New Jersey
Northeast
State Power #10/51Per-capita #7
State Power
64.9
of 100 · #10
SPI
64.9
SCC
68.9
SDI
70.7
Pillar profile
Talent63.1
Capital57.6
Research64.8
Infrastructure88.5
Agentic70.7
Report · generated from New Jersey's indicators
New Jersey, standing in full
New Jersey is the #8 state by economic size ($780bn GSP) and ranks #10/51 on absolute State Power and #7/51 on per-capita intensity. Its strongest pillar is Infrastructure (88.5, Leading); no single pillar is a binding weakness.
Economic & scale context
GDP
$780bn
#8 of 51
GDP / capita
$84k
Population
9.3M
AI investment
$16.0bn
#8 of 51
Notable AI orgs
48
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means, and where New Jersey sits |
|---|---|---|---|
| SPI State Power | 64.9 | Strong · #10/51 | High here, a heavyweight that anchors national AI capacity and pulls in capital and talent. ▲ 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 | 68.9 | Strong · #7/51 | High here, deep capability per resident, a concentrated, high-intensity AI economy. ▲ 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 | 70.7 | Strong · #9/51 | High here, agents are widely deployed locally, a near-term productivity multiplier. ▲ 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 | 63.1 | Strong · #9/51 | High here, a deep talent pool, the scarcest input to building AI. ▲ 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 | 57.6 | Strong · #9/51 | High here, abundant capital flowing into building cognitive infrastructure. ▲ high: abundant capital flowing into building cognitive infrastructure · ▼ low: thin investment, good ideas struggle to scale locally |
| Research Research | 64.8 | Leading · #5/51 | High here, a strong research base feeding a pipeline of ideas and people. ▲ 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 | 88.5 | Leading · #4/51 | High here, the physical and digital rails to run AI at scale are in place. ▲ 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 | 70.7 | Strong · #9/51 | High here, agents are actively deployed, an early-mover productivity edge. ▲ high: agents are actively deployed, an early-mover productivity edge · ▼ low: little agentic deployment, the near-term lever is unused |
Strengths to build on
- Infrastructure (88.5, Leading), the physical and digital rails to run AI at scale are in place.
- Research (64.8, Leading), a strong research base feeding a pipeline of ideas and people.
- Talent (63.1, Strong), a deep talent pool, the scarcest input to building AI.
Risk factors
- No acute structural gaps stand out across the state pillars.
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State values are curated v1 estimates on a consistent scale, not yet measured sub-national data.