Massachusetts
Northeast
State Power #7/51Per-capita #2
State Power
68.7
of 100 · #7
SPI
68.7
SCC
85.4
SDI
87.9
Pillar profile
Talent83.9
Capital76.8
Research94.0
Infrastructure84.5
Agentic87.9
Nearest peers (per-capita)
- Washington81.5
- New York80.5
- California92.7
- District of Columbia77.1
- Virginia69.9
Report · generated from Massachusetts's indicators
Massachusetts, standing in full
Massachusetts is the #12 state by economic size ($700bn GSP) and ranks #7/51 on absolute State Power and #2/51 on per-capita intensity. Its strongest pillar is Talent (83.9, Leading); no single pillar is a binding weakness.
Economic & scale context
GDP
$700bn
#12 of 51
GDP / capita
$100k
Population
7.0M
AI investment
$30.0bn
#4 of 51
Notable AI orgs
90
Index & pillar read
| Index / pillar | Value | Standing | What a high vs low value means, and where Massachusetts sits |
|---|---|---|---|
| SPI State Power | 68.7 | Strong · #7/51 | 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 | 85.4 | Leading · #2/51 | 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 | 87.9 | Leading · #2/51 | 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 | 83.9 | Leading · #2/51 | 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 | 76.8 | Leading · #4/51 | 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 | 94.0 | Leading · #2/51 | 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 | 84.5 | Strong · #7/51 | 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 | 87.9 | Leading · #2/51 | 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
- Talent (83.9, Leading), a deep talent pool, the scarcest input to building AI.
- Research (94.0, Leading), a strong research base feeding a pipeline of ideas and people.
- Agentic (87.9, Leading), agents are actively deployed, an early-mover productivity edge.
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.