Tampa
Metro Power
38.3
of 100 · #103
MPI
38.3
MCC
36.3
MDI
33.7
Pillar profile
Talent31.7
Capital27.7
Research25.2
Infrastructure63.2
Agentic33.7
Indicators
- Population (m)3.3
- GDP ($bn)195
- GDP per capita ($k)59
- AI investment ($bn)1.7
- Tech employment %5.7
- AI talent46
- Research strength48
- Notable AI orgs11
- Compute / data centers63
- Broadband %90
- Tertiary degree %36
- Digital skills63
- Startup ecosystem53
- Agent adoption41
- Patents / 100k14
Nearest peers
- Rome36.3
- Kuala Lumpur36.0
- Kansas City36.0
- Boise36.6
- Buenos Aires35.7
Metro report · generated from Tampa's indicators
Tampa — metro standing in full
Tampa is the #62 metro by economic size ($195bn) in the panel and ranks #103/162 on absolute Metro Power and #116/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is research. Locally it runs below the United States national average (MCC 36.3 vs CC 86.7).
National context: United States scores CC 86.7 per-capita; Tampa sits at MCC 36.3.
Economic & scale context curated v1 estimate
GDP (metro)
$195bn
#62 of 162
GDP / capita
$59k
Population
3.3M
AI investment
$1.7bn
#101 of 162
Notable AI orgs
11
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Tampa's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Tampa sits |
|---|---|---|---|
| MPI Metro Power | 38.3 | Moderate · #103/162 | 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 | 36.3 | Developing · #116/162 | 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 | 33.7 | Developing · #118/162 | 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 | 31.7 | Developing · #124/162 | 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 | 27.7 | Developing · #112/162 | 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 | 25.2 | Developing · #136/162 | 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 | 63.2 | Moderate · #97/162 | 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 | 33.7 | Developing · #118/162 | 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 — Research 25.2 (#136/162, Developing): a weak research base — fewer home-grown breakthroughs and spinouts.
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Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.