Stuttgart
Metro Power
43.1
of 100 · #85
MPI
43.1
MCC
46.8
MDI
43.0
Pillar profile
Talent44.8
Capital31.5
Research47.5
Infrastructure67.1
Agentic43.0
Indicators
- Population (m)2.8
- GDP ($bn)168.2
- GDP per capita ($k)60.5
- AI investment ($bn)2
- Tech employment %8.4
- AI talent60
- Research strength72
- Notable AI orgs24
- Compute / data centers62
- Broadband %92
- Tertiary degree %42
- Digital skills70
- Startup ecosystem58
- Agent adoption44
- Patents / 100k52
Nearest peers
Metro report · generated from Stuttgart's indicators
Stuttgart — metro standing in full
Stuttgart is the #79 metro by economic size ($168bn) in the panel and ranks #85/162 on absolute Metro Power and #72/162 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness. Locally it runs below the Germany national average (MCC 46.8 vs CC 70.0).
National context: Germany scores CC 70.0 per-capita; Stuttgart sits at MCC 46.8.
Economic & scale context ● Eurostat met_10r_3gdp/met_pjanaggr3 (2021/22)
GDP (metro)
$168bn
#79 of 162
GDP / capita
$60k
Population
2.8M
AI investment
$2.0bn
#95 of 162
Notable AI orgs
24
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Stuttgart's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Stuttgart sits |
|---|---|---|---|
| MPI Metro Power | 43.1 | Moderate · #85/162 | 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 | 46.8 | Moderate · #72/162 | Mid-pack. High would mean deep capability per resident — a concentrated, high-intensity ecosystem; low would mean thin intensity per resident — capability is sparse relative to the population. ▲ 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 | 43.0 | Moderate · #78/162 | Mid-pack. High would mean agents are widely deployed locally — a near-term productivity multiplier; low would mean agentic deployment is shallow — the local agent lever is under-used. ▲ 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 | 44.8 | Moderate · #74/162 | Mid-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 Capital | 31.5 | Moderate · #89/162 | 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 | 47.5 | Moderate · #56/162 | Mid-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 Infrastructure | 67.1 | Moderate · #76/162 | 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 | 43.0 | Moderate · #78/162 | Mid-pack. High would mean agents are actively deployed — an early-mover productivity edge; low would mean little agentic deployment — the near-term lever is unused. ▲ high: agents are actively deployed — an early-mover productivity edge · ▼ low: little agentic deployment — the near-term lever is unused |
Strengths to build on
- No pillar stands out as a clear strength yet.
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.