When Adopting AI, Are You Also Looking at National Policies and Strategies?
From practice to theory—and back to the business. VURA Capital’s approach
Where should we source AI? Which business processes should use it? How should we measure the results?
These questions often come up when companies introduce AI. We would like to add one more:
“Will this choice remain viable if national policies or international relationships change?”
That may sound like a broad question. Yet once we consider who supplies the AI, where data is stored, and which markets a service will reach, the connection between business decisions and national developments becomes clear.
At VURA Capital, we have been exploring this connection through management practice and developing our thinking in books and working papers. On September 8, 2026, we published a press release introducing our expanded hands-on management activities, incorporating these insights and compensation linked to outcomes.
This article shares the questions behind that work and explains how we move from practice to theory, then bring what we learn back into practice.
Looking beyond the immediate task of AI adoption
Discussions about AI adoption often focus on model performance, subscription costs, and operational efficiency. All of these matter. From a management perspective, we believe it is also necessary to examine the conditions that make continued use possible.
Imagine launching a new business with an overseas AI service at its core.
The business plan assumes that the service will remain available. It also assumes that the company can process customer data, secure the computing resources it needs, and operate in its intended markets.
What happens if those conditions change? Could the business move to a different platform? Could it continue serving customers? How much additional cost and delay could it absorb?
This is where geoeconomics—the connections among economic activity, security, and international politics—becomes relevant. Understanding which countries’ technologies, institutions, and supply structures support a business helps clarify the assumptions behind its decisions.
Companies do not need to track every development in every country. A useful starting point is to identify what the business depends on and what would happen if those conditions changed. Even that exercise can change how an AI investment is assessed.
Starting with questions from practice
Our research begins with questions that arise in running businesses and building new ventures.
If competitors can use the same AI, where will our advantage lie? What should we build within the company while drawing on external technology? After launching a new service, how do we develop an organization that can keep creating value?
In practice, these questions must be addressed with limited information and time. Even when a decision works well, it may not immediately be clear why it worked—or whether it would work in another company.
We therefore put experience into words and examine the assumptions and causal relationships behind it. We organize these ideas in books and explore them further in working papers. By comparing our thinking with research from around the world, we look for connections with existing knowledge, perspectives that may be distinctive to our work, and areas we still cannot adequately explain.
We want to avoid treating our own experience as a universal answer. Experience gives us a starting point, while alternative explanations and counterexamples help us refine our thinking. Through this process, we aim to develop ideas that can inform the next management decision.
From the AI Foundry Model to national value models
One starting point for this research was the AI Foundry Model.
As VURA Capital uses the term, this model explores the value of combining externally sourced frontier AI with industry knowledge and mechanisms that support trust, then delivering the combination as a system that can operate in practice.
Consider AI in manufacturing. Alongside model performance, implementation requires an understanding of equipment, quality standards, decisions when exceptions arise, and responsibilities on the shop floor. These elements must work together for AI to become useful in daily operations.
Healthcare, finance, and logistics likewise require knowledge and operating conditions specific to each field. This raises a question: could the process of turning AI into practical value itself be a source of accumulated capabilities and business opportunities?
Extending this perspective from companies to countries brings further questions into view.
How can countries outside those leading frontier AI development create value? How can they combine AI with their existing industrial knowledge, people, institutions, and trust? How can they build their own strengths while using technology sourced from elsewhere?
These questions led us from the AI Foundry Model to national value models: a framework for considering how nations create value in the age of AI.
Understanding national positions and business choices
Our national value framework looks at producing AI, transforming it into products and services, and using it across industry and society.
We combine these positions with tiers of AI capability to organize the framework into nine national value cells. It is a research framework that also includes capability domains considered as future possibilities.
The purpose is to make it easier to examine where countries create value, what they depend on externally, and what relationships they build. It should not be read as a ranking of national power.
We also avoid assigning each country to a single fixed position. Countries contain diverse industries and companies, with primary positions and others that complement them.
For businesses, the question is how to incorporate the foundations and constraints of their home country and partner countries into strategy. Where should they operate? Where should they source technology? With whom should they partner? Understanding national structures can inform these concrete choices.
A country’s characteristics alone, however, do not determine an individual company’s competitiveness. Businesses in the same country have different customers, technologies, supply chains, and accumulated capabilities. To examine these differences, we brought our research back to the enterprise level.
From national value models to enterprise value models
Our enterprise value framework connects a company’s position in value creation with its customer and supplier relationships, internal capabilities, and resource allocation.
For example, offering an excellent AI service does not, by itself, establish a company’s future earning power. Can customers easily switch to another provider? Does the company depend on external parties for critical technology or distribution? Does greater use of the service help the company accumulate knowledge and trust? These differences require closer examination.
One concept we emphasize here is Enterprise Brain Capital. We use this term for company-specific knowledge, judgment, and capacity for collaboration: internal capabilities that are difficult to reproduce quickly through external purchases alone.
These include the ability to understand what customers are truly struggling with; to make decisions that account for quality and safety in unusual situations; to turn cooperation across departments into execution; and to retain experience with AI so the organization can apply it to future work.
How can these capabilities be developed together with AI? We see this as an important question for value creation beyond initial adoption.
In our research, we used publicly available information on 31 major companies worldwide to examine the framework’s applicability and limitations. We are looking for ways to explain differences among companies while remaining mindful of what public information can and cannot reveal.
Comparing our thinking with research around the world
As we develop ideas from practice into research, comparison with existing papers and other research is an important part of the process.
What has already been explained? Which discussions does our thinking connect with? Do the differences lie in terminology, in the subject being studied, or in how relationships are understood?
Working through these questions helps us articulate our own perspective more precisely. We do not believe that originality comes simply from giving something a new name.
In this work, we are exploring the connections between the conditions nations create for enterprises and companies’ value creation, bargaining power, internal capabilities, and investment decisions. Moving between national structures and business questions can bring relationships into view that deserve closer attention.
Every theory also has limits to its applicability. A single framework cannot fully explain every company. Publishing ideas while they are still developing—and revising them through discussion and examination—is part of our approach.
We make the VURA Working Paper Series openly accessible to support that process.
Bringing theory back to the next management decision
Once we have organized our thinking, we return to the business.
Which opportunities should we pursue? What should we keep in-house, and where should we work with partners? Whom should we recruit, and which capabilities should we develop? Where should we commit limited capital and time?
For example, discovering a heavy dependence on one AI platform does not necessarily mean a company should immediately build everything internally. It can compare several responses: retaining data and operational knowledge within the business, examining the feasibility of moving to another platform, or investing in stages.
We also seek to avoid building a business plan around a single prediction about AI’s future. We consider scenarios in which access broadens, fragmentation and access restrictions increase, or capability improvements slow. This helps distinguish actions that make sense across several scenarios from those that should proceed as conditions become clearer.
Theory can clarify the questions a decision requires and make assumptions and options easier to compare. Examining what happens after implementation then allows us to revisit both the decision and the theory.
Participating in management and sharing risks and outcomes
VURA Capital applies these insights through hands-on participation in management, working alongside leadership teams to launch and operate businesses.
We agree on roles, authority, and scope according to each company’s needs. Within those responsibilities, we take part in execution across areas such as organizational development, new service development, partnerships, sales, and delivery.
Depending on the engagement, we incorporate compensation linked to profit creation or agreed outcomes, connecting our remuneration to the results of the business. Performance measures, the scope of risk and responsibility, and compensation terms are designed individually.
Making decisions and taking action in the business generates new questions. We organize those questions, explore them through research, and apply what we learn in the next engagement. Continuing this cycle is central to our work.
We have also brought these insights together in the three-volume National Value Models in the Age of AI series and the four-volume Enterprise Value Models in the Age of AI series. Both are available in Japanese and English: seven volumes in each language, comprising 14 books in total.
When introducing AI into a company, it is worth taking a wider view of national policies and strategies—and then bringing that perspective back to decisions about customers, organizations, and businesses.
VURA Capital will continue moving between practice and research as we work to build enterprises that keep creating future value.
You can read more about these initiatives in our press release below.
Books and publicationsVURA Working Paper SeriesContact us about management participation and business partnerships
Press release as below.
VURA Capital Expands Outcome-Based Management Participation to Address Geoeconomic Risks and Enterprise Transformation in the Age of AI
Supporting enterprise transformation amid geopolitical fragmentation and rapid advances in AI. Drawing on a seven-volume book series and research papers integrating academic and management insights, VURA Capital strengthens Japanese companies’ capacity to keep creating future value through a risk-sharing, success-based model.
September 8, 2026, 8:00 a.m. JST
Applying insights from geoeconomics and AI to hands-on managementVURA Capital works with management teams to make decisions on business transformation, organizational change, and resource allocation in light of cross-border regulations and changes in supply chains, taking responsibility for execution within agreed areas.
Completing a seven-volume series on national and enterprise value models in Japanese and EnglishFollowing the three-volume National Value Models in the Age of AI series, the four-volume Enterprise Value Models in the Age of AI series was published on September 7, 2026. The complete series comprises seven volumes in each language, totaling 14 books.
Launching the VURA Working Paper Series to share research findingsThe open-access series was launched in July 2026 (ISSN 2761-011X; advance notification received, formal registration in progress). It develops questions arising from practice into research and brings those insights back into enterprise management.
VURA Capital Innovation Holdings Inc. (headquartered in Minato-ku, Tokyo; President and CEO: Naoki Kadowaki; hereafter “VURA Capital”) announced on September 8, 2026, the expansion of its hands-on management participation incorporating outcome-linked compensation to address geoeconomic risks and enterprise transformation in the age of AI. Depending on the engagement, compensation is linked to profit creation or agreed outcomes, with VURA Capital working alongside management teams to launch and operate businesses.
Drawing on insights gained through its management engagements and its proprietary National and Enterprise Value Models, VURA Capital translates cross-border regulatory conditions and dependencies on technology infrastructure into concrete decisions on business opportunities, in-house development, partnerships, and investment allocation. Within agreed roles and authority, it takes responsibility for execution across organizational development, new service development, alliances, sales, and delivery.
VURA Capital has also published the four-volume Enterprise Value Models in the Age of AI series. Together with the preceding three-volume National Value Models in the Age of AI series, this completes a seven-volume series available in Japanese and English—seven volumes per language, totaling 14 books.
In July 2026, VURA Capital launched the VURA Working Paper Series to share research findings (ISSN 2761-011X; advance notification received, formal registration in progress). Questions arising from management and investment practice are developed systematically through books and papers, with the resulting insights brought back into enterprise management.
Comment from the President and CEO
“Alongside adopting AI, companies must consider what businesses they will build with it. When competitors can use the same AI, how should a company combine its customer base, operational knowledge, and organizational judgment? At the same time, how do cross-border regulations and supply structures shape those choices? Management decisions need to account for both.
“Amid structural changes driven by cross-border regulations and rapid advances in AI, companies need a partner who is in the same boat, sharing outcomes and risks on the ground. By participating directly in management and linking our compensation to results, we connect theory and practice in a continuing cycle and drive the transformation that enables companies to keep creating future value.”
Naoki Kadowaki, President and CEO
What Should Companies Change When National Conditions Shift?
Where should a company source AI? Where should it store data? In which markets should it operate? What should it accumulate internally, and where should it work with external partners?
These decisions involve international relationships, export controls, data regulations, and semiconductor and cloud supply structures, alongside technological performance and cost. Geoeconomics—the intersection of economics, security, and international politics—is becoming a necessary perspective in enterprise management.
When competing companies can access similar AI, another question arises: how can a company combine its customer base, operational knowledge, and organizational judgment to create business value?
VURA Capital translates an understanding of these external conditions into concrete decisions about businesses, organizations, and capital. By participating in management across business, technology, and capital, it works to build enterprises that continue creating future value as conditions change.
Areas of Management Participation
1. Set Business Direction and Take Responsibility for Launches and Transformation
VURA Capital works with management teams to define which markets to serve, which customers to address, and what value to provide, taking account of national and regional regulations and dependencies on technology infrastructure.
It develops business plans and execution structures for reviewing existing businesses, launching new ventures, and developing AI-enabled services. Within agreed areas of responsibility, it advances organizational development, new service development, alliances, sales, and delivery.
As businesses progress, VURA Capital reviews offerings and operating structures based on customer responses and profitability.
2. Combine AI with Company-Specific Strengths and Embed Them in the Business
Creating value with AI requires the combination of operational knowledge, customer relationships, data, decision-making mechanisms, and collaboration across departments.
VURA Capital uses the term Enterprise Brain Capital to describe company-specific knowledge, judgment, and collaborative capabilities that are difficult to reproduce quickly through external purchases alone.
Through management participation, VURA Capital redesigns responsibilities, decision-making, staffing, and ways of working to develop and apply these strengths within the business. It connects management with operations, translating AI use into greater customer value and stronger organizational capabilities.
3. Make Investment and Resource Allocation Decisions, Then Reassess Through Execution
Investment in AI infrastructure, in-house development, external partnerships, supplier diversification, and recruitment and training each require time and money.
VURA Capital considers multiple business environments to distinguish actions that remain worthwhile across scenarios from those best pursued in stages as conditions become clearer. It works with management teams to set priorities and define budgets, staffing, and responsibility for execution.
After implementation, decisions to continue, expand, or modify initiatives are based on business progress and changes in the external environment. By moving between planning and execution, VURA Capital seeks to combine future value creation with capital efficiency.
Engagement Model: Taking Responsibility and Sharing Risks and Outcomes
Roles, authority, and scope of involvement are tailored to each company’s management challenges and stage of development.
Ongoing participation in the management teamIn addition to contributing to management discussions and decisions, VURA Capital takes responsibility for agreed areas, including business and organizational oversight.
Execution of new ventures and enterprise transformationActivities include launching new companies and businesses, transforming existing operations, applying AI, and redesigning organizations and business processes.
Risk-sharing, success-based modelDepending on the engagement, compensation linked to profit creation or agreed outcomes is incorporated to align VURA Capital’s remuneration with business results. Performance indicators, the scope of risk and responsibility, and compensation terms are agreed individually.
The primary focus is on companies pursuing business transformation in the age of AI, creating new growth businesses, or reviewing overseas operations and supply chains. Target companies include large and mid-sized enterprises with annual revenue of approximately JPY 5 billion to JPY 100 billion, including manufacturing, IT, and service businesses with global supply chains or overseas operations.
This initiative integrates research insights on national structures and value creation in the age of AI into hands-on management, applying them to business choices and execution.
National and Enterprise Value Models as a Foundation for Management Decisions
Producing AI, Transforming It into Value, and Applying It Across Society
VURA Capital’s National Value Model organizes AI capability into three tiers—Commodity, Frontier, and Critical—and positions in value creation into three types—Production, Transformation, and Utilization. Combining these dimensions produces the nine national value cells.
The framework examines the structure of value creation by considering the production of AI itself, its transformation into products and services, and its utilization across industry and society.
Figure 1 | Basic Structure of the National Value Model in the Age of AI
The vertical axis shows tiers of AI capability; the horizontal axis shows positions in value creation. The Critical tier (C3) is a capability domain considered in this research as a future possibility requiring dedicated governance. It is treated as a category that has not yet been realized.
Reading Business Conditions Through the Positions of Countries and Regions
A country’s position in value creation affects companies’ technology sourcing, business expansion, and choice of partners.
The research distinguishes primary and secondary positions rather than fixing each country or region in a single cell. For example, Japan is characterized as having a primary position in the utilization of widely available AI, while also participating in its transformation into products and services.
Figure 2 | Primary and Secondary Positions of Countries and Regions
This is the research framework’s assessment as of 2026. It represents countries’ and regions’ positions in value creation, not a ranking of national power or the position of every company within each country.
Building on these national conditions, the enterprise framework analyzes individual companies’ positions in value creation, bargaining power with customers and business partners, and internally accumulated capabilities. These insights are assessed against each company’s business, customers, supply chains, and technology infrastructure to inform management decisions.
Identifying Actions to Take Now Through Three Future Scenarios
The research considers three scenarios for AI’s future: Diffusion, Fragmentation, and Stagnation.
The areas where value remains and the investments required may differ depending on whether access to AI capabilities broadens, fragmentation and access restrictions intensify across countries, or improvements in capability slow.
Figure 3 | Three Future Scenarios and Changes in the Structure of Value Creation
The research describes the current situation, in which C3 has not been realized, as a six-cell structure. It examines the possibility that Diffusion compresses differences between capability tiers and consolidates the structure into three cells; that Fragmentation expands it to nine cells when accompanied by the realization of C3; and that Stagnation leaves C3 unrealized, maintaining six cells. Fragmentation is the reference case in this research, and the cell counts represent structures within the model.
In management engagements, VURA Capital identifies the businesses and investments affected by each scenario while specifying actions that remain meaningful across multiple assumptions. These include accumulating knowledge, developing proprietary data, strengthening the ability to define customer value, and improving execution capacity.
This approach to No-Regret Actions is applied according to each company’s circumstances. The common actions shown in the figure are based on research assumptions and do not guarantee investment outcomes under all conditions.
Analyzing Public Information on Major Global Companies from a Management Perspective
Related research analyzes publicly available information, including Japanese securities reports and U.S. Form 10-K filings, for 31 major global companies, including leading technology companies and advanced manufacturers.
It distinguishes the domains in which companies operate from the bargaining power they actually hold, while clarifying the scope of what can be established from public information and the limitations of the framework.
In management engagements, these research insights are assessed against each company’s business and organizational circumstances and used to inform business development, organizational capability building, and resource allocation.
The companies are subjects of public-information-based analysis. Their inclusion does not indicate management engagements or partnerships.
Related Publications: Completion of the Seven-Volume Series in Japanese and English
The series systematically examines value creation in the age of AI from two perspectives: nations and enterprises. The three national-model volumes were published on August 25, 2026, followed by the four enterprise-model volumes on September 7, 2026.
National Value Models in the Age of AI — Three Volumes
Volume 1: What Determines a Nation’s Value in the Age of AI?
Introduces the nine national value cells through three tiers of AI capability and three types of value creation: Production, Transformation, and Utilization.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Volume 2: Are Nations with AI Truly Strong?
Examines the distinction between a nation’s position in AI and its bargaining power in relation to other countries.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Volume 3: When AI Becomes Available to Everyone, What Will Still Set Nations Apart?
Explores sources of value, including National Brain Capital, that remain after AI becomes widely accessible.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Enterprise Value Models in the Age of AI — Four Volumes
Volume I: Are Companies with AI Truly Strong? National Structures as Given Conditions, and the Nine Cells
Presents a framework for understanding how national structures condition enterprise choices and for identifying a company’s own position.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Volume II: Power That Diminishes When Exercised, Power That Grows Through Use: Chokepoints, Trust Infrastructure, and the Portability Dilemma
Distinguishes indispensability from necessity and analyzes how corporate bargaining power forms and changes.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Volume III: What Cannot Be Replaced by AI? Enterprise Brain Capital and No-Regret Investment
Examines internal assets that are difficult to reproduce quickly and resource allocation under multiple scenarios.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Volume IV: Where Do the 31 Companies Stand? The Interlocking of Four Layers, and the Limits of This Framework
Applies the framework to public information on 31 companies, examining relationships among nations, the era, society, and enterprises, as well as the limits of the analysis.
Japanese edition: Amazon / Google Books
English edition: Amazon / Google Books
Publication Information
Author: Naoki Kadowaki
Languages: Japanese and English; seven volumes in each language, totaling 14 books
Formats: E-book and paperback
E-book publisher: VURA Capital Innovation Holdings
Series details and purchase links: VURA Capital Books and Publications
Launch of the VURA Working Paper Series to Share Research Findings
VURA Capital launched the VURA Working Paper Series in July 2026 to share questions and research findings arising from management and investment practice (ISSN 2761-011X).
The series provides open access to working papers on enterprise value, management in the age of AI, and relationships among nations, society, and enterprises. It aims to share developing ideas widely, refine them through discussion and examination, and bring the resulting insights back into management practice.
Series title: VURA Working Paper Series
ISSN: 2761-011X
Publisher: VURA Capital Innovation Holdings Inc.
Place of publication: Minato-ku, Tokyo, Japan
Launched: July 2026, with No. 1
Frequency: Irregular; at least once a year
Publication format: Online
Access: Open access
Full list: VURA Working Paper Series
A Research Framework Connecting Nations, the Era, Society, and Enterprises
VURA Capital organizes its research framework into four layers: national structures, the structure of the era, social structures, and enterprise management. The framework connects corporate management decisions with changes in the institutions and society surrounding them.
Figure 4 | A Four-Layer Structure Connecting Nations, the Era, Society, and Enterprises
Layer 0 | National Structures and Geoeconomic Boundaries: Conditions that national resources, technology infrastructure, institutions, and rules impose on enterprise choices.
Layer 1 | Structure of the Era: Examination of value creation and economic structures in the age of AI through Redefinition Capitalism.
Layer 2 | Social Structures: Examination of value and roles for individuals, organizations, and society through Self-Defined Society.
Layer 3 | Enterprise Management: Examination of management through Future Value Theory, Enterprise Redefinition, Enterprise Brain Capital, Human-on-the-Loop, and related concepts.
Related Working Papers
National Value Models in the Age of AI
This paper examines how nations create value and build relationships with other countries in the age of AI, focusing on nations outside the two poles leading frontier AI development.
It presents the nine national value cells and distinguishes national position from bargaining power. It proposes the AI Foundry Model, which combines externally sourced frontier AI with industry-specific knowledge, National Brain Capital, and trust infrastructure to deliver integrated systems that can operate in practice.
Paper title: National Value Models: A Theory of Resource, Transformation, and Utilization for Nations in the Age of AI, with Critical-Tier Governance
Publication date: August 24, 2026
SSRN: View the paper
From National Value Models to Enterprise Value Models
This paper examines individual companies’ competitiveness and resource allocation in light of the conditions that national structures create for enterprises.
It distinguishes companies’ positions in value creation from their bargaining power and sets out an approach to investments and initiatives informed by Enterprise Brain Capital and multiple scenarios. Using public information on 31 major global companies, it examines the applicability and limitations of the framework.
Paper title: From National Value Models to Enterprise Value Models: Chokepoints, Trust Infrastructure, and Corporate Leverage Strategy under the Geoeconomic Scenarios of the AI Era
Publication date: September 2, 2026
SSRN: View the paper
About VURA Capital
VURA Capital is a Japan-based investment, management, and value creation platform that puts Enterprise Redefinition into practice in the age of AI.
With a mission to “increase the number of enterprises that continue creating future value,” VURA Capital invests in companies and participates in management to redesign businesses, organizations, and capital structures—and carry those changes through to execution.
Its work begins with questions arising from the practice of enterprise management and transformation. Insights from practice are organized in books and examined through working papers and company case studies. The resulting knowledge is then brought back into management and investment practice.
From practice to theory. From theory, back to practice.
This initiative connects that cycle with business building and value creation.
Comments