Wisconsin
Midwest
State Power #25/51Per-capita #23
State Power
46.7
of 100 · #25
SPI
46.7
SCC
44.2
SDI
45.9
Pillar profile
Talent36.2
Capital34.5
Research46.7
Infrastructure57.6
Agentic45.9
Nearest peers (per-capita)
- Missouri43.7
- New Hampshire43.1
- Delaware42.3
- Rhode Island40.9
- Nevada40.2
Report · generated from Wisconsin's indicators
Wisconsin, standing in full
Wisconsin is the #21 state by economic size ($410bn GSP) and ranks #25/51 on absolute State Power and #23/51 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness.
Economic & scale context
GDP
$410bn
#21 of 51
GDP / capita
$70k
Population
5.9M
AI investment
$4.0bn
#23 of 51
Notable AI orgs
17
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means, and where Wisconsin sits |
|---|---|---|---|
| SPI State Power | 46.7 | Moderate · #25/51 | 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 | 44.2 | Moderate · #23/51 | 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 | 45.9 | Moderate · #26/51 | 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 | 36.2 | Moderate · #27/51 | 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 | 34.5 | Moderate · #24/51 | 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 | 46.7 | Moderate · #22/51 | 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 | 57.6 | Moderate · #23/51 | 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 | 45.9 | Moderate · #26/51 | 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
- 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.