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Overview / Regions / Amman

Amman

Middle East Power #118/162Per-capita #137
Metro Power
35.1
of 100 · #118
MPI
35.1
MCC
30.5
MDI
29.8

Pillar profile

Talent34.0
Capital20.7
Research24.1
Infrastructure44.1
Agentic29.8

Indicators

  • Population (m)4.5
  • GDP ($bn)38
  • GDP per capita ($k)8.4
  • AI investment ($bn)0.5
  • Tech employment %6
  • AI talent48
  • Research strength46
  • Notable AI orgs12
  • Compute / data centers42
  • Broadband %82
  • Tertiary degree %38
  • Digital skills54
  • Startup ecosystem52
  • Agent adoption34
  • Patents / 100k4

Nearest peers

Metro report · generated from Amman's indicators

Amman — metro standing in full

Amman is the #146 metro by economic size ($38bn) in the panel and ranks #118/162 on absolute Metro Power and #137/162 on per-capita intensity. No pillar stands out as a clear strength; the binding concern is capital.

Economic & scale context curated v1 estimate

GDP (metro)
$38bn
#146 of 162
GDP / capita
$8k
Population
4.5M
AI investment
$0.5bn
#144 of 162
Notable AI orgs
12

Index & pillar read

For each metro index and pillar: what it means when high (the value) versus low (the gap), and Amman's own standing.

Index / pillarValueStandingWhat a high vs low value means — and where Amman sits
MPI Metro Power35.1Developing · #118/162Low here — 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 Coefficient30.5Developing · #137/162Low 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 Agentic29.8Developing · #130/162Low 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 Talent34.0Developing · #118/162Low 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 Capital20.7Developing · #141/162Low 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 Research24.1Developing · #139/162Low 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 Infrastructure44.1Developing · #140/162Low 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 Agentic29.8Developing · #130/162Low 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 — Capital 20.7 (#141/162, Developing): thin investment — good ideas struggle to scale locally.
Metro values are curated estimates (v1) on a consistent global scale — not yet measured sub-national data.