Riyadh
Metro Power
55.5
of 100 · #45
MPI
55.5
MCC
39.3
MDI
36.6
Pillar profile
Talent30.5
Capital39.1
Research28.1
Infrastructure62.4
Agentic36.6
Indicators
- Population (m)7.7
- GDP ($bn)230
- GDP per capita ($k)30
- AI investment ($bn)7
- Tech employment %6
- AI talent45
- Research strength42
- Notable AI orgs25
- Compute / data centers62
- Broadband %92
- Tertiary degree %34
- Digital skills60
- Startup ecosystem52
- Agent adoption46
- Patents / 100k10
Nearest peers
- St. Louis39.3
- Lisbon40.0
- Sao Paulo40.4
- Pune38.1
- Birmingham UK40.7
Metro report · generated from Riyadh's indicators
Riyadh, metro standing in full
Riyadh is the #56 metro by economic size ($230bn) in the panel and ranks #45/162 on absolute Metro Power and #109/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is talent. Locally it runs below the Saudi Arabia national average (MCC 39.3 vs CC 48.0).
National context: Saudi Arabia scores CC 48.0 per-capita; Riyadh sits at MCC 39.3.
Economic & scale context curated v1 estimate
GDP (metro)
$230bn
#56 of 162
GDP / capita
$30k
Population
7.7M
AI investment
$7.0bn
#29 of 162
Notable AI orgs
25
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Riyadh's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Riyadh sits |
|---|---|---|---|
| MPI Metro Power | 55.5 | Strong · #45/162 | High here, a heavyweight hub where capital, talent and AI organizations concentrate, it can anchor an entire national AI ecosystem. ▲ 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 | 39.3 | Developing · #109/162 | 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 | 36.6 | Developing · #106/162 | 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 | 30.5 | Developing · #130/162 | 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 | 39.1 | Moderate · #53/162 | Mid-pack. High would mean abundant capital flowing into building cognitive infrastructure; low would mean 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 | 28.1 | Developing · #124/162 | 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 | 62.4 | Moderate · #101/162 | 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 | 36.6 | Developing · #106/162 | 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, Talent 30.5 (#130/162, Developing): a shallow talent base that constrains how much can be built locally.
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Metro values are curated estimates (v1) on a consistent global scale, not yet measured sub-national data.