Pittsburgh
Metro Power
46.7
of 100 · #73
MPI
46.7
MCC
58.3
MDI
60.1
Pillar profile
Talent56.2
Capital43.0
Research61.5
Infrastructure70.5
Agentic60.1
Indicators
- Population (m)2.4
- GDP ($bn)170
- GDP per capita ($k)72.3
- AI investment ($bn)6
- Tech employment %12
- AI talent74
- Research strength88
- Notable AI orgs22
- Compute / data centers58
- Broadband %93
- Tertiary degree %42
- Digital skills80
- Startup ecosystem62
- Agent adoption58
- Patents / 100k140
Nearest peers
Metro report · generated from Pittsburgh's indicators
Pittsburgh, metro standing in full
Pittsburgh is the #77 metro by economic size ($170bn) in the panel and ranks #73/162 on absolute Metro Power and #26/162 on per-capita intensity. Its strongest pillar is Agentic (60.1, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 58.3 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Pittsburgh sits at MCC 58.3.
Economic & scale context ● US Census ACS-1 2022 (population); GDP curated
GDP (metro)
$170bn
#77 of 162
GDP / capita
$72k
Population
2.4M
AI investment
$6.0bn
#33 of 162
Notable AI orgs
22
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Pittsburgh's own standing.
| Index / pillar | Value | Standing | What a high vs low value means, and where Pittsburgh sits |
|---|---|---|---|
| MPI Metro Power | 46.7 | Moderate · #73/162 | Mid-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 Coefficient | 58.3 | Strong · #26/162 | High 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 Agentic | 60.1 | Leading · #16/162 | 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 | 56.2 | Strong · #24/162 | 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 | 43.0 | Strong · #40/162 | 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 | 61.5 | Strong · #19/162 | 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 | 70.5 | Moderate · #58/162 | Mid-pack. High would mean the physical and digital rails to run AI at scale are in place; low would mean infrastructure gaps cap how much AI can actually be run locally. ▲ 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 | 60.1 | Leading · #16/162 | 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
- Agentic (60.1, Leading), agents are actively deployed, an early-mover productivity edge.
- Research (61.5, Strong), a strong research base feeding a pipeline of ideas and people.
- Talent (56.2, Strong), a deep talent pool, the scarcest input to building AI.
Risk factors
- No acute structural gaps stand out across the metro pillars.
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Metro values are curated estimates (v1) on a consistent global scale, not yet measured sub-national data.