National Value Model (NVM): A Framework for National and Enterprise Strategy

A Theory of Resource, Transformation, and Utilization for Nations in the Age of AI, with Critical-Tier Governance

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"The countries that have AI are the strong ones." Intuitively, that sounds right. As analysis, it does not hold. Where a country holds its AI capability (position) and how much that capability acts on others (leverage) are two different variables.

This paper places nations on a grid: the tier of AI capability on the vertical axis, where value is created on the horizontal. On the nine squares where they cross — the nine cells — it describes what happens, and what does not.

VURA Working Paper No.10. This page explains the theory's main points. The full paper (English edition, 1,230 pages; Japanese original, 903 pages) is linked at the end.

This paper in three minutes

• It places nations on nine cells. Vertical: tier of AI capability (C1 commodity / C2 frontier / C3 critical). Horizontal: where value is created (M1 resource / M2 transformation / M3 utilization). A description of position, not a ranking.

• Its strongest claim is one sentence. "Designing AI policy as efficiency policy is a systematic error." AI capability descends to cheaper tiers, so an efficiency advantage is the first to disappear.

• The grid moves. Up (toward resource, toward the frontier) takes years of accumulation. Down takes nothing — others accumulate and you fall. A nation that does nothing descends.

• Having and acting on others are different things. What everyday language calls "dependence," the paper splits into indispensability, lock-in, and desirability.

• Stopping is different, too. A power outage stops at the border. AI stops across borders, at the same time — an AI outage.

• It does not forecast. It hands you instruments. Three futures — fragmentation, diffusion, stagnation — and four investments with positive value in every one: the no-regret actions.

• It writes down its own weak points. Forty-seven limitations, the largest hole (leading indicators never back-tested), the author's conflict of interest, and six places the reader should doubt — all named by the paper itself.

The paper's strongest claim

One sentence runs through the whole paper.

Designing AI policy as efficiency policy is a systematic error.

In plain terms — Using AI to make work faster and cheaper is fine in itself. Making that the purpose of policy puts a nation's resources exactly where value is lost first.

The reason is simple. AI capability descends, over time, into cheaper tiers. Once a capability reaches the tier anyone can buy, efficiency gains built on it are available to everyone — and therefore confer no competitive advantage.

What remains after efficiency advantages are competed away is the ability to decide what counts as value. The paper calls this value-definition capability: deciding, for oneself, what to make and what to regard as valuable.

An analogy: arithmetic after the calculator

An analogy. Being fast at arithmetic was once a professional advantage. When a calculator landed on every desk, it stopped being one. What vanished was not the value of calculation. It was the scarcity of being fast.

What was left was the value of the person who decides what to calculate. AI and efficiency, the paper argues, have the same shape.

This claim carries a falsification condition — every proposition in the paper does. Each states, alongside the claim, "if this observation appears, the claim is refuted." That is the discipline of the series.

The starting point: no one-word answer to "Is AI the new oil?"

From here the paper builds the vertical axis of the nine cells — the tiers of AI capability. Before that, it settles how analogies are to be used at all.

Three analogies recur whenever AI is discussed: oil, electricity, and nuclear weapons. The paper picks none. It first sets out a discipline for using analogies.

An analogy is usable only after likeness and unlikeness are separated

Oil can be stockpiled. AI cannot. When electricity fails, the blackout stops at the border. AI supply is correlated across borders. Nuclear technology acquired a verification mechanism; AI cannot be frozen by the same method.

The paper's answer: "It depends on the tier of capability." The same word, "AI," covers different tiers, and the fitting analogy changes with the tier. So the tiers are defined first.

Three tiers of AI capability (C1, C2, C3)

The vertical axis has three levels. The higher the tier, the less it is something anyone can obtain.

TierWhat it is

C1 | Commodity tierCapability that has become widely available and is subject to price competition

C2 | Frontier tierCapability near the leading edge, where a gap over others is maintained

C3 | Critical tierA domain of capability that would require dedicated governance. Not yet realized

C3 is a category the paper examines as a future possibility. It does not speak of it as something that has arrived. So six of the nine cells are currently operating. The paper holds that restraint to the end.

The part of the paper that asks how C3 would be governed is critical-tier governance — the phrase in the subtitle: governance designed in advance, for a tier that does not yet exist.

The nine cells — where value is created × tier of AI capability

Now the horizontal axis — where the country creates value — is added and the grid is complete.

• M1 | Resource Model — the position that produces AI itself

• M2 | Transformation Model — the position that converts AI into products and services

• M3 | Utilization Model — the position that puts AI to use in industry and society

C1–C3 crossed with M1–M3 gives the nine national value cells.

M1 ResourceM2 TransformationM3 Utilization

C3 Critical tiernot yet realizednot yet realizednot yet realized

C2 Frontier tieroperatingoperatingoperating

C1 Commodity tieroperatingoperatingoperating

Two misreadings to head off

"Is the nine-cell grid a league table of national power?" No. It is a description of position, not a ranking. The paper never says "the upper cells" or "the more advanced position." It describes only direction — toward resource, toward the frontier. Countries and regions are units of analysis, not objects of evaluation.

An analogy. Picture an orchestra's seating chart. Strings at the front, brass behind, percussion at the back. It is a diagram of placement, not one in which the front seats outrank the rest. Once you know the placement, you can read which gap would make the whole fall apart. The nine cells give the same kind of information.

"If a nation is in this cell, are its companies in the same cell?" No. A nation's position sets the cell-occupancy cost of each cell — what it costs to stand there. It does not decide which cell a company occupies. That correspondence is the subject of the sister paper (No.11, the Enterprise Value Model).

One more point. A reviewer in the paper's pre-publication review recommended adding a fourth model (disciplinary / institution-supplying). The paper declined: there, the source of value is not a relationship to a general-purpose input but the constraint placed on other actors' behavior, which this grid cannot measure as a quantity. The paper treats it as a theoretical exclusion and leaves the extension to future work.

The nine cells are not a classification. They are a field of transition

The grid is built. From here, the paper describes nations moving on it. The most practically useful part of the description is that the grid is not a static classification table.

• Upward transition (toward resource, toward the frontier) requires accumulation. The time constant is years.

• Downward transition happens passively, through relative depreciation of what has been accumulated. Nothing has to be lost. Others accumulate, and that is enough.

A nation that does nothing descends.

In plain terms — Falling does not require a failure. Standing still is enough.

This is not pessimism. It follows from the asymmetry between going up and going down: up requires active accumulation, down requires nothing.

Having is not being strong — position and leverage

Now the paper leaves the grid and turns to leverage. A position on the nine cells says where value is created. How much that position acts on others is a separate variable. Here the paper draws a strict line through three things that everyday language collapses into "dependence."

TermWhose question it isIn everyday words

IndispensabilityA third party's"Can they go elsewhere?"

Lock-inAn existing counterparty's"Can they switch?"

DesirabilityThe counterparty's behavior"Are they still chosen anyway?"

Collapse the three into "dependence" and the judgment is lost. Being impossible to route around (indispensability), being impossible to switch away from (lock-in), and being chosen anyway (desirability) are entirely different states.

When the paper's English edition was produced, this collapse into "dependence" was treated as the single greatest risk, and a rule separating the terms was fixed before translation began.

There is also an asymmetry of sign: indispensability diminishes when exercised; desirability grows the more it is used. The sister paper (No.11, the Enterprise Value Model) takes this up at the level of the firm.

The AI Foundry Model

One of the national types the paper names is the AI Foundry Model: not the position that defines frontier capability itself, but the position that takes on and supplies the capability others ask for.

The paper always writes "AI Foundry Model" or "AI Foundry State," never the bare term, because a commercial product of the same name exists.

The paper also gives a separate section to the cost of sovereignty — which level of sovereignty is bought, and at what price. Sovereignty, on this view, is not a yes-or-no state but a priced choice.

The AI outage — unlike a power outage, it stops across borders at once

The next device is the AI outage, the paper's coinage for a correlated halt in AI supply — "power outage" carried over to AI.

The paper formalizes it as the product of dependence × supplier concentration × failure correlation: heavy use, a skewed set of suppliers, and suppliers that fail together for the same reason. The more the three overlap, the larger the outage.

The decisive difference from a power outage is that supplier concentration is global. So an AI outage occurs across borders and sectors at the same time. And unlike oil, AI capability cannot be stockpiled.

Exposure and dependence are different things

Here the paper separates two quantities that are often confused.

• Exposure — how much is being used. Digital-services balance-of-payments figures measure this.

• Dependence — how much degradation occurs when supply is interrupted

Dependence is neither a usage rate nor a spending figure. It is defined by degradation on interruption. High usage with substitutes means low dependence; low usage with no substitute means high dependence. Much policy debate measures exposure and argues about dependence.

What "selective sovereignty" actually guarantees

"Should we hold frontier-class capability ourselves?" stalls at the cost wall. The paper resolves it by changing what is guaranteed — not a level of capability but three functions:

1. Execution capacity — being able to keep running

2. Update capability — being able to keep updating

3. Conditions for sensitive processing — being able to process sensitive material somewhere that meets the required conditions

With that substitution, the contradiction "we cannot hold the frontier, but we need sovereignty" dissolves.

The critical tier (C3), and what the nuclear regime does not teach

From here the paper turns to critical-tier governance: governance design for the case in which C3 arrives.

If C3 arrives, dedicated governance is required. The usual reference for that design is the nuclear non-proliferation regime. But induction from a sample of one is dangerous: it draws a general law from a single case that happened to work.

So the paper widens the comparison to five regimes: nuclear weapons, the Chemical Weapons Convention (CWC), the Biological Weapons Convention (BWC), the Missile Technology Control Regime (MTCR), and the norms of cyberspace.

The best contrasting case is the BWC. Like the nuclear case it carries an existential externality, and a treaty was concluded. Even so, its verification protocol collapsed in July 2001, and to this day it has no verification mechanism. "It is existential, so a verification mechanism must be achievable" does not hold. The BWC is the counter-example.

AI adds a difficulty of its own: the half-life of the verification anchor. A "verification anchor" is the fixed line a regulation drives in as its reference — "above this amount of compute, regulation applies."

The compute needed to reach a given capability falls with a short half-life (roughly three months, on the paper's evidence). A fixed compute-based threshold therefore loses its force within a few years.

The very line one tries to freeze moves downward every year. In this respect, freezing AI is fundamentally harder than the nuclear case.

In plain terms — The anchor drifts away on its own. The line is valid the day it is drawn; left there, it means nothing a few years later.

Three futures, and the investments you will not regret in any of them

Now the scenario device. The paper does not forecast. It deliberately declines to say which scenario is more probable, and instead hands over instruments for telling which one is under way.

ScenarioWhat happensOperating cells

S1 Fragmentation (base case)Compute dependence, supply concentration, cross-axis transition, and power limits dominate6 → expands to 9 (C3 arrives)

S2 DiffusionOpen-weight and edge execution meet the requirements of use; the distinction between capability tiers disappears6 → contracts to 3 (the C1 row only)

S3 StagnationDiminishing returns; AI capability levels offstays at 6 (C3 does not arrive)

Leading indicators are defined as well. For S2: narrowing of the lag width; diffusion of edge inference chips. For S1: wider use of access-control measures; longer grid-connection queues. For S3: smaller gains between generations; worse returns on frontier investment. They are the gauge for reading which future is under way.

No-regret actions — positive value whichever of the three arrives

A no-regret action is an investment that never becomes "we should not have done that," in any of the three futures.

Proposition 20 | Existence of no-regret actions The following four have positive marginal value in all three scenarios. National brain capital / exclusive domain data / value-definition capability / operational readiness

In plain terms — These four are not wasted however the future turns out. So they can start now, before the future can be called.

By contrast, owning frontier-class compute infrastructure oneself is scenario-dependent: high value under S1, over-investment under S2, a stranded asset under S3.

A practical implication follows. While the scenarios cannot yet be told apart, investment priorities should be set by robustness, not by expected value. Not betting on which future arrives, but placing first what works in every one.

This conclusion also serves as a robustness check, by an entirely different method, on the foundation the paper derives theoretically elsewhere (national brain capital and value-definition capability). Two routes, one destination.

National brain capital — AI capability can be imported. This cannot

The first of the no-regret actions was national brain capital: the judgment capacity accumulated in a country on the side of people and institutions.

• tacit knowledge built up on the ground

• judgment embedded in language and culture

• trust in institutions

• long domain experience

What supports the defensibility of the Transformation Model (M2)? This is the paper's answer.

AI capability can be imported. National brain capital cannot. On that single point, the human-foundation arguments the series makes at the firm level (Brain Capital Management, Ageless Management) join national strategy in one theory.

Layer 0 — what national structure hands down to the layers below

With this paper, VURA's theoretical architecture expanded from three layers to four.

[Layer 0: National structure (geo)] National Value Model (this paper) [Layer 1: Structure of the era (macro)] Redefinition Capitalism [Layer 2: Social structure (meso)] Self-Defined Society [Layer 3: Enterprise management (micro)] Future Value Theory, Enterprise Redefinition and others

Layer 0 hands down the operating conditions of the three layers below. The boundary of the strategies a firm can choose is, in part, set by the outer layer — national structure and institutions. The paper makes that pathway explicit.

The placement is architectural, not a claim of logical dependence — not "once the nation is decided, the firm is decided."

A general theory, not a thesis about Japan

The paper treats Japan as a one-section case study, but it is not a thesis about Japan. The three constraints middle powers share — energy, data sovereignty, and the capacity to define value — operate independently of region, income level, and political system. Japan was chosen as "the application for which the author has access to the most detailed primary sources." As that application, the paper makes these re-readings:

• It separates the correspondences and non-correspondences between the Shōwa-era processing trade (crude oil → heavy chemicals and automobiles) and a Reiwa-era processing trade (general-purpose foundation models → domain-specific AI)

• What gets compressed is the transformation margin that reduces to general-purpose functions, not the transformation margin protected by integration cost

• Domestic players' convergence on "lightweight, compute-thrifty, on-premises, confidential" is consistent if read as investment in the three functions above. A one-to-two-order-of-magnitude gap in compute can be read as design, not defect

• As a policy yardstick it proposes "domestic value added per yen of digital procurement" — a mapping of energy intensity

All of this is written in conditionals. Not "this should be done," but "if efficiency is the aim / if a defensive wall is the aim, the comparison comes out like this."

What the paper admits it cannot yet show

The paper gives objections and limitations a section of their own and lists forty-seven limitations. The principal ones:

• No measurement framework — many of the concepts it proposes have no standardized way of being measured yet

• No opportunity for falsification, and thin evidence — C3 has not been realized, so that part remains an "if it arrives" supposition

• Leading indicators not back-tested — the gauge above has not been tested against historical data. The paper names this as its largest hole

• No probabilities assigned to the scenarios — the paper openly acknowledges the burden this restraint places on practice

• Design not reached — its institutional proposals are not completed designs

Conflict of interest, stated

This is a practitioner's argument. The implication that "middle powers have room to move toward the frontier side of the Transformation Model" coincides with the author's field of business, and the coincidence is not accidental.

The paper does not hide it. The author names six specific places the reader should doubt — overstating the promise of the Transformation Model; understating the option of committing fully to the Utilization Model; the recommended no-regret actions pointing in a direction favorable to the author's business; and others.

The question to ask is not the purity of the motive, but whether the claim can be verified independently of the motive.

In plain terms — Do not judge by whether the writer stands to gain. Judge by whether what is written can be checked without reference to the writer.

On that basis the paper positions its claims as "recommendations that are at the same time hypotheses the author undertakes to test," and states in advance what it retracts if they are refuted.

Implications

For executives. For the AI capability your company relies on, are you measuring dependence rather than exposure — degradation on interruption? If not, the size of the risk is unknown.

For investors. Separate which scenario a holding's defensive wall works in. Frontier-class compute infrastructure has high value under S1 and is a stranded asset under S3.

For policymakers. A measure designed for efficiency puts resources where the value of efficiency falls toward zero fastest. What should be guaranteed is not a level of capability but three functions: execution capacity, update capability, and the conditions for sensitive processing.