Minneapolis
Metro Power
48.5
of 100 · #69
MPI
48.5
MCC
52.6
MDI
50.0
Pillar profile
Talent49.3
Capital38.1
Research51.9
Infrastructure73.5
Agentic50.0
Indicators
- Population (m)3.7
- GDP ($bn)320
- GDP per capita ($k)86.7
- AI investment ($bn)5
- Tech employment %12
- AI talent60
- Research strength78
- Notable AI orgs14
- Compute / data centers62
- Broadband %94
- Tertiary degree %44
- Digital skills81
- Startup ecosystem56
- Agent adoption54
- Patents / 100k135
Nearest peers
- Hong Kong52.6
- Copenhagen52.7
- Vancouver52.5
- Guangzhou53.0
- Lausanne53.1
Metro report · generated from Minneapolis's indicators
Minneapolis — metro standing in full
Minneapolis is the #34 metro by economic size ($320bn) in the panel and ranks #69/162 on absolute Metro Power and #46/162 on per-capita intensity. Its strongest pillar is Research (51.9, Strong); no single pillar is a binding weakness. Locally it runs below the United States national average (MCC 52.6 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Minneapolis sits at MCC 52.6.
Economic & scale context ● US Census ACS-1 2022 (population); GDP curated
GDP (metro)
$320bn
#34 of 162
GDP / capita
$87k
Population
3.7M
AI investment
$5.0bn
#39 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 Minneapolis's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Minneapolis sits |
|---|---|---|---|
| MPI Metro Power | 48.5 | Moderate · #69/162 | 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 | 52.6 | Strong · #46/162 | 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 | 50.0 | Strong · #39/162 | 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 | 49.3 | Strong · #48/162 | 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 | 38.1 | Moderate · #57/162 | Mid-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 Research | 51.9 | Strong · #36/162 | 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 | 73.5 | Strong · #43/162 | 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 | 50.0 | Strong · #39/162 | 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
- Research (51.9, Strong) — a strong research base feeding a pipeline of ideas and people.
- Agentic (50.0, Strong) — agents are actively deployed — an early-mover productivity edge.
- Infrastructure (73.5, 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.