CognitiveAristocracy
Detail
Overview / Regions / Dublin

Dublin

Europe Power #70/162Per-capita #37National view: Ireland →
Metro Power
47.8
of 100 · #70
MPI
47.8
MCC
54.2
MDI
47.2

Pillar profile

Talent52.7
Capital42.4
Research47.8
Infrastructure80.8
Agentic47.2

Indicators

  • Population (m)2.2
  • GDP ($bn)248.8
  • GDP per capita ($k)113.6
  • AI investment ($bn)5
  • Tech employment %10
  • AI talent60
  • Research strength70
  • Notable AI orgs34
  • Compute / data centers80
  • Broadband %94
  • Tertiary degree %56
  • Digital skills78
  • Startup ecosystem64
  • Agent adoption50
  • Patents / 100k30

Nearest peers

Metro report · generated from Dublin's indicators

Dublin — metro standing in full

Dublin is the #50 metro by economic size ($249bn) in the panel and ranks #70/162 on absolute Metro Power and #37/162 on per-capita intensity. Its strongest pillar is Infrastructure (80.8, Leading); no single pillar is a binding weakness. Locally it runs below the Ireland national average (MCC 54.2 vs CC 62.2).

National context: Ireland scores CC 62.2 per-capita; Dublin sits at MCC 54.2.

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

GDP (metro)
$249bn
#50 of 162
GDP / capita
$114k
Population
2.2M
AI investment
$5.0bn
#44 of 162
Notable AI orgs
34

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Dublin sits
MPI Metro Power47.8Moderate · #70/162Mid-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 Coefficient54.2Strong · #37/162High 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 Agentic47.2Moderate · #53/162Mid-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 Talent52.7Strong · #35/162High 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 Capital42.4Strong · #42/162High 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 Research47.8Moderate · #54/162Mid-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 Infrastructure80.8Leading · #12/162High 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 Agentic47.2Moderate · #53/162Mid-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

  • Infrastructure (80.8, Leading) — the physical and digital rails to run AI at scale are in place.
  • Talent (52.7, Strong) — a deep talent pool — the scarcest input to building AI.
  • Capital (42.4, Strong) — abundant capital flowing into building cognitive infrastructure.

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.