AI orgs
45
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Tokyo's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Tokyo sits |
|---|---|---|---|
| MPI Metro Power | 80.3 | Leading · #5/162 | 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 | 58.9 | Strong · #25/162 | 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 | 51.7 | Strong · #32/162 | 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 | 53.7 | Strong · #32/162 | 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 | 44.5 | Strong · #35/162 | High here — abundant capital flowing into building cognitive infrastructure. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment — good ideas struggle to scale locally |
| Research Research | 65.5 | Leading · #14/162 | 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 | 78.9 | Strong · #20/162 | 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 | 51.7 | Strong · #32/162 | 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 (65.5, Leading) — a strong research base feeding a pipeline of ideas and people.
- Infrastructure (78.9, Strong) — the physical and digital rails to run AI at scale are in place.
- Talent (53.7, Strong) — a deep talent pool — the scarcest input to building AI.
Risk factors
- No acute structural gaps stand out across the metro pillars.
▲
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.