Indonesia
Falling behindAsia-PacificLower-middle income
Power #26 / 50Per-capita #45
Cognitive Power
34.6
of 100 · #26
CPI
34.6
CC
29.3
ADI
44.3
CDI
0.266
AIR
28.7
AIX
23.8
CRI
23.5
CM
23.2
CV
2.9%
Primary · absolute lens
Cognitive Power
34.6 · #26/50
Total national capacity — AI capital, compute, models & robotics. Strongest in agentic deployment (scale), economic mass, researchers (total).
Per-capita lens
Cognitive Coefficient
29.3 · #45/50
How deep infrastructure runs per person — rewards intensity, like GDP-per-capita or the HDI.
Agentic Deployment Index — the army of agents
Indonesia's agentic capacity
44.3
ADI · #43/50
How many capable, autonomous agents this society can field, how intelligent they are, and what they are permitted to do — across citizens, business and government. An automated army of agentic problem-solvers may be the single clearest near-term lever of cognitive advantage.
Agent capability (intelligence)56.0
Access — citizens40.0
Autonomy & reach (what agents can do)48.0
Business deployment32.0
Government deployment40.0
CC projection to 2040 — Baseline
All 8 scenarios →Monte-Carlo band (P10–P90) around the median path. Dashed = illustrative historical reconstruction.
Median (P50)P10–P90 bandReconstruction
Pillar profile
Country report · generated from Indonesia's indices & economy
Indonesia — cognitive standing in full
Indonesia is the world's #17 economy by GDP ($1,446bn) and ranks #26/50 on absolute Cognitive Power and #45/50 on per-capita intensity. No index ranks as a clear strength across the headline indices; its trajectory is Falling behind — growing more slowly than the frontier. The binding concern is cognitive development index.
Economic & scale context
The economic base AI capacity is built on — and how its scale interacts with the cognitive indices.
GDP (total)
$1,446bn
#17 of 50
GDP / capita
$17,660
Lower-middle income · PPP
Population
286M
AI investment
$0.6bn
#32 globally
R&D intensity
0.28%
of GDP
Index-by-index read
For each index: what it means when high (the value) versus low (the risk), and Indonesia's own standing.
| Index | Value | Standing | What a high vs low value means — and where Indonesia sits |
|---|---|---|---|
| CPI Cognitive Power Index | 34.6 | Moderate · #26/50 | Mid-pack. High would mean great-power scale: the country can shape the frontier, attract capital and talent, and set standards others follow; low would mean limited absolute weight: a price-taker that depends on capacity built elsewhere. ▲ high: great-power scale: the country can shape the frontier, attract capital and talent, and set standards others follow · ▼ low: limited absolute weight: a price-taker that depends on capacity built elsewhere |
| CC Cognitive Coefficient | 29.3 | Lagging · #45/50 | Low here — thin per-person depth: gains stay concentrated and most of the workforce is under-equipped. ▲ high: deep capability per person: broad productivity gains and a well-equipped workforce · ▼ low: thin per-person depth: gains stay concentrated and most of the workforce is under-equipped |
| ADI Agentic Deployment Index | 44.3 | Developing · #43/50 | Low here — agents are under-deployed — the clearest near-term productivity lever is being left on the table. ▲ high: an automated-agent workforce multiplier is already in place across society · ▼ low: agents are under-deployed — the clearest near-term productivity lever is being left on the table |
| CDI Cognitive Development Index | 0.266 | Lagging · #46/50 | Low here — imbalance or underdevelopment — at least one dimension is a binding weakness. ▲ high: broad, balanced development with no single dimension dragging it down · ▼ low: imbalance or underdevelopment — at least one dimension is a binding weakness |
| AIR AI Readiness | 28.7 | Developing · #42/50 | Low here — governance, data or infrastructure gaps will slow how fast AI can actually be used. ▲ high: institutions and infrastructure are ready to convert capability into real deployment · ▼ low: governance, data or infrastructure gaps will slow how fast AI can actually be used |
| AIX Augmentation Index | 23.8 | Lagging · #45/50 | Low here — access without adoption — the tools exist but are under-used, so the value is unrealised. ▲ high: AI is actively in use across the workforce, so capability is being turned into value · ▼ low: access without adoption — the tools exist but are under-used, so the value is unrealised |
| CRI Cognitive Resilience Index | 23.5 | Lagging · #45/50 | Low here — dependency risk: heavy reliance on frontier infrastructure others control — a strategic vulnerability. ▲ high: strategic autonomy: a broad home-grown base that is hard to cut off or coerce · ▼ low: dependency risk: heavy reliance on frontier infrastructure others control — a strategic vulnerability |
| CM Cognitive Momentum | 23.2 | Developing · #44/50 | Low here — a weak pipeline — the current position may stall or erode without new investment. ▲ high: investment and pipeline favour sustained improvement — today's position is likely to compound · ▼ low: a weak pipeline — the current position may stall or erode without new investment |
| CV Cognitive Velocity | 2.9% | Developing · #44/50 | Low here — slow improvement — at risk of drifting backwards in relative terms as the frontier advances. ▲ high: improving quickly relative to a moving frontier · ▼ low: slow improvement — at risk of drifting backwards in relative terms as the frontier advances |
Trajectory & growth potential
Trajectory & growth potential
Falling behindIndonesia's trajectory is Falling behind — growing more slowly than the frontier. Risk: the relative gap is widening — a compounding disadvantage that can pull capital and talent toward leaders and deepen dependency. The clearest call to act.
Momentum (CM): 23.2 #44/50
Velocity (CV): 2.9% #44/50
Closing the gap: -2.62 pts/yr vs the frontier
Projected CC by 2040: 43.7 (now 29.3, P50 · scenario not forecast)
Strengths to build on
- No standout strengths across the headline indices yet.
Risk factors
- Dependency / low resilience — CRI 23.5 (#45/50): dependency risk: heavy reliance on frontier infrastructure others control — a strategic vulnerability.
- Relative trajectory — Falling behind: Risk: the relative gap is widening — a compounding disadvantage that can pull capital and talent toward leaders and deepen dependency. The clearest call to act.
- Binding weakness — Cognitive Development Index 0.266 (#46/50, Lagging): imbalance or underdevelopment — at least one dimension is a binding weakness.
Recommended priorities
- Prioritise the weakest pillar (AI Adoption) to lift the geometric-mean development index (CDI).
- Convert access into utilization: workforce AI-skilling and agentic-workflow adoption.
- Broaden the base (education + data governance) to raise resilience and reduce concentration risk.
▲
These are model outputs and scenarios, not forecasts of actual outcomes. This platform measures access to, utilization of, and leverage from cognitive infrastructure — not intelligence. No causality or certainty is claimed.
Pillars
AI Access37.1
AI Adoption19.2
Compute21.6
Data32.2
Education32.4
Digital Literacy37.5
Innovation19.4
Knowledge Infrastructure21.5
Agentic Deployment42.7