Brisbane
Metro Power
41.2
of 100 · #92
MPI
41.2
MCC
47.8
MDI
45.8
Pillar profile
Talent47.6
Capital33.0
Research41.4
Infrastructure71.0
Agentic45.8
Indicators
- Population (m)2.6
- GDP ($bn)180
- GDP per capita ($k)69
- AI investment ($bn)1.8
- Tech employment %7.5
- AI talent60
- Research strength66
- Notable AI orgs20
- Compute / data centers66
- Broadband %92
- Tertiary degree %50
- Digital skills74
- Startup ecosystem62
- Agent adoption48
- Patents / 100k34
Nearest peers
- Edinburgh47.8
- Abu Dhabi47.6
- Barcelona47.4
- Oslo48.2
- Gothenburg48.3
Metro report · generated from Brisbane's indicators
Brisbane — metro standing in full
Brisbane is the #70 metro by economic size ($180bn) in the panel and ranks #92/162 on absolute Metro Power and #66/162 on per-capita intensity. No pillar stands out as a clear strength; no single pillar is a binding weakness. Locally it runs below the Australia national average (MCC 47.8 vs CC 61.9).
National context: Australia scores CC 61.9 per-capita; Brisbane sits at MCC 47.8.
Economic & scale context curated v1 estimate
GDP (metro)
$180bn
#70 of 162
GDP / capita
$69k
Population
2.6M
AI investment
$1.8bn
#100 of 162
Notable AI orgs
20
Index & pillar read
For each metro index and pillar: what it means when high (the value) versus low (the gap), and Brisbane's own standing.
| Index / pillar | Value | Standing | What a high vs low value means — and where Brisbane sits |
|---|---|---|---|
| MPI Metro Power | 41.2 | Moderate · #92/162 | 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 | 47.8 | Moderate · #66/162 | Mid-pack. High would mean deep capability per resident — a concentrated, high-intensity ecosystem; low would mean 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 | 45.8 | Moderate · #62/162 | Mid-pack. High would mean agents are widely deployed locally — a near-term productivity multiplier; low would mean 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 | 47.6 | Moderate · #59/162 | 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 | 33.0 | Moderate · #79/162 | Mid-pack. High would mean abundant capital flowing into building cognitive infrastructure; low would mean 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 | 41.4 | Moderate · #81/162 | Mid-pack. High would mean a strong research base feeding a pipeline of ideas and people; low would mean 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 | 71.0 | Moderate · #55/162 | 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 | 45.8 | Moderate · #62/162 | Mid-pack. High would mean agents are actively deployed — an early-mover productivity edge; low would mean 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
- No acute structural gaps stand out across the metro pillars.
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Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.