Portland OR
Metro Power
44.8
of 100 · #80
MPI
44.8
MCC
54.1
MDI
50.0
Pillar profile
Talent50.3
Capital39.2
Research54.6
Infrastructure76.4
Agentic50.0
Indicators
- Population (m)2.5
- GDP ($bn)210
- GDP per capita ($k)83.7
- AI investment ($bn)5
- Tech employment %14
- AI talent60
- Research strength72
- Notable AI orgs14
- Compute / data centers68
- Broadband %94
- Tertiary degree %42
- Digital skills81
- Startup ecosystem58
- Agent adoption54
- Patents / 100k230
Nearest peers
- Munich54.0
- Dublin54.2
- Sydney53.9
- Berlin54.4
- Salt Lake City53.5
Metro report · generated from Portland OR's indicators
Portland OR, metro standing in full
Portland OR is the #59 metro by economic size ($210bn) in the panel and ranks #80/162 on absolute Metro Power and #38/162 on per-capita intensity. Its strongest pillar is Infrastructure (76.4, Strong); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 54.1 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Portland OR sits at MCC 54.1.
Economic & scale context ● US Census ACS-1 2022 (population); GDP curated
GDP (metro)
$210bn
#59 of 162
GDP / capita
$84k
Population
2.5M
AI investment
$5.0bn
#40 of 162
Notable AI orgs
14
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Portland OR's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Portland OR sits |
|---|---|---|---|
| MPI Metro Power | 44.8 | Moderate · #80/162 | Mid-pack. High would mean a heavyweight hub where capital, talent and AI organizations concentrate, it can anchor an entire national AI ecosystem; low would mean 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 | 54.1 | Strong · #38/162 | 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 | 50.0 | Strong · #40/162 | 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 | 50.3 | Strong · #40/162 | 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 | 39.2 | Moderate · #52/162 | 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 | 54.6 | Strong · #31/162 | 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 | 76.4 | Strong · #30/162 | 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 | 50.0 | Strong · #40/162 | 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
- Infrastructure (76.4, Strong), the physical and digital rails to run AI at scale are in place.
- Research (54.6, Strong), a strong research base feeding a pipeline of ideas and people.
- Talent (50.3, Strong), a deep talent pool, the scarcest input to building AI.
Risk factors
- No acute structural gaps stand out across the metro pillars.
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Metro values are curated estimates (v1) on a consistent global scale, not yet measured sub-national data.