CognitiveAristocracy
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Overview / Rankings / US States / Maryland

Maryland

South State Power #15/51Per-capita #10
State Power
56.5
of 100 · #15
SPI
56.5
SCC
65.7
SDI
70.7

Pillar profile

Talent64.8
Capital47.7
Research62.4
Infrastructure82.7
Agentic70.7

Nearest peers (per-capita)

Report · generated from Maryland's indicators

Maryland — standing in full

Maryland is the #17 state by economic size ($480bn GSP) and ranks #15/51 on absolute State Power and #10/51 on per-capita intensity. Its strongest pillar is Talent (64.8, Strong); no single pillar is a binding weakness.

Economic & scale context

GDP
$480bn
#17 of 51
GDP / capita
$78k
Population
6.2M
AI investment
$7.0bn
#14 of 51
Notable AI orgs
50

Index & pillar read

Index / pillarValueStandingWhat a high vs low value means — and where Maryland sits
SPI State Power56.5Strong · #15/51High 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 Coefficient65.7Strong · #10/51High 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 Agentic70.7Strong · #8/51High 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 Talent64.8Strong · #8/51High 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 Capital47.7Moderate · #16/51Mid-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 Research62.4Strong · #10/51High 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 Infrastructure82.7Strong · #8/51High 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 Agentic70.7Strong · #8/51High 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

  • Talent (64.8, Strong) — a deep talent pool — the scarcest input to building AI.
  • Infrastructure (82.7, Strong) — the physical and digital rails to run AI at scale are in place.
  • Agentic (70.7, Strong) — 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.