CognitiveAristocracy
Detail
Overview / Regions / Stockholm

Stockholm

Europe Power #72/162Per-capita #32National view: Sweden →
Metro Power
46.9
of 100 · #72
MPI
46.9
MCC
55.7
MDI
50.3

Pillar profile

Talent51.6
Capital46.8
Research52.2
Infrastructure77.6
Agentic50.3

Indicators

  • Population (m)2.4
  • GDP ($bn)185.0
  • GDP per capita ($k)76.4
  • AI investment ($bn)5
  • Tech employment %9.5
  • AI talent62
  • Research strength76
  • Notable AI orgs30
  • Compute / data centers64
  • Broadband %97
  • Tertiary degree %52
  • Digital skills84
  • Startup ecosystem72
  • Agent adoption53
  • Patents / 100k62

Nearest peers

Metro report · generated from Stockholm's indicators

Stockholm — metro standing in full

Stockholm is the #65 metro by economic size ($185bn) in the panel and ranks #72/162 on absolute Metro Power and #32/162 on per-capita intensity. Its strongest pillar is Infrastructure (77.6, Strong); no single pillar is a binding weakness. Locally it runs below the Sweden national average (MCC 55.7 vs CC 67.2).

National context: Sweden scores CC 67.2 per-capita; Stockholm sits at MCC 55.7.

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

GDP (metro)
$185bn
#65 of 162
GDP / capita
$76k
Population
2.4M
AI investment
$5.0bn
#42 of 162
Notable AI orgs
30

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Stockholm sits
MPI Metro Power46.9Moderate · #72/162Mid-pack. High would mean a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem; low would mean 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 Coefficient55.7Strong · #32/162High 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 Agentic50.3Strong · #37/162High 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 Talent51.6Strong · #38/162High 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 Capital46.8Strong · #27/162High 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 Research52.2Strong · #34/162High 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 Infrastructure77.6Strong · #24/162High 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 Agentic50.3Strong · #37/162High 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

  • Infrastructure (77.6, Strong) — the physical and digital rails to run AI at scale are in place.
  • Capital (46.8, Strong) — abundant capital flowing into building cognitive infrastructure.
  • Research (52.2, Strong) — a strong research base feeding a pipeline of ideas and people.

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.