Malaysia
MaintainingAsia-PacificUpper-middle income
Power #23 / 50Per-capita #31
Cognitive Power
34.9
of 100 · #23
CPI
34.9
CC
45.7
ADI
52.5
CDI
0.425
AIR
40.0
AIX
32.2
CRI
35.6
CM
38.0
CV
3.3%
Primary · absolute lens
Cognitive Power
34.9 · #23/50
Total national capacity, AI capital, compute, models & robotics. Strongest in researchers (total), agentic deployment (scale), semiconductor capability.
Per-capita lens
Cognitive Coefficient
45.7 · #31/50
How deep infrastructure runs per person, rewards intensity, like GDP-per-capita or the HDI.
Agentic Deployment Index, the army of agents
Malaysia's agentic capacity
52.5
ADI · #31/50
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)62.0
Access, citizens50.0
Autonomy & reach (what agents can do)56.0
Business deployment40.0
Government deployment50.0
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 Malaysia's indices & economy
Malaysia, cognitive standing in full
Malaysia is the world's #35 economy by GDP ($472bn) and ranks #23/50 on absolute Cognitive Power and #31/50 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 resilience index.
Economic & scale context
The economic base AI capacity is built on, and how its scale interacts with the cognitive indices.
GDP (total)
$472bn
#35 of 50
GDP / capita
$41,498
Upper-middle income · PPP
Population
36M
AI investment
$0.6bn
#33 globally
R&D intensity
0.95%
of GDP
Index-by-index read
For each index: what it means when high (the value) versus low (the risk), and Malaysia's own standing.
| Index | Value | Standing | What a high vs low value means, and where Malaysia sits |
|---|---|---|---|
| CPI Cognitive Power Index | 34.9 | Moderate · #23/50 | 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 | 45.7 | Moderate · #31/50 | Mid-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 Index | 52.5 | Moderate · #31/50 | Mid-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 Index | 0.425 | Developing · #34/50 | 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 | 40.0 | Developing · #34/50 | 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 | 32.2 | Developing · #34/50 | 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 | 35.6 | Developing · #35/50 | 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 | 38.0 | Moderate · #29/50 | Mid-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 Velocity | 3.3% | Moderate · #24/50 | Mid-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
MaintainingMalaysia'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): 38.0 #29/50
Velocity (CV): 3.3% #24/50
Closing the gap: -1.95 pts/yr vs the frontier
Projected CC by 2040: 63.2 (now 45.7, P50 · scenario not forecast)
Strengths to build on
- No standout strengths across the headline indices yet.
Risk factors
- Dependency / low resilience, CRI 35.6 (#35/50): dependency risk: heavy reliance on frontier infrastructure others control, a strategic vulnerability.
- 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, an upper-middle-income economy (GDP/cap $41,498 PPP) whose AI utilization (AIX 32.2) lags its means.
- Binding weakness, Cognitive Resilience Index 35.6 (#35/50, Developing): dependency risk: heavy reliance on frontier infrastructure others control, a strategic vulnerability.
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 Access56.5
AI Adoption26.1
Compute34.6
Data58.6
Education48.8
Digital Literacy63.1
Innovation36.9
Knowledge Infrastructure32.7
Agentic Deployment54.1
Nearest peers
- Russia45.1
- Saudi Arabia48.0
- Greece42.4
- Turkey42.4
- Poland50.0
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
| Indicator | Value | Year | Source | Kind |
|---|---|---|---|---|
| agent_access_pct | 50.0 | 2025 | curated (agentic-deployment estimate) | estimated |
| agent_autonomy_idx | 56.0 | 2025 | curated (agentic-deployment estimate) | estimated |
| agent_capability_idx | 62.0 | 2025 | curated (agentic-deployment estimate) | estimated |
| ai_capital_b | 8.0 | 2024 | Stanford AI Index / state & infra capex (curated) | estimated |
| ai_index_score | 27 | 2024 | Tortoise Global AI Index 2024 | estimated |
| ai_private_investment_b | 0.6 | 2024 | Stanford AI Index 2025 (cumulative) | estimated |
| ai_pubs_share | 0.6 | 2023 | OECD / Elsevier | estimated |
| ai_regulation_idx | 52 | 2024 | curated | estimated |
| ai_skill_penetration | 54 | 2024 | LinkedIn/Stanford AI Index 2025 | estimated |
| ai_strategy_year | 2021 | 2021 | OECD AI Policy Observatory | estimated |
| ai_talent_idx | 39 | 2024 | Tortoise Global AI Index 2024 | estimated |
| cloud_regions | 3 | 2024 | AWS/Azure/GCP region maps 2024 | measured |
| data_governance_idx | 62 | 2024 | PDPA/curated | estimated |
| datacenter_mw | 700 | 2024 | curated estimate (Johor boom) | estimated |
| digital_skills_idx | 58 | 2024 | WEF / ITU-style composite | estimated |
| enterprise_agent_adoption | 40.0 | 2025 | curated (agentic-deployment estimate) | estimated |
| fixed_broadband_per100 | 12 | 2023 | ITU 2023 | measured |
| gdp_pc_ppp | 41498.0 | 2025 | World Bank WDI (PPP) | measured |
| gdp_total_b | 472.2 | 2025 | World Bank WDI | measured |
| gii_score | 40.5 | 2024 | WIPO Global Innovation Index 2024 | measured |
| gov_agent_adoption | 50.0 | 2025 | curated (agentic-deployment estimate) | estimated |
| gov_ai_readiness | 64 | 2024 | Oxford Insights Gov AI Readiness 2024 | measured |
| human_capital_index | 0.61 | 2020 | World Bank HCI 2020 | measured |
| internet_pct | 97 | 2023 | ITU 2023 | measured |
| mean_years_schooling | 10.6 | 2022 | UNDP HDR 2023/24 | measured |
| mobile_broadband_per100 | 130 | 2023 | ITU 2023 | estimated |
| notable_models | 0 | 2024 | Stanford AI Index 2025 | estimated |
| patents_per_million | 40 | 2023 | WIPO | estimated |
| population_m | 36.0 | 2025 | World Bank WDI | measured |
| rd_gdp_pct | 0.95 | 2020 | UNESCO UIS | measured |
| researchers_per_million | 2400 | 2020 | UNESCO UIS | estimated |
| robot_density | 70.0 | 2024 | IFR World Robotics | estimated |
| robot_installs_k | 3.0 | 2024 | IFR World Robotics | estimated |
| robot_stock_k | 18.0 | 2024 | IFR World Robotics | estimated |
| sci_pubs_per_million | 720 | 2022 | World Bank WDI | estimated |
| semiconductor_idx | 42 | 2024 | curated estimate (Penang ATP hub) | estimated |
| stem_grads_share | 27 | 2020 | World Bank/MOHE Malaysia | estimated |
| tertiary_enrollment_pct | 43 | 2021 | UNESCO UIS | measured |
| top500_systems | 1 | 2024 | Top500 2024 | estimated |