North Carolina
South
State Power #12/51Per-capita #15
State Power
61.9
of 100 · #12
SPI
61.9
SCC
56.9
SDI
61.6
Pillar profile
Talent52.1
Capital49.1
Research57.7
Infrastructure63.9
Agentic61.6
Nearest peers (per-capita)
- Georgia55.6
- Connecticut55.2
- Minnesota55.2
- Oregon58.7
- Pennsylvania60.6
Report · generated from North Carolina's indicators
North Carolina — standing in full
North Carolina is the #11 state by economic size ($730bn GSP) and ranks #12/51 on absolute State Power and #15/51 on per-capita intensity. Its strongest pillar is Research (57.7, Strong); no single pillar is a binding weakness.
Economic & scale context
GDP
$730bn
#11 of 51
GDP / capita
$68k
Population
10.7M
AI investment
$8.0bn
#13 of 51
Notable AI orgs
50
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means — and where North Carolina sits |
|---|---|---|---|
| SPI State Power | 61.9 | Strong · #12/51 | High here — a heavyweight that anchors national AI capacity and pulls in capital and talent. ▲ 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 | 56.9 | Strong · #15/51 | 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 | 61.6 | Strong · #14/51 | 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 | 52.1 | Moderate · #17/51 | Mid-pack. High would mean a deep talent pool — the scarcest input to building AI; low would mean 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 | 49.1 | Strong · #15/51 | 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 | 57.7 | Strong · #14/51 | 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 | 63.9 | Moderate · #19/51 | 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 | 61.6 | Strong · #14/51 | 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
- Research (57.7, Strong) — a strong research base feeding a pipeline of ideas and people.
- Agentic (61.6, Strong) — agents are actively deployed — an early-mover productivity edge.
- Capital (49.1, Strong) — abundant capital flowing into building cognitive infrastructure.
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.