CognitiveAristocracy
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Overview / Regions / Grenoble

Grenoble

Europe Power #136/162Per-capita #82National view: France →
Metro Power
29.3
of 100 · #136
MPI
29.3
MCC
45.0
MDI
41.6

Pillar profile

Talent47.8
Capital22.7
Research51.5
Infrastructure61.4
Agentic41.6

Indicators

  • Population (m)1.3
  • GDP ($bn)48.4
  • GDP per capita ($k)37.5
  • AI investment ($bn)1
  • Tech employment %10
  • AI talent56
  • Research strength80
  • Notable AI orgs16
  • Compute / data centers42
  • Broadband %94
  • Tertiary degree %50
  • Digital skills76
  • Startup ecosystem50
  • Agent adoption45
  • Patents / 100k95

Nearest peers

Metro report · generated from Grenoble's indicators

Grenoble — metro standing in full

Grenoble is the #139 metro by economic size ($48bn) in the panel and ranks #136/162 on absolute Metro Power and #82/162 on per-capita intensity. Its strongest pillar is Research (51.5, Strong); the binding concern is capital. Locally it runs below the France national average (MCC 45.0 vs CC 65.1).

National context: France scores CC 65.1 per-capita; Grenoble sits at MCC 45.0.

Economic & scale context ● Eurostat met_10r_3gdp/met_pjanaggr3 (2021/22)

GDP (metro)
$48bn
#139 of 162
GDP / capita
$38k
Population
1.3M
AI investment
$1.0bn
#127 of 162
Notable AI orgs
16

Index & pillar read

For each metro index and pillar: what it means when high (the value) versus low (the gap), and Grenoble's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where Grenoble sits
MPI Metro Power29.3Developing · #136/162Low here — limited absolute weight — a smaller node that leans on capacity built in larger hubs.
▲ 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 Coefficient45.0Moderate · #82/162Mid-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 Agentic41.6Moderate · #88/162Mid-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 Talent47.8Moderate · #58/162Mid-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 Capital22.7Developing · #135/162Low here — 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 Research51.5Strong · #38/162High 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 Infrastructure61.4Developing · #106/162Low 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 Agentic41.6Moderate · #88/162Mid-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

  • Research (51.5, Strong) — a strong research base feeding a pipeline of ideas and people.

Risk factors

  • Binding weakness — Capital 22.7 (#135/162, Developing): thin investment — good ideas struggle to scale locally.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.