CognitiveAristocracy
Detail
Overview / Regions / Geneva

Geneva

Europe Power #149/162Per-capita #74National view: Switzerland →
Metro Power
23.3
of 100 · #149
MPI
23.3
MCC
46.5
MDI
41.6

Pillar profile

Talent45.8
Capital28.3
Research49.7
Infrastructure67.3
Agentic41.6

Indicators

  • Population (m)0.5
  • GDP ($bn)56.4
  • GDP per capita ($k)110.6
  • AI investment ($bn)2
  • Tech employment %7
  • AI talent56
  • Research strength78
  • Notable AI orgs18
  • Compute / data centers48
  • Broadband %96
  • Tertiary degree %52
  • Digital skills80
  • Startup ecosystem52
  • Agent adoption45
  • Patents / 100k70

Nearest peers

Metro report · generated from Geneva's indicators

Geneva — metro standing in full

Geneva is the #131 metro by economic size ($56bn) in the panel and ranks #149/162 on absolute Metro Power and #74/162 on per-capita intensity. Its strongest pillar is Research (49.7, Strong); the binding concern is capital. Locally it runs below the Switzerland national average (MCC 46.5 vs CC 68.2).

National context: Switzerland scores CC 68.2 per-capita; Geneva sits at MCC 46.5.

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

GDP (metro)
$56bn
#131 of 162
GDP / capita
$111k
Population
0.5M
AI investment
$2.0bn
#81 of 162
Notable AI orgs
18

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Geneva sits
MPI Metro Power23.3Lagging · #149/162Low 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 Coefficient46.5Moderate · #74/162Mid-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 · #87/162Mid-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 Talent45.8Moderate · #67/162Mid-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 Capital28.3Developing · #107/162Low 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 Research49.7Strong · #45/162High 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 Infrastructure67.3Moderate · #74/162Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean 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 · #87/162Mid-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 (49.7, Strong) — a strong research base feeding a pipeline of ideas and people.

Risk factors

  • Binding weakness — Capital 28.3 (#107/162, 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.