Bangkok
Metro Power
49.5
of 100 · #63
MPI
49.5
MCC
31.5
MDI
27.8
Pillar profile
Talent29.0
Capital25.2
Research26.9
Infrastructure48.6
Agentic27.8
Indicators
- Population (m)10.7
- GDP ($bn)260
- GDP per capita ($k)24
- AI investment ($bn)1.5
- Tech employment %6
- AI talent44
- Research strength50
- Notable AI orgs12
- Compute / data centers56
- Broadband %78
- Tertiary degree %32
- Digital skills54
- Startup ecosystem50
- Agent adoption34
- Patents / 100k12
Nearest peers
- San Antonio31.6
- Manama31.6
- Ankara31.9
- Jakarta32.1
- Jeddah30.9
Metro report · generated from Bangkok's indicators
Bangkok, metro standing in full
Bangkok is the #45 metro by economic size ($260bn) in the panel and ranks #63/162 on absolute Metro Power and #133/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is agentic. Locally it runs below the Thailand national average (MCC 31.5 vs CC 37.9).
National context: Thailand scores CC 37.9 per-capita; Bangkok sits at MCC 31.5.
Economic & scale context curated v1 estimate
GDP (metro)
$260bn
#45 of 162
GDP / capita
$24k
Population
10.7M
AI investment
$1.5bn
#106 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 Bangkok's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Bangkok sits |
|---|---|---|---|
| MPI Metro Power | 49.5 | Moderate · #63/162 | Mid-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 Coefficient | 31.5 | Developing · #133/162 | Low 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 Agentic | 27.8 | Developing · #137/162 | Low 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 Talent | 29.0 | Developing · #137/162 | Low 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 Capital | 25.2 | Developing · #128/162 | Low 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 Research | 26.9 | Developing · #129/162 | Low 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 Infrastructure | 48.6 | Developing · #132/162 | Low 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 Agentic | 27.8 | Developing · #137/162 | Low 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, Agentic 27.8 (#137/162, Developing): little agentic deployment, the near-term lever is unused.
▲
Metro values are curated estimates (v1) on a consistent global scale, not yet measured sub-national data.