Doha
Middle East
Power #109/162Per-capita #121
Metro Power
37.6
of 100 · #109
MPI
37.6
MCC
35.5
MDI
33.7
Pillar profile
Talent29.7
Capital27.1
Research25.2
Infrastructure61.8
Agentic33.7
Indicators
- Population (m)2.4
- GDP ($bn)135
- GDP per capita ($k)56
- AI investment ($bn)3
- Tech employment %6
- AI talent42
- Research strength44
- Notable AI orgs15
- Compute / data centers54
- Broadband %96
- Tertiary degree %36
- Digital skills62
- Startup ecosystem44
- Agent adoption44
- Patents / 100k12
Nearest peers
- Santiago35.5
- Cincinnati35.4
- Buenos Aires35.7
- Monterrey35.7
- Guadalajara35.2
Metro report · generated from Doha's indicators
Doha — metro standing in full
Doha is the #94 metro by economic size ($135bn) in the panel and ranks #109/162 on absolute Metro Power and #121/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is research.
Economic & scale context curated v1 estimate
GDP (metro)
$135bn
#94 of 162
GDP / capita
$56k
Population
2.4M
AI investment
$3.0bn
#72 of 162
Notable AI orgs
15
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Doha's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Doha sits |
|---|---|---|---|
| MPI Metro Power | 37.6 | Developing · #109/162 | Low 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 Coefficient | 35.5 | Developing · #121/162 | 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 | 33.7 | Developing · #117/162 | 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 | 29.7 | Developing · #133/162 | 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 | 27.1 | Developing · #118/162 | 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 | 25.2 | Developing · #135/162 | 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 | 61.8 | Moderate · #105/162 | Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean 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 | 33.7 | Developing · #117/162 | 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 — Research 25.2 (#135/162, 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.