Beijing
Metro Power
83.8
of 100 · #3
MPI
83.8
MCC
72.7
MDI
70.0
Pillar profile
Talent64.0
Capital67.0
Research81.0
Infrastructure81.7
Agentic70.0
Indicators
- Population (m)21.9
- GDP ($bn)760
- GDP per capita ($k)35
- AI investment ($bn)22
- Tech employment %10
- AI talent85
- Research strength88
- Notable AI orgs90
- Compute / data centers86
- Broadband %92
- Tertiary degree %50
- Digital skills76
- Startup ecosystem82
- Agent adoption64
- Patents / 100k260
Nearest peers
- Tel Aviv70.7
- Washington DC70.0
- Shenzhen69.7
- New York75.9
- London69.2
Metro report · generated from Beijing's indicators
Beijing, metro standing in full
Beijing is the #9 metro by economic size ($760bn) in the panel and ranks #3/162 on absolute Metro Power and #5/162 on per-capita intensity. Its strongest pillar is Research (81.0, Leading); no single pillar is a binding weakness. Locally it runs above the China national average (MCC 72.7 vs CC 69.9).
National context: China scores CC 69.9 per-capita; Beijing sits at MCC 72.7.
Economic & scale context curated v1 estimate
GDP (metro)
$760bn
#9 of 162
GDP / capita
$35k
Population
21.9M
AI investment
$22.0bn
#7 of 162
Notable AI orgs
90
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Beijing's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Beijing sits |
|---|---|---|---|
| MPI Metro Power | 83.8 | Leading · #3/162 | 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 | 72.7 | Leading · #5/162 | 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 | 70.0 | Leading · #6/162 | 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 | 64.0 | Leading · #10/162 | 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 | 67.0 | Leading · #7/162 | 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 | 81.0 | Leading · #2/162 | 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 | 81.7 | Leading · #11/162 | 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 | 70.0 | Leading · #6/162 | 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 (81.0, Leading), a strong research base feeding a pipeline of ideas and people.
- Agentic (70.0, Leading), agents are actively deployed, an early-mover productivity edge.
- Capital (67.0, Leading), abundant capital flowing into building cognitive infrastructure.
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.