Pune
Metro Power
48.7
of 100 · #68
MPI
48.7
MCC
38.1
MDI
35.7
Pillar profile
Talent44.1
Capital28.4
Research33.0
Infrastructure49.1
Agentic35.7
Indicators
- Population (m)7.4
- GDP ($bn)75
- GDP per capita ($k)10
- AI investment ($bn)1.5
- Tech employment %12
- AI talent54
- Research strength54
- Notable AI orgs18
- Compute / data centers58
- Broadband %74
- Tertiary degree %40
- Digital skills58
- Startup ecosystem56
- Agent adoption38
- Patents / 100k22
Nearest peers
- Sacramento37.1
- Indianapolis37.0
- Riyadh39.3
- St. Louis39.3
- Boise36.6
Metro report · generated from Pune's indicators
Pune — metro standing in full
Pune is the #125 metro by economic size ($75bn) in the panel and ranks #68/162 on absolute Metro Power and #111/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is infrastructure. Locally it runs below the India national average (MCC 38.1 vs CC 41.0).
National context: India scores CC 41.0 per-capita; Pune sits at MCC 38.1.
Economic & scale context curated v1 estimate
GDP (metro)
$75bn
#125 of 162
GDP / capita
$10k
Population
7.4M
AI investment
$1.5bn
#105 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 Pune's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Pune sits |
|---|---|---|---|
| MPI Metro Power | 48.7 | Moderate · #68/162 | 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 | 38.1 | Developing · #111/162 | Low here — 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 | 35.7 | Developing · #111/162 | Low here — 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 | 44.1 | Moderate · #80/162 | 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 | 28.4 | Developing · #106/162 | Low here — 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 | 33.0 | Developing · #107/162 | Low here — 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 | 49.1 | Developing · #130/162 | 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 | 35.7 | Developing · #111/162 | Low here — 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
- Binding weakness — Infrastructure 49.1 (#130/162, 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.