Osaka
Metro Power
67.1
of 100 · #20
MPI
67.1
MCC
50.7
MDI
45.5
Pillar profile
Talent49.6
Capital38.2
Research47.1
Infrastructure73.1
Agentic45.5
Indicators
- Population (m)19
- GDP ($bn)680
- GDP per capita ($k)36
- AI investment ($bn)4.5
- Tech employment %7.5
- AI talent62
- Research strength68
- Notable AI orgs28
- Compute / data centers70
- Broadband %94
- Tertiary degree %52
- Digital skills72
- Startup ecosystem58
- Agent adoption46
- Patents / 100k62
Nearest peers
Metro report · generated from Osaka's indicators
Osaka — metro standing in full
Osaka is the #11 metro by economic size ($680bn) in the panel and ranks #20/162 on absolute Metro Power and #53/162 on per-capita intensity. Its strongest pillar is Infrastructure (73.1, Strong); no single pillar is a binding weakness. Locally it runs below the Japan national average (MCC 50.7 vs CC 64.4).
National context: Japan scores CC 64.4 per-capita; Osaka sits at MCC 50.7.
Economic & scale context curated v1 estimate
GDP (metro)
$680bn
#11 of 162
GDP / capita
$36k
Population
19.0M
AI investment
$4.5bn
#48 of 162
Notable AI orgs
28
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Osaka's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Osaka sits |
|---|---|---|---|
| MPI Metro Power | 67.1 | Strong · #20/162 | 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 | 50.7 | Moderate · #53/162 | 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 | 45.5 | Moderate · #64/162 | 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 | 49.6 | Strong · #47/162 | 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 | 38.2 | Moderate · #56/162 | 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 | 47.1 | Moderate · #58/162 | 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 | 73.1 | Strong · #45/162 | 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 | 45.5 | Moderate · #64/162 | 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
- Infrastructure (73.1, Strong) — the physical and digital rails to run AI at scale are in place.
- Talent (49.6, 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.