Washington DC
Metro Power
67.2
of 100 · #19
MPI
67.2
MCC
70.0
MDI
71.2
Pillar profile
Talent65.6
Capital58.3
Research61.5
Infrastructure93.5
Agentic71.2
Indicators
- Population (m)6.4
- GDP ($bn)640
- GDP per capita ($k)100.5
- AI investment ($bn)18
- Tech employment %17
- AI talent74
- Research strength86
- Notable AI orgs32
- Compute / data centers95
- Broadband %96
- Tertiary degree %52
- Digital skills87
- Startup ecosystem70
- Agent adoption74
- Patents / 100k110
Nearest peers
Metro report · generated from Washington DC's indicators
Washington DC — metro standing in full
Washington DC is the #12 metro by economic size ($640bn) in the panel and ranks #19/162 on absolute Metro Power and #7/162 on per-capita intensity. Its strongest pillar is Infrastructure (93.5, Leading); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 70.0 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Washington DC sits at MCC 70.0.
Economic & scale context ● US Census ACS-1 2022 (population); GDP curated
GDP (metro)
$640bn
#12 of 162
GDP / capita
$100k
Population
6.4M
AI investment
$18.0bn
#9 of 162
Notable AI orgs
32
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Washington DC's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Washington DC sits |
|---|---|---|---|
| MPI Metro Power | 67.2 | Strong · #19/162 | High here — a heavyweight hub where capital, talent and AI organizations concentrate — it can anchor an entire national AI ecosystem. ▲ 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 | 70.0 | Leading · #7/162 | 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 | 71.2 | Leading · #5/162 | 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 | 65.6 | Leading · #9/162 | 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 | 58.3 | Leading · #12/162 | 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 · #18/162 | 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 | 93.5 | Leading · #2/162 | 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 | 71.2 | Leading · #5/162 | 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
- Infrastructure (93.5, Leading) — the physical and digital rails to run AI at scale are in place.
- Agentic (71.2, Leading) — agents are actively deployed — an early-mover productivity edge.
- Talent (65.6, Leading) — a deep talent pool — the scarcest input to building AI.
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.