Machinepower Index / Dossiers / Philippines
Rank 34–46 across the scoring rules tested. How this is tested
Philippines
Diffusion Advantage — For nations that cannot build the frontier but can use it faster than anyone: import the models and win on deployment, across the state and the economy, with public consent.
How the Score, Potential and bottleneck cost are worked out: methodology.
The three layers
Energy, grids, data centres and silicon — the physical capacity to run models at scale.
Epoch AI records no large AI clusters or data centres here yet.
Models, alignment capability, standards influence and the talent that produces them.
The capacity to wire AI into the state and the economy while holding public consent.
Where the score comes from
| Layer | Sub-dimension | Basis | Score |
|---|---|---|---|
| Watts | Planning & Permitting | Assessed | 5.2 |
| Firm Power Capacity | Dataset | 4.4 | |
| Sovereign Compute | Assessed | 2.0 | |
| Hardware & Silicon Access | Dataset | 4.8 | |
| Weights | Frontier Model Output | Dataset | 3.0 |
| Alignment Capability | Assessed | 3.5 | |
| Regulatory Standing | Dataset | 8.3 | |
| Talent Density | Assessed | 5.0 | |
| Will | Policy Capacity | Dataset | 8.5 |
| Public Sector Adoption | Dataset | 6.9 | |
| Workforce Transition | Dataset | 7.3 | |
| Public Trust | Assessed | 7.6 |
Assessed marks a measurement we judged rather than took from a dataset: 5 of the 12 here.
Sources
Fast-track permits and a plan to grow AI capacity from about 50 MW to 1.5 GW by 2033, on some of the region's dearest power.
View source →A national AI roadmap but no AI law or safety body.
View source →A cross-check for planning and permitting, which stays assessed: it scores permits and electricity connections for ordinary firms, not grid-scale connections for data centres.
View source →No system on the June 2026 TOP500 and no compute controlled by the state, universities or firms in Epoch AI; set at the floor.
View source →Stanford does not count Philippines. Estimated from 2.8 million GitHub developers and Oxford Insights' diffusion pillar, calibrated on the nations Stanford counts.
View source →Feeds governance and public-sector adoption; policy capacity is listed separately.
View source →No AI survey in the last three years covers it; set at the median of the 15 surveyed emerging and developing economies in the Index.
View source →Feeds workforce, rescaled across 173 economies.
View source →Fossil, nuclear, hydro and other dispatchable plant; averaged with generation for firm power.
View source →Bottlenecks
These hold Philippines below its Potential. Its two lowest scores cost it the most: sovereign compute at 2.0 (part of Watts) and frontier model output at 3.0 (part of Weights).
Assessment
The Philippines is the world's back office, and AI threatens that first. It has a large developer base, little compute and some of the region's dearest power.
The art of the possible
A new masterplan aims to grow AI data-centre capacity thirty-fold by 2033. The bigger gain is moving the outsourcing industry from doing the work to supervising the models that do it.
Strategic play — Diffusion Advantage
Retrain the back office for AI operations — evaluation, data work, oversight — before automation takes the jobs it has.
Leverage — the nearest position. No chokepoint. Its position is the outsourcing industry itself: work the world's firms rely on, but can move.
Open Philippines in the live Index → — every source behind every number, and the comparison tool.