Oregon
West
State Power #21/51Per-capita #14
State Power
47.4
of 100 · #21
SPI
47.4
SCC
58.7
SDI
61.1
Pillar profile
Talent60.4
Capital43.4
Research55.6
Infrastructure73.2
Agentic61.1
Nearest peers (per-capita)
- North Carolina56.9
- Pennsylvania60.6
- Georgia55.6
- Connecticut55.2
- Minnesota55.2
Report · generated from Oregon's indicators
Oregon — standing in full
Oregon is the #25 state by economic size ($290bn GSP) and ranks #21/51 on absolute State Power and #14/51 on per-capita intensity. Its strongest pillar is Talent (60.4, Strong); no single pillar is a binding weakness.
Economic & scale context
GDP
$290bn
#25 of 51
GDP / capita
$68k
Population
4.2M
AI investment
$4.0bn
#22 of 51
Notable AI orgs
28
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means — and where Oregon sits |
|---|---|---|---|
| SPI State Power | 47.4 | Moderate · #21/51 | Mid-pack. High would mean a heavyweight that anchors national AI capacity and pulls in capital and talent; low would mean limited absolute weight — a smaller node leaning on capacity built in larger states. ▲ high: a heavyweight that anchors national AI capacity and pulls in capital and talent · ▼ low: limited absolute weight — a smaller node leaning on capacity built in larger states |
| SCC State Coefficient | 58.7 | Strong · #14/51 | High here — deep capability per resident — a concentrated, high-intensity AI economy. ▲ high: deep capability per resident — a concentrated, high-intensity AI economy · ▼ low: thin intensity per resident — capability is sparse relative to population |
| SDI State Agentic | 61.1 | Strong · #15/51 | 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 | 60.4 | Strong · #11/51 | 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 | 43.4 | Moderate · #18/51 | 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 | 55.6 | Moderate · #16/51 | Mid-pack. High would mean a strong research base feeding a pipeline of ideas and people; low would mean 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 | 73.2 | Strong · #12/51 | 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 | 61.1 | Strong · #15/51 | 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 (60.4, Strong) — a deep talent pool — the scarcest input to building AI.
- Infrastructure (73.2, Strong) — the physical and digital rails to run AI at scale are in place.
- Agentic (61.1, Strong) — agents are actively deployed — an early-mover productivity edge.
Risk factors
- No acute structural gaps stand out across the state pillars.
▲
State values are curated v1 estimates on a consistent scale — not yet measured sub-national data.