Total Sovereignty
For the two nations able to attempt every layer alone: own the whole stack, from energy and chips to frontier models and the rules, while depending on each other somewhere.
The Machinepower Index is an AI sovereignty index that ranks countries on whether they can build, power and control their own AI, and maps the chokepoints and blocs that decide who depends on whom.
The decisive resources of the twenty-first century will not be land, labour, or votes — but compute, models, and the energy to sustain them.
Whoever controls this infrastructure will control everything built atop it: markets, militaries, governance, and the information environment itself.
This is machinepower: the ability to generate and deploy artificial intelligence at scale.
The difference between an AI maker and an AI taker will determine national fate in the century ahead.
The Machinepower Index (MPI) 2026 is a live policy tool, updated regularly, that assesses national capacity across three strategic axes — Watts (Material), Weights (Intellectual), and Will (Political).
Nations are not adopting AI because it is innovative. They are adopting it because they must.
The tangible foundations: energy, infrastructure, and compute. Without the physical capacity to run models, sovereignty is impossible.
Control over intelligence itself: who builds models, shapes behaviour, and retains talent.
The capacity to wire AI into the state while maintaining legitimacy and public consent.
AI capability behaves like a production system: the slowest stage limits total output. So the Index does not average. A nation’s Score comes from the twelve measurements beneath the three layers, and one weak measurement pulls the whole Score down instead of being averaged away.
What most indices would publish.
Two of Singapore’s twelve measurements sit far below the layers holding them. Averaging hid both.
Singapore, as of October 2026. Nearly a full point separates what its average promises (6.77) from what it can actually do (5.86), and a Will of 8.5 buys none of it back. Read the dossier →
Not every nation needs, or can afford, full AI sovereignty. Each of the eight playbooks starts from one question about what a nation holds, and the Index assigns every nation to one.
For the two nations able to attempt every layer alone: own the whole stack, from energy and chips to frontier models and the rules, while depending on each other somewhere.
For economies big enough to cover most layers without leading any: build enough compute, open models and a resilient grid to depend on no single supplier and bargain from strength.
For nations holding a step in the chain nobody can route around, which their government could switch off: trade access for compute, investment and protection, and stay irreplaceable.
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.
For nations whose main asset is the ground itself, meaning cheap clean power, land and stability: host other nations' compute and turn geography into rent, jobs and relevance.
For nations among the world's best at something the frontier needs but could find elsewhere: keep earning the lead before others catch up, and trade expertise for access.
For nations with more money than research depth: buy the frontier rather than build it, acquiring chips, talent, data centres and equity stakes at scale while the window is open.
For nations cut off from allied hardware and markets: build whatever the available silicon allows, accept a slower path, and treat sovereignty as a necessity rather than a choice.
Measured — October 2026 update. All 50 ranked nations plus the EU. Every point sits below the diagonal, because no nation is perfectly balanced; the vertical drop is what its imbalance costs. The Score uses the twelve measurements beneath the three layers rather than the layer averages, which is why lopsided nations fall — Estonia carries the widest gap in the Index at 2.19 Hover any point, or read the full dossiers.
Leavy, E. (2026). Machinepower Index: The AI Sovereignty Index. Updated October 2026. https://machinepowerindex.org
Fifty nations scored on the record, plus the EU for reference, which is not ranked. Figures as of October 2026. Read the full dossiers →
Agreed during Xi Jinping's state visit to Washington: a channel for AI incidents and a standing dialogue on advanced AI, with the next session due by November.
China's answer to Washington's AI Opportunity statement: 29 founders in Shanghai and 37 signatories within a fortnight, five of whom have also signed with Washington.
The Index is updated regularly, as new data and events arrive, with essays in between. Leave your email and each update comes to you, or follow along on the Machinepower Substack.
The Machinepower Index is an AI sovereignty index that ranks countries on whether they can build, power and control their own AI, and maps the chokepoints and blocs that decide who depends on whom. It scores twelve measurements across three layers: energy and compute, models and talent, and the state's capacity to adopt AI with public consent. A nation's Score is set by its weakest measurements rather than its average.
Machinepower is the strategic capability and capacity to generate and deploy artificial intelligence at scale. It represents a paradigm shift from manpower — the historical foundation of national strength — to sovereign computational and algorithmic capacity. The aim of the Index is to do for that shift what GDP did for industrial output: give governments one measure they can compare across nations.
The Index looks for bottlenecks. AI capability works like a production line: the slowest stage sets the output. Most indices average their dimensions, which lets a good score in one place cancel a bad one somewhere else. This one does not, because a world-class model is no use on a grid that cannot power it. A nation needs all three at once.
The Score comes from the twelve measurements beneath the three layers, not from the layer averages — because averaging hides things. A 10 next to a 3 comes out as a forgettable 6.5, and you lose both facts. Potential is the plain average of the three layers, and the gap between the two is what being lopsided costs.
The exact formula, how much the ranking moves under every other scoring rule we tested, where each number came from and what the Index gets wrong are all on the methodology page.
As of October 2026, the United States ranks first in the Machinepower Index with a Score of 8.30 out of 10, followed by China (8.23), South Korea (7.40), France (6.75) and Germany (6.74). Because the Score is set by a nation's weakest measurements, lopsided nations rank lower than their strengths suggest.
As of October 2026, 54 countries have signed Washington's Joint Statement on AI Opportunity and 37 have signed the founding agreement of China's World AI Cooperation Organization (WAICO). Five have signed both: Georgia, Kazakhstan, Malaysia, Serbia and Vietnam. Of the nations the Index ranks, 30 are in the US-led group and ten are WAICO members, with Kazakhstan, Malaysia and Vietnam in both, and 13 are in neither, among them Canada, France, Saudi Arabia, Spain and Taiwan.
The idea is older than AI. In 1890 Alfred Thayer Mahan, an American naval officer, argued in The Influence of Sea Power upon History that power at sea came from two sources: what a nation could build and keep up for itself, meaning its trade, its shipping and its fleet, and the positions it held on the routes everyone else had to use, the “stations along the road” such as Gibraltar and the Cape. A nation needed both, and neither could be bought with the other. In 1904 Admiral Sir John Fisher, the head of the Royal Navy, named Britain’s positions in a single line: “Five keys lock up the world! Singapore, the Cape, Alexandria, Gibraltar, Dover.”
AI splits the same way. Building and running your own systems is one kind of power, and holding something every other country has to pass through is another, so a nation can have a great deal of one and none of the other. The Score measures the first, and the chokepoint register maps the second.
The Index itself grew out of research for the book, Machinepower: The Realpolitik of Artificial Intelligence, which examines how the ability to deploy AI at scale is becoming the defining strategic capability of the twenty-first century. I am interviewing the people shaping the Intelligence Age — government insiders, think tank heads, executives at the major hyperscalers — to inform its structure.