CognitiveAristocracy
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Overview / Regions / Salt Lake City

Salt Lake City

US Power #105/162Per-capita #41National view: United States →
Metro Power
38.1
of 100 · #105
MPI
38.1
MCC
53.5
MDI
50.3

Pillar profile

Talent49.3
Capital45.2
Research48.8
Infrastructure74.0
Agentic50.3

Indicators

  • Population (m)1.3
  • GDP ($bn)120
  • GDP per capita ($k)94.5
  • AI investment ($bn)6
  • Tech employment %15
  • AI talent58
  • Research strength72
  • Notable AI orgs14
  • Compute / data centers62
  • Broadband %94
  • Tertiary degree %40
  • Digital skills82
  • Startup ecosystem66
  • Agent adoption56
  • Patents / 100k140

Nearest peers

Metro report · generated from Salt Lake City's indicators

Salt Lake City — metro standing in full

Salt Lake City is the #98 metro by economic size ($120bn) in the panel and ranks #105/162 on absolute Metro Power and #41/162 on per-capita intensity. Its strongest pillar is Capital (45.2, Strong); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 53.5 vs CC 86.7).

National context: United States scores CC 86.7 per-capita; Salt Lake City sits at MCC 53.5.

Economic & scale context ● US Census ACS-1 2022 (population); GDP curated

GDP (metro)
$120bn
#98 of 162
GDP / capita
$94k
Population
1.3M
AI investment
$6.0bn
#35 of 162
Notable AI orgs
14

Index & pillar read

For each metro index and pillar: what it means when high (the value) versus low (the gap), and Salt Lake City's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where Salt Lake City sits
MPI Metro Power38.1Moderate · #105/162Mid-pack. High would mean a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem; low would mean limited absolute weight — a smaller node that leans on capacity built in larger hubs.
▲ high: a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem  ·  ▼ low: limited absolute weight — a smaller node that leans on capacity built in larger hubs
MCC Metro Coefficient53.5Strong · #41/162High here — deep capability per resident — a concentrated, high-intensity ecosystem.
▲ high: deep capability per resident — a concentrated, high-intensity ecosystem  ·  ▼ low: thin intensity per resident — capability is sparse relative to the population
MDI Metro Agentic50.3Strong · #36/162High 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 Talent49.3Moderate · #49/162Mid-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 Capital45.2Strong · #30/162High 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 Research48.8Moderate · #50/162Mid-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 Infrastructure74.0Strong · #38/162High 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 Agentic50.3Strong · #36/162High 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

  • Capital (45.2, Strong) — abundant capital flowing into building cognitive infrastructure.
  • Agentic (50.3, Strong) — agents are actively deployed — an early-mover productivity edge.
  • Infrastructure (74.0, Strong) — the physical and digital rails to run AI at scale are in place.

Risk factors

  • No acute structural gaps stand out across the metro pillars.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.