Nigeria
Cognitive Power
Total national capacity — AI capital, compute, models & robotics. Strongest in agentic deployment (scale), economic mass, research output (total).
Cognitive Coefficient
How deep infrastructure runs per person — rewards intensity, like GDP-per-capita or the HDI.
Nigeria's agentic capacity
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.
CC projection to 2040 — Baseline
All 8 scenarios →Monte-Carlo band (P10–P90) around the median path. Dashed = illustrative historical reconstruction.
Pillar profile
Nigeria — cognitive standing in full
Nigeria is the world's #45 economy by GDP ($291bn) and ranks #48/50 on absolute Cognitive Power and #49/50 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 velocity.
Economic & scale context
The economic base AI capacity is built on — and how its scale interacts with the cognitive indices.
Index-by-index read
For each index: what it means when high (the value) versus low (the risk), and Nigeria's own standing.
| Index | Value | Standing | What a high vs low value means — and where Nigeria sits |
|---|---|---|---|
| CPI Cognitive Power Index | 18.0 | Lagging · #48/50 | Low here — 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 | 14.1 | Lagging · #49/50 | 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 | 36.2 | Lagging · #48/50 | 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 | 0.103 | Lagging · #49/50 | 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 | 16.9 | Lagging · #48/50 | 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 | 17.9 | Lagging · #49/50 | 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 | 10.6 | Lagging · #49/50 | 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 | 10.8 | Lagging · #50/50 | 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 | 2.4% | Lagging · #50/50 | 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 behindNigeria'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.
Strengths to build on
- No standout strengths across the headline indices yet.
Risk factors
- Dependency / low resilience — CRI 10.6 (#49/50): 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 Velocity 2.4% (#50/50, Lagging): slow improvement — at risk of drifting backwards in relative terms as the frontier advances.
Recommended priorities
- Prioritise the weakest pillar (Innovation) 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.