Vienna
Metro Power
40.4
of 100 · #94
MPI
40.4
MCC
43.7
MDI
38.9
Pillar profile
Talent40.8
Capital29.4
Research43.2
Infrastructure66.3
Agentic38.9
Indicators
- Population (m)2.9
- GDP ($bn)151.6
- GDP per capita ($k)52.1
- AI investment ($bn)2
- Tech employment %7
- AI talent52
- Research strength70
- Notable AI orgs18
- Compute / data centers54
- Broadband %94
- Tertiary degree %46
- Digital skills74
- Startup ecosystem54
- Agent adoption44
- Patents / 100k40
Nearest peers
Metro report · generated from Vienna's indicators
Vienna — metro standing in full
Vienna is the #91 metro by economic size ($152bn) in the panel and ranks #94/162 on absolute Metro Power and #90/162 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness. Locally it runs below the Austria national average (MCC 43.7 vs CC 59.8).
National context: Austria scores CC 59.8 per-capita; Vienna sits at MCC 43.7.
Economic & scale context ● Eurostat met_10r_3gdp/met_pjanaggr3 (2021/22)
GDP (metro)
$152bn
#91 of 162
GDP / capita
$52k
Population
2.9M
AI investment
$2.0bn
#83 of 162
Notable AI orgs
18
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Vienna's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Vienna sits |
|---|---|---|---|
| MPI Metro Power | 40.4 | Moderate · #94/162 | 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 | 43.7 | Moderate · #90/162 | 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 | 38.9 | Moderate · #99/162 | 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 | 40.8 | Moderate · #92/162 | 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 | 29.4 | Moderate · #97/162 | 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 | 43.2 | Moderate · #72/162 | 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 | 66.3 | Moderate · #82/162 | 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 | 38.9 | Moderate · #99/162 | 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.