San Antonio
Metro Power
32.9
of 100 · #126
MPI
32.9
MCC
31.6
MDI
27.1
Pillar profile
Talent27.2
Capital22.7
Research21.2
Infrastructure59.7
Agentic27.1
Indicators
- Population (m)2.6
- GDP ($bn)160
- GDP per capita ($k)61
- AI investment ($bn)1.2
- Tech employment %5
- AI talent40
- Research strength44
- Notable AI orgs9
- Compute / data centers62
- Broadband %89
- Tertiary degree %35
- Digital skills58
- Startup ecosystem48
- Agent adoption36
- Patents / 100k12
Nearest peers
Metro report · generated from San Antonio's indicators
San Antonio — metro standing in full
San Antonio is the #87 metro by economic size ($160bn) in the panel and ranks #126/162 on absolute Metro Power and #131/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is research. Locally it runs below the United States national average (MCC 31.6 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; San Antonio sits at MCC 31.6.
Economic & scale context curated v1 estimate
GDP (metro)
$160bn
#87 of 162
GDP / capita
$61k
Population
2.6M
AI investment
$1.2bn
#120 of 162
Notable AI orgs
9
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and San Antonio's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where San Antonio sits |
|---|---|---|---|
| MPI Metro Power | 32.9 | Developing · #126/162 | 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 · #131/162 | 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 | 27.1 | Developing · #138/162 | 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 | 27.2 | Developing · #140/162 | 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 | 22.7 | Developing · #136/162 | 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 | 21.2 | Lagging · #146/162 | 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 | 59.7 | Developing · #113/162 | 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 | 27.1 | Developing · #138/162 | 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 21.2 (#146/162, 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.