Manama
Middle East
Power #146/162Per-capita #132
Metro Power
23.9
of 100 · #146
MPI
23.9
MCC
31.6
MDI
28.4
Pillar profile
Talent28.1
Capital19.2
Research17.7
Infrastructure64.5
Agentic28.4
Indicators
- Population (m)1.6
- GDP ($bn)44
- GDP per capita ($k)28
- AI investment ($bn)0.6
- Tech employment %5
- AI talent40
- Research strength40
- Notable AI orgs8
- Compute / data centers58
- Broadband %99
- Tertiary degree %37
- Digital skills60
- Startup ecosystem48
- Agent adoption38
- Patents / 100k6
Nearest peers
- San Antonio31.6
- Bangkok31.5
- Ankara31.9
- Jakarta32.1
- Jeddah30.9
Metro report · generated from Manama's indicators
Manama — metro standing in full
Manama is the #143 metro by economic size ($44bn) in the panel and ranks #146/162 on absolute Metro Power and #132/162 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)
$44bn
#143 of 162
GDP / capita
$28k
Population
1.6M
AI investment
$0.6bn
#142 of 162
Notable AI orgs
8
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Manama's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Manama sits |
|---|---|---|---|
| MPI Metro Power | 23.9 | Lagging · #146/162 | 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 | 31.6 | Developing · #132/162 | 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 | 28.4 | Developing · #133/162 | 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 | 28.1 | Developing · #138/162 | 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 | 19.2 | Developing · #142/162 | 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 | 17.7 | Lagging · #151/162 | 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 | 64.5 | Moderate · #91/162 | 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 | 28.4 | Developing · #133/162 | 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 17.7 (#151/162, Lagging): 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.