CognitiveAristocracy
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Overview / Regions / Cape Town

Cape Town

Africa Power #89/162Per-capita #140National view: South Africa →
Metro Power
41.7
of 100 · #89
MPI
41.7
MCC
29.4
MDI
26.4

Pillar profile

Talent25.4
Capital26.0
Research30.1
Infrastructure39.3
Agentic26.4

Indicators

  • Population (m)4.8
  • GDP ($bn)90
  • GDP per capita ($k)19
  • AI investment ($bn)1
  • Tech employment %6
  • AI talent44
  • Research strength48
  • Notable AI orgs22
  • Compute / data centers46
  • Broadband %72
  • Tertiary degree %24
  • Digital skills52
  • Startup ecosystem56
  • Agent adoption32
  • Patents / 100k4

Nearest peers

Metro report · generated from Cape Town's indicators

Cape Town — metro standing in full

Cape Town is the #121 metro by economic size ($90bn) in the panel and ranks #89/162 on absolute Metro Power and #140/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure. Locally it runs below the South Africa national average (MCC 29.4 vs CC 31.6).

National context: South Africa scores CC 31.6 per-capita; Cape Town sits at MCC 29.4.

Economic & scale context curated v1 estimate

GDP (metro)
$90bn
#121 of 162
GDP / capita
$19k
Population
4.8M
AI investment
$1.0bn
#131 of 162
Notable AI orgs
22

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Cape Town sits
MPI Metro Power41.7Moderate · #89/162Mid-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 Coefficient29.4Developing · #140/162Low 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 Agentic26.4Developing · #141/162Low 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 Talent25.4Lagging · #144/162Low 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 Capital26.0Developing · #124/162Low 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 Research30.1Developing · #117/162Low 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 Infrastructure39.3Lagging · #147/162Low 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 Agentic26.4Developing · #141/162Low 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 39.3 (#147/162, Lagging): 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.