South Dakota
Midwest
State Power #47/51Per-capita #43
State Power
12.5
of 100 · #47
SPI
12.5
SCC
20.1
SDI
22.7
Pillar profile
Talent20.4
Capital12.3
Research18.1
Infrastructure27.2
Agentic22.7
Nearest peers (per-capita)
- Alabama20.8
- North Dakota21.9
- Montana22.1
- Oklahoma17.4
- Louisiana17.2
Report · generated from South Dakota's indicators
South Dakota — standing in full
South Dakota is the #46 state by economic size ($70bn GSP) and ranks #47/51 on absolute State Power and #43/51 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is research.
Economic & scale context
GDP
$70bn
#46 of 51
GDP / capita
$77k
Population
0.9M
AI investment
$0.4bn
#47 of 51
Notable AI orgs
4
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means — and where South Dakota sits |
|---|---|---|---|
| SPI State Power | 12.5 | Lagging · #47/51 | Low here — 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 | 20.1 | Developing · #43/51 | 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 | 22.7 | Developing · #42/51 | 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 | 20.4 | Developing · #42/51 | 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 | 12.3 | Lagging · #45/51 | 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 | 18.1 | Lagging · #45/51 | 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 | 27.2 | Developing · #41/51 | 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 | 22.7 | Developing · #42/51 | 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 — Research 18.1 (#45/51, Lagging): a weak research base — fewer home-grown breakthroughs and spinouts.
▲
State values are curated v1 estimates on a consistent scale — not yet measured sub-national data.