Nagoya
Metro Power
55.8
of 100 · #42
MPI
55.8
MCC
46.6
MDI
42.0
Pillar profile
Talent46.0
Capital31.4
Research44.3
Infrastructure69.3
Agentic42.0
Indicators
- Population (m)9.4
- GDP ($bn)420
- GDP per capita ($k)45
- AI investment ($bn)3
- Tech employment %7
- AI talent58
- Research strength66
- Notable AI orgs20
- Compute / data centers64
- Broadband %94
- Tertiary degree %50
- Digital skills70
- Startup ecosystem52
- Agent adoption44
- Patents / 100k78
Nearest peers
Metro report · generated from Nagoya's indicators
Nagoya — metro standing in full
Nagoya is the #25 metro by economic size ($420bn) in the panel and ranks #42/162 on absolute Metro Power and #73/162 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness. Locally it runs below the Japan national average (MCC 46.6 vs CC 64.4).
National context: Japan scores CC 64.4 per-capita; Nagoya sits at MCC 46.6.
Economic & scale context curated v1 estimate
GDP (metro)
$420bn
#25 of 162
GDP / capita
$45k
Population
9.4M
AI investment
$3.0bn
#76 of 162
Notable AI orgs
20
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Nagoya's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Nagoya sits |
|---|---|---|---|
| MPI Metro Power | 55.8 | Strong · #42/162 | 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 | 46.6 | Moderate · #73/162 | Mid-pack. High would mean deep capability per resident — a concentrated, high-intensity ecosystem; low would mean 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 | 42.0 | Moderate · #84/162 | Mid-pack. High would mean agents are widely deployed locally — a near-term productivity multiplier; low would mean 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 | 46.0 | Moderate · #66/162 | Mid-pack. High would mean a deep talent pool — the scarcest input to building AI; low would mean 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 | 31.4 | Moderate · #91/162 | 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 | 44.3 | Moderate · #67/162 | Mid-pack. High would mean a strong research base feeding a pipeline of ideas and people; low would mean 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 | 69.3 | Moderate · #63/162 | Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean 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 | 42.0 | Moderate · #84/162 | Mid-pack. High would mean agents are actively deployed — an early-mover productivity edge; low would mean 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
- 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.