OpenAI、知能時代の産業政策に基づき14プロジェクトに助成金交付

OpenAI is awarding grants to 14 projects led by independent organizations to promote economic opportunity and societal resilience as AI advances. The grants follow through on a commitment we made when we published Industrial Policy for the Intelligence Age in April 2026: to support others in testing, challenging, and building on the ideas we put forward to ensure that advanced AI benefits everyone.

AI is quickly becoming more capable, with the potential to transform how people learn, create, and participate in the economy. Its reach is also expanding: ChatGPT is used by 1 billion people around the world, across geographies, income levels, and demographic groups. Users span every major age group; we have more adult users both under and over the age of 30 than any other frontier lab.

But broad access to the technology is only part of the equation. Whether AI ultimately serves the many rather than the few will also depend on the choices societies make about how to deploy it and distribute its benefits. If the benefits of the Intelligence Age are going to be broadly shared, the policy response needs to be as ambitious as the technological change itself—and that means calling for new approaches rather than adjustments to existing policy.

These choices should not be made by technology companies alone. In democratic societies, they should be shaped through democratic institutions and public debate. Independent research and policy organizations play an especially important role: they can develop and test new approaches, challenge assumptions—including ours—and serve as laboratories for ideas that governments can adapt to their own communities and circumstances.

Through these new grants, researchers and practitioners will turn high-level ideas into concrete work, examining what could work, what it might cost, and how approaches could be implemented responsibly. More than 400 people and organizations responded to our call for proposals. Applicants identified an idea and proposed projects that could meaningfully contribute to public understanding and policy development. OpenAI will provide a total of $1 million in funding and up to $1 million in API credits across the selected projects.

The projects span the United States, the European Union, Brazil, Singapore, and South Korea and address two broad questions: how AI can broaden economic opportunity, and how societies can build resilience as capabilities advance. Some will produce research and policy models, while others will build prototypes, datasets, and frameworks that can be tested in practice. Summaries of the selected projects are included below.

Building a more open economy

American Enterprise Institute: AEI-Urban Bipartisan Commission on Artificial Intelligence and the Future of the American Workforce. The AEI-Urban bipartisan commission will develop low-, moderate-, and high-disruption scenarios for AI’s effects on employment and skills and connect observable indicators of disruption to policy playbooks.

Centre for European Policy Studies—Sharing the AI Dividend. CEPS will examine how AI-driven productivity gains are distributed across workers, firms, sectors, regions, and countries in Europe, benchmarking the EU against the United States. Building on a synthesis of existing empirical evidence, the project will develop innovative policy principles for a renewed European social investment model and adaptive safety nets to ensure that AI-driven prosperity is broadly shared. The project will deliver a policy study, visualisations, and a stakeholder validation workshop.

European Centre for International Political Economy: From Labour to Productive Ownership. ECIPE will examine how broader access to AI and ownership of productive assets could help people participate economically as technology becomes more capable. The project will develop a practical framework for a “Right to AI” and compare models including employee ownership, citizen investment, pension-based ownership, social wealth funds, and intellectual-property participation. It will produce a final report, shorter insights, and a public webinar.

Abundance Institute: Energy Abundance, State by State. Abundance Institute will compare how US states can expand generation and transmission in response to data center demand while producing measurable local benefits. It will develop a state policy framework, historical analysis, and a public Data Center Atlas policy layer.

Progressive Policy Institute: Person-based Benefits in the Age of Information. PPI will design a person-based benefits system covering retirement, health, leave, education, training, and disability across different forms of work. It will prototype “livelihood insurance” triggered by broad changes in an occupation, then identify the legislative and technical changes required to implement the model.

Tax Foundation: Tax Policy in the Age of AI. Tax Foundation will analyze how AI adoption could change the balance among labor income, corporate profits, capital gains, and other sources of public revenue. A final white paper with supporting quantitative analysis will assess taxation options against neutrality, simplicity, transparency, stability, and economic efficiency, explicitly considering innovation, adoption, competition, competitiveness, and fiscal resilience.

Windfall Trust: National working groups for AI economic policy. Windfall Trust will scale a network of working groups in the United States, United Kingdom, Canada, European Union, and Latin America to examine fiscal, labor-market, welfare, and competitiveness questions under different AI scenarios. It will also launch an International Working Group focused entirely on international economic preparedness and coordination. The working groups will connect economists, policy experts, pollsters, and regional partners, and Windfall Trust will produce public syntheses of the main working groups’ takeaways.

Instituto de Matemática Pura e Aplicada: Building Resilient Research in the Intelligence Age. IMPA will study what research institutions need to turn AI access into meaningful scientific progress, including engineering support, training, governance, compute, and local infrastructure. Working with mathematicians in Brazil, it will develop a transferable measurement and cost framework, practical guidance for trustworthy AI use in mathematics, and a public report evaluating the Right to AI and distributed scientific discovery.

Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo: People-First AI Clinical Infrastructure for Public Hospitals. HCFMUSP will conduct a controlled, pre-deployment evaluation of an AI-enabled clinical information infrastructure prototype designed to organize clinical information in Brazil’s Unified Health System, SUS. Using only synthetic or appropriately de-identified data, the project will assess whether people-first clinical AI can reduce fragmented record review, improve clinician workflows, support evidence-based care and risk stratification processes, and help patients navigate health services, manage prescription-renewal workflows, and identify warning symptoms that should be escalated for clinician review, while preserving physician judgment and human oversight.

Building a more resilient society

Institute for Security and Technology: Operational Framework for Uncontrolled RSI—Measurement, Coordination, and Response. IST will establish a measurement and coordination framework for recursively self-improving (RSI) AI systems. This project develops technically grounded definitions, observable indicators of uncontrolled self-modification, incident taxonomies for cross-lab communication, and escalation criteria that map technical signals to coordinated response decisions. Outputs include an incident-classification schema, escalation pathways for industry-government coordination, and a public executive summary.

Nuclear Threat Initiative: Designing Cross-Border Information-Sharing for AIxBio Risk. NTI | bio will test the legal feasibility for secure international sharing of AI capabilities, risks, and mitigations. NTI | bio will then design a basic information-sharing architecture to enhance international AIxBio safety and security.

Council on Strategic Risks: Safer with People—A Frontier AI-Safety Module and Lab Immersion for National Security Professionals. CSR’s Converging Risks Lab will examine how national-security professionals can build institutional capacity in frontier-AI safety and governance. Through fellowship training and engagement with frontier AI labs and safety researchers, the project will produce public-facing analysis on oversight and preserving meaningful human control as AI capabilities advance.

Nanyang Technological University: Privacy-Preserving LLM Agents for Auditable Government Policy Simulation. NTU will develop and evaluate an AI-agent framework that transforms individual-level financial transaction data into privacy-preserving behavioral profiles to simulate how households would respond to government transfers and industrial policies before implementation. The simulations will be validated against observed responses to prior policies and established statistical benchmarks. The project will deliver a prototype, a privacy-preserving profile schema, auditable reports explaining the basis for each prediction and how changes in policy design are expected to alter it, and guardrails for responsible government use.

Yonsei University: AI-enabled democratic accountability. Yonsei University will test whether transparent, human-validated AI methods can help assess the quality of oversight in South Korea’s National Assembly. The initial phase will produce an analytical report, pilot dataset, and codebook examining evidence use, polarization, and the quality of legislative oversight.

What comes next

Projects will run for six months, with results reported in 2027.

In *Industrial Policy for the Intelligence Age,* we argued that governments should be prepared to use the full policy toolbox—from research funding and workforce development to market-shaping tools and targeted regulation—to help societies navigate a technological transition of this scale. But no company or government has all the answers.

The purpose of these grants is to widen the circle of people developing them: supporting independent institutions around the world as they test new ideas, build evidence, and help democratic societies decide how AI can expand opportunity and strengthen resilience. These projects are a beginning, and we hope the results will inform a much broader public debate about the policies the Intelligence Age requires.