Tel Aviv
Metro Power
68.9
of 100 · #15
MPI
68.9
MCC
70.7
MDI
67.0
Pillar profile
Talent69.1
Capital71.3
Research71.1
Infrastructure74.9
Agentic67.0
Indicators
- Population (m)4.2
- GDP ($bn)290
- GDP per capita ($k)69
- AI investment ($bn)22
- Tech employment %16
- AI talent82
- Research strength80
- Notable AI orgs120
- Compute / data centers62
- Broadband %94
- Tertiary degree %52
- Digital skills84
- Startup ecosystem90
- Agent adoption62
- Patents / 100k140
Nearest peers
- Washington DC70.0
- Shenzhen69.7
- London69.2
- Beijing72.7
- Austin67.2
Metro report · generated from Tel Aviv's indicators
Tel Aviv — metro standing in full
Tel Aviv is the #39 metro by economic size ($290bn) in the panel and ranks #15/162 on absolute Metro Power and #6/162 on per-capita intensity. Its strongest pillar is Capital (71.3, Leading); no single pillar is a binding weakness. Locally it runs above the Israel national average (MCC 70.7 vs CC 65.9).
National context: Israel scores CC 65.9 per-capita; Tel Aviv sits at MCC 70.7.
Economic & scale context curated v1 estimate
GDP (metro)
$290bn
#39 of 162
GDP / capita
$69k
Population
4.2M
AI investment
$22.0bn
#8 of 162
Notable AI orgs
120
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Tel Aviv's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Tel Aviv sits |
|---|---|---|---|
| MPI Metro Power | 68.9 | Leading · #15/162 | 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 | 70.7 | Leading · #6/162 | 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 | 67.0 | Leading · #8/162 | 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 | 69.1 | Leading · #6/162 | 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 | 71.3 | Leading · #5/162 | 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 | 71.1 | Leading · #7/162 | 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 | 74.9 | Strong · #36/162 | 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 | 67.0 | Leading · #8/162 | 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
- Capital (71.3, Leading) — abundant capital flowing into building cognitive infrastructure.
- Talent (69.1, Leading) — a deep talent pool — the scarcest input to building AI.
- Research (71.1, Leading) — a strong research base feeding a pipeline of ideas and people.
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.