Paris
Metro Power
72.2
of 100 · #10
MPI
72.2
MCC
59.8
MDI
53.5
Pillar profile
Talent53.4
Capital57.9
Research59.3
Infrastructure75.0
Agentic53.5
Indicators
- Population (m)12.3
- GDP ($bn)818.2
- GDP per capita ($k)66.4
- AI investment ($bn)14
- Tech employment %7.5
- AI talent72
- Research strength82
- Notable AI orgs55
- Compute / data centers72
- Broadband %94
- Tertiary degree %48
- Digital skills74
- Startup ecosystem74
- Agent adoption50
- Patents / 100k42
Nearest peers
- Raleigh-Durham60.0
- Cambridge UK60.0
- Chicago60.3
- Montreal59.3
- Ann Arbor59.0
Metro report · generated from Paris's indicators
Paris — metro standing in full
Paris is the #6 metro by economic size ($818bn) in the panel and ranks #10/162 on absolute Metro Power and #22/162 on per-capita intensity. Its strongest pillar is Capital (57.9, Leading); no single pillar is a binding weakness. Locally it runs below the France national average (MCC 59.8 vs CC 65.1).
National context: France scores CC 65.1 per-capita; Paris sits at MCC 59.8.
Economic & scale context ● Eurostat met_10r_3gdp/met_pjanaggr3 (2021/22)
GDP (metro)
$818bn
#6 of 162
GDP / capita
$66k
Population
12.3M
AI investment
$14.0bn
#12 of 162
Notable AI orgs
55
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Paris's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Paris sits |
|---|---|---|---|
| MPI Metro Power | 72.2 | Leading · #10/162 | 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 | 59.8 | Strong · #22/162 | 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 | 53.5 | Strong · #29/162 | 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 | 53.4 | Strong · #33/162 | 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 | 57.9 | Leading · #13/162 | 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 | 59.3 | Strong · #25/162 | 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 | 75.0 | Strong · #35/162 | 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 | 53.5 | Strong · #29/162 | 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
- Capital (57.9, Leading) — abundant capital flowing into building cognitive infrastructure.
- Research (59.3, Strong) — a strong research base feeding a pipeline of ideas and people.
- Agentic (53.5, Strong) — agents are actively deployed — an early-mover productivity edge.
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.