Wuhan
Metro Power
59.6
of 100 · #32
MPI
59.6
MCC
44.7
MDI
42.0
Pillar profile
Talent40.5
Capital35.2
Research44.5
Infrastructure61.3
Agentic42.0
Indicators
- Population (m)13.7
- GDP ($bn)280
- GDP per capita ($k)20
- AI investment ($bn)3.2
- Tech employment %7
- AI talent58
- Research strength66
- Notable AI orgs24
- Compute / data centers66
- Broadband %85
- Tertiary degree %38
- Digital skills62
- Startup ecosystem58
- Agent adoption44
- Patents / 100k58
Nearest peers
Metro report · generated from Wuhan's indicators
Wuhan — metro standing in full
Wuhan is the #43 metro by economic size ($280bn) in the panel and ranks #32/162 on absolute Metro Power and #84/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure. Locally it runs below the China national average (MCC 44.7 vs CC 69.9).
National context: China scores CC 69.9 per-capita; Wuhan sits at MCC 44.7.
Economic & scale context curated v1 estimate
GDP (metro)
$280bn
#43 of 162
GDP / capita
$20k
Population
13.7M
AI investment
$3.2bn
#64 of 162
Notable AI orgs
24
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Wuhan's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Wuhan sits |
|---|---|---|---|
| MPI Metro Power | 59.6 | Strong · #32/162 | 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 | 44.7 | Moderate · #84/162 | 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 · #85/162 | 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 | 40.5 | Moderate · #96/162 | 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 | 35.2 | Moderate · #70/162 | 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 | 44.5 | Moderate · #62/162 | 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 | 61.3 | Developing · #108/162 | 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 | 42.0 | Moderate · #85/162 | 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
- Scale without depth — a heavyweight by absolute Metro Power (#32) but thinner per-capita intensity (MCC #84): big in total, less dense per resident.
- Binding weakness — Infrastructure 61.3 (#108/162, 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.