CognitiveAristocracy
Detail
Overview / Rankings / US States / Virginia

Virginia

South State Power #10/51Per-capita #6
State Power
63.5
of 100 · #10
SPI
63.5
SCC
68.8
SDI
74.7

Pillar profile

Talent66.4
Capital54.6
Research60.9
Infrastructure87.5
Agentic74.7

Nearest peers (per-capita)

Report · generated from Virginia's indicators

Virginia — standing in full

Virginia is the #13 state by economic size ($650bn GSP) and ranks #10/51 on absolute State Power and #6/51 on per-capita intensity. Its strongest pillar is Infrastructure (87.5, Leading); no single pillar is a binding weakness.

Economic & scale context

GDP
$650bn
#13 of 51
GDP / capita
$75k
Population
8.7M
AI investment
$11.0bn
#10 of 51
Notable AI orgs
60

Index & pillar read

Index / pillarValueStandingWhat a high vs low value means — and where Virginia sits
SPI State Power63.5Strong · #10/51High 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 Coefficient68.8Strong · #6/51High 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 Agentic74.7Strong · #6/51High 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 Talent66.4Strong · #7/51High 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 Capital54.6Strong · #11/51High 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 Research60.9Strong · #12/51High 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 Infrastructure87.5Leading · #5/51High 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 Agentic74.7Strong · #6/51High 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 (87.5, Leading) — the physical and digital rails to run AI at scale are in place.
  • Agentic (74.7, Strong) — agents are actively deployed — an early-mover productivity edge.
  • Talent (66.4, Strong) — a deep talent pool — the scarcest input to building AI.

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.