South Carolina
South
State Power #27/51Per-capita #38
State Power
37.8
of 100 · #27
SPI
37.8
SCC
25.7
SDI
25.2
Pillar profile
Talent22.5
Capital21.1
Research25.1
Infrastructure34.4
Agentic25.2
Nearest peers (per-capita)
- Hawaii26.3
- Maine24.0
- Montana22.1
- North Dakota21.9
- Alabama20.8
Report · generated from South Carolina's indicators
South Carolina — standing in full
South Carolina is the #26 state by economic size ($290bn GSP) and ranks #27/51 on absolute State Power and #38/51 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is talent.
Economic & scale context
GDP
$290bn
#26 of 51
GDP / capita
$55k
Population
5.3M
AI investment
$1.5bn
#31 of 51
Notable AI orgs
12
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means — and where South Carolina sits |
|---|---|---|---|
| SPI State Power | 37.8 | Moderate · #27/51 | 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 | 25.7 | Developing · #38/51 | Low here — thin intensity per resident — capability is sparse relative to population. ▲ 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 | 25.2 | Developing · #40/51 | Low here — agentic deployment is shallow — the local agent lever is under-used. ▲ 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 | 22.5 | Developing · #41/51 | Low here — 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 | 21.1 | Developing · #35/51 | Low here — 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 | 25.1 | Developing · #37/51 | Low here — 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 | 34.4 | Developing · #37/51 | Low here — 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 | 25.2 | Developing · #40/51 | Low here — little agentic deployment — the near-term lever is unused. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- No pillar stands out as a clear strength yet.
Risk factors
- Binding weakness — Talent 22.5 (#41/51, Developing): a shallow talent base that constrains how much can be built locally.
▲
State values are curated v1 estimates on a consistent scale — not yet measured sub-national data.