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Overview / Rankings / New Zealand

New Zealand

MaintainingAsia-PacificHigh income Power #44 / 50Per-capita #24
Cognitive Power
20.3
of 100 · #44
CPI
20.3
CC
56.3
ADI
62.5
CDI
0.551
AIR
43.5
AIX
42.8
CRI
43.3
CM
42.8
CV
3.3%
Primary · absolute lens

Cognitive Power

20.3 · #44/50

Total national capacity, AI capital, compute, models & robotics. Strongest in researchers (total), economic mass, research output (total).

Per-capita lens

Cognitive Coefficient

56.3 · #24/50

How deep infrastructure runs per person, rewards intensity, like GDP-per-capita or the HDI.

Agentic Deployment Index, the army of agents

New Zealand's agentic capacity

62.5
ADI · #23/50

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)71.0
Access, citizens63.0
Autonomy & reach (what agents can do)67.0
Business deployment49.0
Government deployment56.0

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 New Zealand's indices & economy

New Zealand, cognitive standing in full

New Zealand is the world's #47 economy by GDP ($264bn) and ranks #44/50 on absolute Cognitive Power and #24/50 on per-capita intensity. No index ranks as a clear strength across the headline indices; its trajectory is Maintaining, holding position but not compounding an advantage. The binding concern is cognitive power index.

Economic & scale context

The economic base AI capacity is built on, and how its scale interacts with the cognitive indices.

GDP (total)
$264bn
#47 of 50
GDP / capita
$57,350
High income · PPP
Population
5M
AI investment
$0.6bn
#34 globally
R&D intensity
1.45%
of GDP

Index-by-index read

For each index: what it means when high (the value) versus low (the risk), and New Zealand's own standing.

IndexValueStandingWhat a high vs low value means, and where New Zealand sits
CPI Cognitive Power Index20.3Developing · #44/50Low 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 Coefficient56.3Moderate · #24/50Mid-pack. High would mean deep capability per person: broad productivity gains and a well-equipped workforce; low would mean 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 Index62.5Moderate · #23/50Mid-pack. High would mean an automated-agent workforce multiplier is already in place across society; low would mean 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 Index0.551Moderate · #24/50Mid-pack. High would mean broad, balanced development with no single dimension dragging it down; low would mean 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 Readiness43.5Moderate · #28/50Mid-pack. High would mean institutions and infrastructure are ready to convert capability into real deployment; low would mean 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 Index42.8Moderate · #24/50Mid-pack. High would mean AI is actively in use across the workforce, so capability is being turned into value; low would mean 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 Index43.3Moderate · #26/50Mid-pack. High would mean strategic autonomy: a broad home-grown base that is hard to cut off or coerce; low would mean 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 Momentum42.8Moderate · #25/50Mid-pack. High would mean investment and pipeline favour sustained improvement, today's position is likely to compound; low would mean 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 Velocity3.3%Moderate · #25/50Mid-pack. High would mean improving quickly relative to a moving frontier; low would mean 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

Maintaining

New Zealand's trajectory is Maintaining, holding position but not compounding an advantage. Risk: the frontier keeps moving, so standing still means slow relative decline. A stable base, but it needs fresh momentum to avoid drifting back.

Momentum (CM): 42.8 #25/50 Velocity (CV): 3.3% #25/50 Closing the gap: -1.60 pts/yr vs the frontier Projected CC by 2040: 74.6 (now 56.3, P50 · scenario not forecast)

Strengths to build on

  • No standout strengths across the headline indices yet.

Risk factors

  • Relative trajectory, Maintaining: Risk: the frontier keeps moving, so standing still means slow relative decline. A stable base, but it needs fresh momentum to avoid drifting back.
  • Affluent but under-utilizing, a high-income economy (GDP/cap $57,350 PPP) whose AI utilization (AIX 42.8) lags its means.
  • Binding weakness, Cognitive Power Index 20.3 (#44/50, Developing): limited absolute weight: a price-taker that depends on capacity built elsewhere.

Recommended priorities

  • Prioritise the weakest pillar (Compute) 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 Access65.6
AI Adoption33.7
Compute21.0
Data87.5
Education62.8
Digital Literacy78.6
Innovation47.2
Knowledge Infrastructure42.3
Agentic Deployment68.3
Provenance & what changed · 39 indicator cells · year, source, measured vs estimated

Rank movement

  • no rank movement since the previous snapshot

Applied research changes

  • no applied research changes name this economy in the window
IndicatorValueYearSourceKind
agent_access_pct63.02025curated (agentic-deployment estimate) estimated
agent_autonomy_idx67.02025curated (agentic-deployment estimate) estimated
agent_capability_idx71.02025curated (agentic-deployment estimate) estimated
ai_capital_b2.02024Stanford AI Index / state & infra capex (curated) estimated
ai_index_score302024Tortoise Global AI Index 2024 estimated
ai_private_investment_b0.62024Stanford AI Index 2025 (cumulative) estimated
ai_pubs_share0.52023OECD / Elsevier estimated
ai_regulation_idx602024curated estimated
ai_skill_penetration662024LinkedIn/Stanford AI Index 2025 estimated
ai_strategy_yearNone2024OECD AI Policy Observatory estimated
ai_talent_idx472024Tortoise Global AI Index 2024 estimated
cloud_regions32024AWS/Azure/GCP region maps 2024 measured
data_governance_idx822024OECD/curated estimated
datacenter_mw2502024curated estimate estimated
digital_skills_idx742024WEF / ITU-style composite estimated
enterprise_agent_adoption49.02025curated (agentic-deployment estimate) estimated
fixed_broadband_per100372023ITU 2023 measured
gdp_pc_ppp57350.02025World Bank WDI (PPP) measured
gdp_total_b264.12025World Bank WDI measured
gii_score47.52024WIPO Global Innovation Index 2024 measured
gov_agent_adoption56.02025curated (agentic-deployment estimate) estimated
gov_ai_readiness752024Oxford Insights Gov AI Readiness 2024 measured
human_capital_index0.772020World Bank HCI 2020 measured
internet_pct962023ITU 2023 measured
mean_years_schooling12.92022UNDP HDR 2023/24 measured
mobile_broadband_per1001102023ITU 2023 estimated
notable_models02024Stanford AI Index 2025 estimated
patents_per_million1202023WIPO estimated
population_m5.32025World Bank WDI measured
rd_gdp_pct1.452021OECD measured
researchers_per_million56502019UNESCO UIS / OECD estimated
robot_density60.02024IFR World Robotics estimated
robot_installs_k0.32024IFR World Robotics estimated
robot_stock_k2.02024IFR World Robotics estimated
sci_pubs_per_million23002022World Bank WDI estimated
semiconductor_idx202024curated estimate estimated
stem_grads_share202020OECD measured
tertiary_enrollment_pct812020UNESCO UIS measured
top500_systems12024Top500 2024 estimated