CognitiveAristocracy
Detail
Overview / Regions / Medellin

Medellin

Latin America Power #120/162Per-capita #142National view: Colombia →
Metro Power
34.0
of 100 · #120
MPI
34.0
MCC
29.0
MDI
27.9

Pillar profile

Talent30.2
Capital21.0
Research23.5
Infrastructure42.4
Agentic27.9

Indicators

  • Population (m)4.1
  • GDP ($bn)56
  • GDP per capita ($k)13.7
  • AI investment ($bn)0.4
  • Tech employment %5
  • AI talent47
  • Research strength46
  • Notable AI orgs11
  • Compute / data centers50
  • Broadband %74
  • Tertiary degree %33
  • Digital skills52
  • Startup ecosystem54
  • Agent adoption32
  • Patents / 100k5

Nearest peers

Metro report · generated from Medellin's indicators

Medellin — metro standing in full

Medellin is the #132 metro by economic size ($56bn) in the panel and ranks #120/162 on absolute Metro Power and #142/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure. Locally it runs below the Colombia national average (MCC 29.0 vs CC 31.5).

National context: Colombia scores CC 31.5 per-capita; Medellin sits at MCC 29.0.

Economic & scale context curated v1 estimate

GDP (metro)
$56bn
#132 of 162
GDP / capita
$14k
Population
4.1M
AI investment
$0.4bn
#145 of 162
Notable AI orgs
11

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Medellin sits
MPI Metro Power34.0Developing · #120/162Low 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 Coefficient29.0Developing · #142/162Low here — 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 Agentic27.9Developing · #136/162Low here — 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 Talent30.2Developing · #131/162Low here — 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 Capital21.0Developing · #139/162Low 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 Research23.5Developing · #140/162Low here — 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 Infrastructure42.4Developing · #142/162Low 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 Agentic27.9Developing · #136/162Low here — 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

  • Binding weakness — Infrastructure 42.4 (#142/162, Developing): infrastructure gaps cap how much AI can actually be run locally.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.