Kolkata
Metro Power
50.1
of 100 · #62
MPI
50.1
MCC
30.5
MDI
31.2
Pillar profile
Talent31.3
Capital20.9
Research29.2
Infrastructure39.9
Agentic31.2
Indicators
- Population (m)15.1
- GDP ($bn)110
- GDP per capita ($k)7
- AI investment ($bn)0.7
- Tech employment %6
- AI talent48
- Research strength52
- Notable AI orgs14
- Compute / data centers52
- Broadband %68
- Tertiary degree %32
- Digital skills52
- Startup ecosystem50
- Agent adoption36
- Patents / 100k12
Nearest peers
- Amman30.5
- Rio de Janeiro30.8
- Jeddah30.9
- Brasilia29.8
- Bangkok31.5
Metro report · generated from Kolkata's indicators
Kolkata — metro standing in full
Kolkata is the #107 metro by economic size ($110bn) in the panel and ranks #62/162 on absolute Metro Power and #136/162 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 30.5 vs CC 41.0).
National context: India scores CC 41.0 per-capita; Kolkata sits at MCC 30.5.
Economic & scale context curated v1 estimate
GDP (metro)
$110bn
#107 of 162
GDP / capita
$7k
Population
15.1M
AI investment
$0.7bn
#139 of 162
Notable AI orgs
14
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Kolkata's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Kolkata sits |
|---|---|---|---|
| MPI Metro Power | 50.1 | Moderate · #62/162 | 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 | 30.5 | Developing · #136/162 | 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 | 31.2 | Developing · #127/162 | 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 | 31.3 | Developing · #126/162 | Low here — 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 | 20.9 | Developing · #140/162 | 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 | 29.2 | Developing · #121/162 | 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 | 39.9 | Lagging · #146/162 | 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 | 31.2 | Developing · #127/162 | 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 39.9 (#146/162, Lagging): 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.