Missouri
Midwest
State Power #24/51Per-capita #24
State Power
46.8
of 100 · #24
SPI
46.8
SCC
43.7
SDI
52.4
Pillar profile
Talent45.8
Capital33.0
Research41.6
Infrastructure45.5
Agentic52.4
Nearest peers (per-capita)
- Wisconsin44.2
- New Hampshire43.1
- Delaware42.3
- Rhode Island40.9
- Nevada40.2
Report · generated from Missouri's indicators
Missouri, standing in full
Missouri is the #22 state by economic size ($390bn GSP) and ranks #24/51 on absolute State Power and #24/51 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure.
Economic & scale context
GDP
$390bn
#22 of 51
GDP / capita
$63k
Population
6.2M
AI investment
$3.0bn
#27 of 51
Notable AI orgs
18
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means, and where Missouri sits |
|---|---|---|---|
| SPI State Power | 46.8 | Moderate · #24/51 | 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 | 43.7 | Moderate · #24/51 | Mid-pack. High would mean deep capability per resident, a concentrated, high-intensity AI economy; low would mean 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 | 52.4 | Moderate · #23/51 | Mid-pack. High would mean agents are widely deployed locally, a near-term productivity multiplier; low would mean 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 | 45.8 | Moderate · #22/51 | 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 | 33.0 | Moderate · #26/51 | 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 | 41.6 | Moderate · #25/51 | 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 | 45.5 | Developing · #34/51 | 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 | 52.4 | Moderate · #23/51 | Mid-pack. High would mean agents are actively deployed, an early-mover productivity edge; low would mean 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, Infrastructure 45.5 (#34/51, Developing): infrastructure gaps cap how much AI can actually be run locally.
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State values are curated v1 estimates on a consistent scale, not yet measured sub-national data.