CognitiveAristocracy
Detail
Overview / Regions / Ho Chi Minh City

Ho Chi Minh City

Asia-Pacific Power #75/162Per-capita #139National view: Vietnam →
Metro Power
45.9
of 100 · #75
MPI
45.9
MCC
29.4
MDI
26.4

Pillar profile

Talent27.2
Capital26.0
Research23.1
Infrastructure44.5
Agentic26.4

Indicators

  • Population (m)9.3
  • GDP ($bn)120
  • GDP per capita ($k)13
  • AI investment ($bn)1.2
  • Tech employment %6
  • AI talent44
  • Research strength44
  • Notable AI orgs12
  • Compute / data centers52
  • Broadband %76
  • Tertiary degree %28
  • Digital skills52
  • Startup ecosystem54
  • Agent adoption32
  • Patents / 100k6

Nearest peers

Metro report · generated from Ho Chi Minh City's indicators

Ho Chi Minh City — metro standing in full

Ho Chi Minh City is the #99 metro by economic size ($120bn) in the panel and ranks #75/162 on absolute Metro Power and #139/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is research. Locally it runs below the Vietnam national average (MCC 29.4 vs CC 35.6).

National context: Vietnam scores CC 35.6 per-capita; Ho Chi Minh City sits at MCC 29.4.

Economic & scale context curated v1 estimate

GDP (metro)
$120bn
#99 of 162
GDP / capita
$13k
Population
9.3M
AI investment
$1.2bn
#119 of 162
Notable AI orgs
12

Index & pillar read

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

Index / pillarValueStandingWhat a high vs low value means — and where Ho Chi Minh City sits
MPI Metro Power45.9Moderate · #75/162Mid-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 · #139/162Low 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 · #140/162Low 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 Talent27.2Developing · #139/162Low 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 · #122/162Low 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 Research23.1Developing · #142/162Low 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 Infrastructure44.5Developing · #139/162Low 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 · #140/162Low 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 — Research 23.1 (#142/162, Developing): a weak research base — fewer home-grown breakthroughs and spinouts.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.