Austin
Metro Power
54.3
of 100 · #47
MPI
54.3
MCC
67.2
MDI
68.7
Pillar profile
Talent63.6
Capital60.8
Research61.1
Infrastructure81.7
Agentic68.7
Indicators
- Population (m)2.4
- GDP ($bn)230
- GDP per capita ($k)95.0
- AI investment ($bn)15
- Tech employment %18
- AI talent72
- Research strength78
- Notable AI orgs28
- Compute / data centers74
- Broadband %94
- Tertiary degree %48
- Digital skills86
- Startup ecosystem78
- Agent adoption72
- Patents / 100k190
Nearest peers
- Shanghai66.2
- London69.2
- Singapore65.0
- Los Angeles64.7
- Shenzhen69.7
Metro report · generated from Austin's indicators
Austin — metro standing in full
Austin is the #54 metro by economic size ($230bn) in the panel and ranks #47/162 on absolute Metro Power and #10/162 on per-capita intensity. Its strongest pillar is Agentic (68.7, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 67.2 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Austin sits at MCC 67.2.
Economic & scale context ● US Census ACS-1 2022 (population); GDP curated
GDP (metro)
$230bn
#54 of 162
GDP / capita
$95k
Population
2.4M
AI investment
$15.0bn
#10 of 162
Notable AI orgs
28
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Austin's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Austin sits |
|---|---|---|---|
| MPI Metro Power | 54.3 | Strong · #47/162 | 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 | 67.2 | Leading · #10/162 | High here — deep capability per resident — a concentrated, high-intensity ecosystem. ▲ 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 | 68.7 | Leading · #7/162 | High here — agents are widely deployed locally — a near-term productivity multiplier. ▲ 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 | 63.6 | Leading · #11/162 | High here — a deep talent pool — the scarcest input to building AI. ▲ 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 | 60.8 | Leading · #10/162 | High here — abundant capital flowing into building cognitive infrastructure. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment — good ideas struggle to scale locally |
| Research Research | 61.1 | Strong · #21/162 | High here — a strong research base feeding a pipeline of ideas and people. ▲ 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 | 81.7 | Leading · #10/162 | High here — the physical and digital rails to run AI at scale are in place. ▲ 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 | 68.7 | Leading · #7/162 | High here — agents are actively deployed — an early-mover productivity edge. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- Agentic (68.7, Leading) — agents are actively deployed — an early-mover productivity edge.
- Capital (60.8, Leading) — abundant capital flowing into building cognitive infrastructure.
- Infrastructure (81.7, Leading) — the physical and digital rails to run AI at scale are in place.
Risk factors
- No acute structural gaps stand out across the metro pillars.
▲
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.