Mississippi
South
State Power #41/51Per-capita #50
State Power
22.1
of 100 · #41
SPI
22.1
SCC
9.2
SDI
9.0
Pillar profile
Talent7.5
Capital8.7
Research9.3
Infrastructure11.6
Agentic9.0
Nearest peers (per-capita)
- Arkansas12.6
- West Virginia5.5
- Wyoming14.5
- Alaska14.9
- Kentucky16.6
Report · generated from Mississippi's indicators
Mississippi — standing in full
Mississippi is the #37 state by economic size ($130bn GSP) and ranks #41/51 on absolute State Power and #50/51 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is agentic.
Economic & scale context
GDP
$130bn
#37 of 51
GDP / capita
$44k
Population
2.9M
AI investment
$0.5bn
#44 of 51
Notable AI orgs
5
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means — and where Mississippi sits |
|---|---|---|---|
| SPI State Power | 22.1 | Developing · #41/51 | 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 | 9.2 | Lagging · #50/51 | 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 | 9.0 | Lagging · #50/51 | 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 | 7.5 | Lagging · #50/51 | 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 | 8.7 | Lagging · #50/51 | 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 | 9.3 | Lagging · #50/51 | 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 | 11.6 | Lagging · #50/51 | 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 | 9.0 | Lagging · #50/51 | 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 — Agentic 9.0 (#50/51, Lagging): little agentic deployment — the near-term lever is unused.
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State values are curated v1 estimates on a consistent scale — not yet measured sub-national data.