Boulder
Metro Power
24.3
of 100 · #145
MPI
24.3
MCC
63.7
MDI
58.3
Pillar profile
Talent71.6
Capital44.8
Research72.2
Infrastructure71.5
Agentic58.3
Indicators
- Population (m)0.3
- GDP ($bn)35
- GDP per capita ($k)106
- AI investment ($bn)4
- Tech employment %22
- AI talent68
- Research strength84
- Notable AI orgs16
- Compute / data centers50
- Broadband %95
- Tertiary degree %62
- Digital skills88
- Startup ecosystem72
- Agent adoption60
- Patents / 100k380
Nearest peers
- Toronto64.1
- Los Angeles64.7
- San Diego62.5
- Singapore65.0
- Seoul61.5
Metro report · generated from Boulder's indicators
Boulder — metro standing in full
Boulder is the #149 metro by economic size ($35bn) in the panel and ranks #145/162 on absolute Metro Power and #15/162 on per-capita intensity. Its strongest pillar is Talent (71.6, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 63.7 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Boulder sits at MCC 63.7.
Economic & scale context curated v1 estimate
GDP (metro)
$35bn
#149 of 162
GDP / capita
$106k
Population
0.3M
AI investment
$4.0bn
#50 of 162
Notable AI orgs
16
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Boulder's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Boulder sits |
|---|---|---|---|
| MPI Metro Power | 24.3 | Lagging · #145/162 | 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 | 63.7 | Leading · #15/162 | 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 | 58.3 | Strong · #20/162 | 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 | 71.6 | Leading · #4/162 | 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 | 44.8 | Strong · #33/162 | 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 | 72.2 | Leading · #6/162 | 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 | 71.5 | Moderate · #52/162 | 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 | 58.3 | Strong · #20/162 | 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
- Talent (71.6, Leading) — a deep talent pool — the scarcest input to building AI.
- Research (72.2, Leading) — a strong research base feeding a pipeline of ideas and people.
- Agentic (58.3, Strong) — agents are actively deployed — an early-mover productivity edge.
Risk factors
- Depth without scale — high per-capita intensity (MCC #15) but limited absolute weight (MPI #145): dense per resident, but small in total.
▲
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.