CognitiveAristocracy
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Overview / Regions / Warsaw

Warsaw

Europe Power #93/162Per-capita #103National view: Poland →
Metro Power
40.9
of 100 · #93
MPI
40.9
MCC
41.3
MDI
37.5

Pillar profile

Talent40.4
Capital29.4
Research37.0
Infrastructure62.3
Agentic37.5

Indicators

  • Population (m)3.3
  • GDP ($bn)107.7
  • GDP per capita ($k)33.0
  • AI investment ($bn)2
  • Tech employment %7.5
  • AI talent52
  • Research strength62
  • Notable AI orgs18
  • Compute / data centers52
  • Broadband %92
  • Tertiary degree %44
  • Digital skills70
  • Startup ecosystem54
  • Agent adoption42
  • Patents / 100k14

Nearest peers

Metro report · generated from Warsaw's indicators

Warsaw — metro standing in full

Warsaw is the #109 metro by economic size ($108bn) in the panel and ranks #93/162 on absolute Metro Power and #103/162 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness. Locally it runs below the Poland national average (MCC 41.3 vs CC 50.0).

National context: Poland scores CC 50.0 per-capita; Warsaw sits at MCC 41.3.

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

GDP (metro)
$108bn
#109 of 162
GDP / capita
$33k
Population
3.3M
AI investment
$2.0bn
#85 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 Warsaw's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where Warsaw sits
MPI Metro Power40.9Moderate · #93/162Mid-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 Coefficient41.3Moderate · #103/162Mid-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 Agentic37.5Moderate · #104/162Mid-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 Talent40.4Moderate · #97/162Mid-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 Capital29.4Moderate · #98/162Mid-pack. High would mean abundant capital flowing into building cognitive infrastructure; low would mean 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 Research37.0Moderate · #93/162Mid-pack. High would mean a strong research base feeding a pipeline of ideas and people; low would mean a weak research base — fewer home-grown breakthroughs and spinouts.
▲ high: a strong research base feeding a pipeline of ideas and people  ·  ▼ low: a weak research base — fewer home-grown breakthroughs and spinouts
Infrastructure Infrastructure62.3Moderate · #102/162Mid-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 Agentic37.5Moderate · #104/162Mid-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

  • No pillar stands out as a clear strength yet.

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.