Bangalore
Metro Power
68.9
of 100 · #14
MPI
68.9
MCC
55.7
MDI
55.9
Pillar profile
Talent58.1
Capital54.3
Research50.2
Infrastructure60.1
Agentic55.9
Indicators
- Population (m)13.6
- GDP ($bn)160
- GDP per capita ($k)12
- AI investment ($bn)7
- Tech employment %14
- AI talent74
- Research strength66
- Notable AI orgs55
- Compute / data centers68
- Broadband %78
- Tertiary degree %42
- Digital skills66
- Startup ecosystem80
- Agent adoption52
- Patents / 100k40
Nearest peers
- Stockholm55.7
- Taipei56.1
- Dallas55.1
- Amsterdam56.4
- Philadelphia54.8
Metro report · generated from Bangalore's indicators
Bangalore — metro standing in full
Bangalore is the #84 metro by economic size ($160bn) in the panel and ranks #14/162 on absolute Metro Power and #33/162 on per-capita intensity. Its strongest pillar is Capital (54.3, Leading); the binding concern is infrastructure. Locally it runs above the India national average (MCC 55.7 vs CC 41.0).
National context: India scores CC 41.0 per-capita; Bangalore sits at MCC 55.7.
Economic & scale context curated v1 estimate
GDP (metro)
$160bn
#84 of 162
GDP / capita
$12k
Population
13.6M
AI investment
$7.0bn
#28 of 162
Notable AI orgs
55
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Bangalore's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Bangalore sits |
|---|---|---|---|
| MPI Metro Power | 68.9 | Leading · #14/162 | 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 | 55.7 | Strong · #33/162 | 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 | 55.9 | Strong · #25/162 | 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 | 58.1 | Strong · #21/162 | 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 | 54.3 | Leading · #15/162 | 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 | 50.2 | Strong · #43/162 | 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 | 60.1 | Developing · #111/162 | Low here — 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 | 55.9 | Strong · #25/162 | 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 (54.3, Leading) — abundant capital flowing into building cognitive infrastructure.
- Talent (58.1, Strong) — a deep talent pool — the scarcest input to building AI.
- Agentic (55.9, Strong) — agents are actively deployed — an early-mover productivity edge.
Risk factors
- Concentration — Bangalore runs well above its national average (MCC 55.7 vs India CC 41.0), a sign cognitive capacity is concentrating in the metro.
- Binding weakness — Infrastructure 60.1 (#111/162, Developing): infrastructure gaps cap how much AI can actually be run locally.
▲
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.