A National AI Laboratory to Support the Administration’s AI Agenda at the Department of Commerce
The United States faces intensifying international competition in Artificial Intelligence (AI). The Trump administration’s AI Action Plan places the Department of Commerce at the center of its agenda to strengthen international standards-setting, protect intellectual property, enforce export controls, and ensure the reliability of advanced AI systems. Yet no existing federal institution combines the flexibility, scale, and technical depth needed to fully support these functions.
To deliver on this agenda, Commerce should expand their AI capability by sponsoring a new Federally Funded Research and Development Center (FFRDC), the National AI Laboratory (NAIL). NAIL would:
- Advance the science of AI,
- Ensure that the United States leads in international AI standards and promotes the trusted adoption of U.S. AI products abroad,
- Identify and mitigate AI security risks,
- Protect U.S. technologies through effective export controls.
While the National Institute of Standards and Technology’s (NIST’s) Center for AI Standards and Innovation (CAISI) within Commerce provides a base of expertise to advance these goals, a dedicated FFRDC offers Commerce the scale, flexibility, and talent recruitment necessary to deliver on this broader commercial and strategic agenda. Together with complementary efforts to strengthen CAISI and expand public-private partnerships, NAIL would serve as the backbone of a more capable AI ecosystem within Commerce. By aligning with Commerce’s broader mission, NAIL will give the Administration a powerful tool to advance exports, protect American leadership, and counter foreign competition.
Challenge
AI’s breakneck pace is having a real-world impact. The Trump administration has made clear that widespread adoption of AI, backed by strong export promotion and international standards leadership, is essential for maintaining America’s position as the world’s technology leader. The Department of Commerce sits at the center of this agenda: advancing AI trade, developing international standards, advancing the science of AI, promoting exports, and ensuring effective export controls on critical technology.
Even as companies and countries race to adopt AI, the U.S. lacks the capacity to fully characterize the behavior and risks of AI systems and ensure leadership across the AI stack. This gap has direct consequences for Commerce’s core missions. First, advances in the science of AI are necessary to ensure that AI systems are sufficiently robust and well understood to be widely adopted at home and abroad. Second, without trusted methods for evaluating AI, the U.S. cannot credibly lead the development of international standards, an area where allies are seeking American leadership and where adversaries are pushing their own approaches. Third, this deep understanding of AI models is needed to identify and mitigate security concerns present in both foreign and domestic models. Fourth, deep technical expertise within the federal government is required to properly create and enforce export controls, ensuring that sensitive AI technologies and underlying hardware are not misused abroad. A deep bench of subject matter experts in AI models and infrastructure is increasingly critical to these efforts.
As AI systems become more capable, the lack of predictable and understandable behavior risks further eroding public trust in AI and inhibiting beneficial AI adoption. Jailbreaking attacks, in which carefully crafted prompts get around Large Language Model (LLM) guardrails, can produce unexpected behavior of models. For example, jailbreaking can prime LLMs for use in cyberattacks, which can cause significant economic harms, or cause them to leak personal information, or produce toxic content, causing legal liability and reputational harm to companies using these models. As companies deploy custom models built on top of LLMs they need to know that medical assistants will not produce harmful recommendations, or that agentic AI systems will not misspend personal funds. Addressing these concerns is an extremely challenging technical problem that requires more effective and consistent methods of evaluating and predicting model performance.
The ability to effectively characterize these models is central to the Trump administration’s AI Action Plan, which highlights widespread adoption of AI as a major policy priority, while also recognizing that the government has a key role to play in managing emerging national security threats. The AI Action Plan gives Commerce a central role in addressing these concerns; nearly two fifths of the plan’s recommendations involve Commerce. Commerce’s responsibilities include:
- Creating methods of AI model evaluation and developing international standards.
- Identifying security risks.
- Promoting research on AI interpretability, control and robustness.
- Recruiting leading AI researchers.
- Promoting exports of AI technology.
For a full list of AI Action Plan recommendations involving Commerce, see Appendix A.
While Commerce has an impressive track record in AI, including through its work at the National Institute of Standards and Technology and CAISI, it will face immense institutional challenges in delivering on the ambitions of the AI Action Plan, which require broad and deep expertise. Like other U.S. government entities, Commerce operates under federal hiring rules that make it difficult to quickly recruit and retain top technical talent. The government also struggles to match AI industry pay scales. For example, fresh PhDs joining AI companies frequently receive total compensation that is twice the cap set for the overwhelming majority of government workers, and senior researchers earn five times this cap or more. In some cases, top researchers may also hold equity in private companies, further complicating their employment by the government. Without a new institutional mechanism designed to attract and deploy world-class expertise, Commerce will struggle to execute on the ambitious goals of the AI Action Plan.
Opportunity
To deliver on the scope of the AI Action Plan, the Department of Commerce needs a dedicated institution with the resources, flexibility, and talent pipeline that existing structures cannot provide. A Federally Funded Research and Development Center (FFRDC) offers this capacity. Unlike traditional government offices, an FFRDC can recruit competitively from the same pools as industry, while remaining mission-driven and independent of commercial interests.
At its core, a new FFRDC, the National AI Laboratory (NAIL), would provide the technical expertise Commerce needs to carry out its central responsibilities. Specifically, NAIL would:
- Advance the science of AI, including the measurement and evaluation of AI models.
- Develop the methods and benchmarks that underpin international standards and ensure U.S. companies remain the trusted source for global AI solutions.
- Identify and mitigate AI security risks, ensuring U.S. technologies are not exploited by adversaries.
- Provide the technical expertise needed to support export promotion, export controls, and international trade negotiations.
NAIL would equip Commerce with the authoritative science and engineering base it needs to advance America’s commercial and strategic AI leadership.
FFRDCs are unique in combining the flexibility of private organizations with the mission focus of federal agencies. Their long-term partnership with a sponsoring agency ensures alignment with government priorities, while their independent status allows them to provide objective analysis and rapid technical response. This hybrid structure is particularly well-suited to the fast-moving and security-relevant domain of frontier AI. More background information on FFRDCs can be found in Appendix C.
The current talent landscape underscores the value of the FFRDC model. While industry salaries are high, many senior researchers are constrained by proprietary agendas and limited opportunities to pursue foundational, publishable work. To obtain greater freedom in their research, many top industry researchers have been seeking positions at universities, despite drastically lower salaries. An FFRDC focused on frontier model understanding, interpretability, and security offers a rare combination: freedom to pursue scientifically important problems, the ability to publish, and a mission anchored in national competitiveness and public service. This environment can attract researchers who would not join the civil service but are motivated by high-impact scientific and policy goals.
FFRDCs have repeatedly demonstrated their ability to deliver large-scale technical capability for federal sponsors. For example, NASA’s Jet Propulsion Laboratory has successfully built and landed multiple rovers on Mars, among many other achievements. The Departments of Energy and Defense have led much of the U.S.’ efforts in science and technology assisted by more than two dozen FFRDCs. Their track record shows that FFRDCs are uniquely suited to problems where neither academia nor industry is structured to meet federal needs—exactly the situation Commerce now faces in AI. Commerce currently supports one FFRDC, the fourth smallest. As advanced AI technology grows even more central to Commerce’s mission, it makes sense to add to this capacity.
Plan of Action
Recommendation 1. Establish an FFRDC to support the AI Mission at Commerce.
Commerce should establish a new FFRDC within two years with a mission to begin important research and timely evaluations. Establishing a new FFRDC requires the sponsoring organization (Commerce in this case) to satisfy the criteria laid out in the Federal Acquisition Regulations (48 CFR 35.017-2) for creating a new FFRDC. Key requirements involve demonstrating needs that are not met by existing sources and that Commerce has sufficient expertise to evaluate the FFRDC. It will require consistent government support through appropriations, and Commerce must identify an appropriate organization to manage it. The rapid pace of AI development makes it an urgent priority to move forward as soon as possible. Recent FFRDCs have taken about 18 months to establish after initial announcement, a significant length of time in the AI field. Further details related to establishing an FFRDC can be found in Appendix D.
Recommendation 2. NAIL should focus on topics that will advance the Administration’s AI Agenda, including recommendations given to Commerce in the AI Action Plan.
These topics should include:
- Development of a standardized federal science of measurement that enables evaluation and comparison of models. These evaluations should be predictive of their performance on real-world tasks. NIST has already laid out how measurement science can advance AI innovation in this report.
- Use of these advances in the science of AI measurement for the development of unified AI standards. This would build greater confidence in models, promoting adoption and U.S. AI exports.
- Development of comprehensive methods to assess security implications of models. This includes security concerns in foreign models and vulnerabilities, such as jailbreaks, backdoors, and leakage of sensitive data, and their susceptibility to data poisoning attacks. Of particular note are attacks that can obtain dangerous information related to topics such as biological weapons. While much of this work can be done without access to classified information, NAIL workers may need security clearances, for example, to determine whether models could leak specific secure data. NAIL should also promote AI security by advancing technical work on AI interpretability, robustness, and control, which was highlighted as a priority in the AI Action Plan.
- Determination of whether AI models or hardware provide capabilities that might warrant export controls.
The proposed FFRDC should pursue activities that range from longer term, fundamental research to rapid response to new developments. Much of the knowledge needed to fulfill Commerce’s mandate lies at the heart of the most significant research questions in AI. This requires deep research, which is also important in attracting top tier talent. On a shorter time scale, it will be important for the FFRDC to provide regular evaluations of models as they progress, including the evaluation of security concerns in foreign models. NAIL can speed up these time critical security evaluations. It will also need to use these evaluations to help create and update procurement guidelines for federal agencies and assess the state of international AI competition. Finally, the FFRDC should be a source of expertise that can support Commerce in a wide range of topics such as export control and development of a workforce trained to appropriately take advantage of AI tools.
The FFRDC will also need to work closely with industry to develop standards for the evaluation of models, and support efforts to create international standards. For example, it may seek to facilitate an industry consensus on the evaluation of new models for security concerns. NIST is well known for similar efforts in many technical areas. Finally, the FFRDC should provide a capacity for rapid response to significant AI developments, including possible urgent security concerns.
Recommendation 3. Provide a sufficient budget to cover the necessary scale of work.
There are different possible scales at which NAIL might be created. It is important to note that creating industry scale models from scratch can cost tens or hundreds of millions of dollars. However, the task of evaluating models may be undertaken without this expense by experimenting on models that have already been trained. Much of the published work on model evaluation takes this course. Such evaluations and experiments still require access to significant computational resources, requiring millions of dollars a year in compute, depending on the size of the effort. The FFRDC’s research might also include experiments in which smaller models are built from scratch at a much smaller expense than what is required to train industry sized models.
We consider two alternatives as to the size and budget of the proposed FFRDC:
- Testbed for AI Competitiveness and Knowledge (TACK): A smaller, prototype effort involving dozens of researchers and support staff, including staff that will facilitate collaborations with industry and other agencies. Such a small-scale effort will not be able to address the full range of problems that Commerce has been tasked with, but will be able to contribute to important missions and demonstrate the value of such an FFRDC on an accelerated timeline. This might cost a few tens of millions of dollars per year, on the scale of Commerce’s current National Cybersecurity FFRDC (NCF).
- Full NAIL: A larger-scale effort could address the full range of tasks outlined above. At this scale, the FFRDC could also take the lead in shaping international standards. For comparison, the Software Engineering Institute (SEI) operates as an FFRDC with a staff of roughly 700 and an annual budget of about $130 million.
The figure in Appendix B lists all current FFRDCs and their annual budget in 2023.
The budget of the FFRDC would need to cover several different costs:
- Research staff. This would consist of experienced researchers who would lead fundamental research and oversee shorter term technical work.
- Research support staff. This would include experienced developers, many with experience in data collection and cleaning, model training and evaluation.
- Administrative support.
- Policy experts skilled in interfacing with industry and other government agencies.
- Computer staff, with experience in supporting large scale computing resources.
- Computing resources, including funds to purchase GPU clusters or to obtain them through cloud services.
- Other expenses such as travel, office space, and miscellaneous overhead.
Recommendation 4. Make NAIL the Backbone of a Broader AI Ecosystem at Commerce.
While an FFRDC offers a unique combination of technical depth and recruiting flexibility, other institutional approaches could also expand Commerce’s AI expertise. One option is to expand the Center for AI Standards and Innovation (CAISI) within NIST, leveraging its standards and measurement mission, though it remains bound by federal hiring and funding rules that slow recruitment and limit pay competitiveness.
A separate proposal envisions a NIST Foundation—a congressionally authorized nonprofit akin to the CDC Foundation or the newly created Foundation for Energy Security and Innovation (FESI)—to mobilize philanthropic and private funding, convene stakeholders, and run fellowships supporting NIST’s mission. Such a foundation could strengthen public-private engagement but would not provide the sustained, large-scale technical capacity needed for Commerce’s AI responsibilities.
Taken together, these models could form a complementary ecosystem: an expanded CAISI to coordinate standards and technical policy within government as well as providing oversight over the FFRDC; a NIST Foundation to channel flexible funding and external partnerships; and an FFRDC to serve as the enduring research and engineering backbone capable of executing large-scale technical work.
Conclusion
The Trump administration has set ambitious goals for advancing U.S. leadership in artificial intelligence, with the Department of Commerce at the center of this effort. Ensuring America’s continued leadership in AI requires technical expertise that existing institutions cannot provide at scale.
NAIL, a new Federally Funded Research and Development Center (FFRDC) offers Commerce the capacity to:
- Push forward our fundamental understanding of frontier AI models along axes that are central to Commerce’s mission, including measurement and evaluation.
- Build the trusted benchmarks and standards that can become the global default.
- Rapidly respond to new technical and security challenges, ensuring the U.S. stays ahead of competitors.
- Provide authoritative analysis for export promotion and control, ensuring U.S. technologies are widely adopted abroad while protected from adversaries, and strengthening America’s hand in international negotiations and trade forums.
By sponsoring this FFRDC, Commerce can secure the talent, flexibility, and independence needed to deliver on the Administration’s commercial AI agenda. While CAISI provides the technical anchor within NIST, the FFRDC will enable Commerce to act at the necessary scale—ensuring the U.S. leads the world in AI innovation, standards, and exports.
Appendix A. References to the Department of Commerce in America’s AI Action Plan
Appendix B. FFRDC Budgets
Appendix C. Further Background on FFRDCs
FFRDCs in Practice: Successes and Pitfalls
FFRDCs have been supporting US government institutions since World War II. Overviews can be found here and here. In this appendix we briefly describe the functioning of FFRDCs and lessons that can be drawn for the current proposal.
In a paper by the Institute for Defense Analyses (IDA) a panel of experts “expressed their belief that high-quality technical expertise and a trusting relationship between laboratory leaders and their sponsor agencies were important to the success of FFRDC laboratories” and felt that “The most effective customers and sponsors set only ‘the what’ (research objectives to be met) and allow the laboratories to determine ‘the how’ (specific research projects and procedures).” Frequent personnel exchange programs between the FFRDC and its sponsor are also suggested.
This and the experience of successful FFRDCs suggests that the proposed FFRDC be closely linked to relevant ongoing efforts in NIST, especially CAISI, with frequent exchanges of information and even personnel. At the same time, the proposed FFRDC should have the freedom to explore very challenging research questions that lie at the heart of its mission.
As an example of the relationship between agencies and associated FFRDCs, the Jet Propulsion Laboratory supports many of NASA’s priorities, addressing long-term goals such as understanding how life emerged on earth, along with more immediate goals such as catalyzing economic growth and contributing to national security. Caltech manages operations of JPL. In general, NASA sets strategic goals, and JPL aligns its long-term quests with these goals. NASA may solicit proposals and JPL may compete to lead or participate in appropriate missions. JPL may also propose missions to NASA. As an example, in 2011 the National Academies recommended that NASA begin a mission to return samples from Mars. NASA decided to launch a new Mars rover mission. NASA then tasked JPL to build and manage operations of Perseverance, to accomplish this mission.
On a less positive note, after concerns about the Department of Energy’s (DOE) management of FFRDCs, DOE shifted from a “transactional model to a systems-based approach” offering greater oversight, but also leading to concerns of loss of flexibility and micromanagement. Concerns have also previously been raised about the level of transparency and assessment of alternatives when agencies renew FFRDC contracts, as well as mission creep of existing FFRDCs
Existing FFRDCs Relevant to AI Work
One of the most important criteria for establishing a new FFRDC is to demonstrate that this will fill a need that cannot be filled by existing entities. Many current FFRDCs are conducting work on AI, but this work does not adequately address the needs of Commerce, especially in light of the requirements of the AI Action Plan. For example, the Software Engineering Institute (SEI) run by CMU has deep expertise in the development of AI systems, along with software development and acquisition. However, their mission is to “execute applied research to drive systemic transition of new capabilities for the DoD.” Its AI work focuses on defense related capabilities, and not on the comprehensive evaluation of frontier models needed by NIST.
NIST does support the National Cybersecurity FFRDC (NCF) operated by MITRE. This unit focuses on security needs, not on general model evaluation (although it will be important to clearly delineate the scopes of a new Commerce FFRDC and the NCF). Other FFRDCs, such as Los Alamos or Lawrence Berkeley have significant AI efforts aimed at using AI to enhance scientific discovery. Industry AI labs address some of the questions central to the proposed FFRDC, but it is important that the government have access to deep technical expertise that is able to act in the public interest.
Establishing a New FFRDC
A precedent on the establishment of FFRDCs comes from the Department of Homeland Security (DHS). Under Section 305 of the Homeland Security Act of 2002, DHS was authorized to establish one or more FFRDCs to provide independent technical analysis and systems engineering for critical homeland security missions. In April 2004, DHS created its first FFRDC, the Homeland Security Institute. Four years later, on April 3, 2008, it issued a notice of intent to establish a successor organization, the Homeland Security Systems Engineering and Development Institute (HSSEDI), and in 2009 selected the MITRE Corporation to operate it. HSSEDI—along with DHS’s other FFRDC, the Homeland Security Operational Analysis Center—is overseen by the Department’s FFRDC Program Management Office. This case illustrates both a procedural pathway (statutory authorization, public notice, operator selection) and the typical timeline for standing up such an entity: roughly 12–18 months from notice of intent to full operation. Similarly, the National Cybersecurity FFRDC had its first notice of intent filed April 22, 2013, with the final contract to operate the FFRDC awarded to MITRE on September 24, 2014, about 17 months later.
Appendix D. Requirements for Establishing an FFRDC
Establishing a new FFRDC requires the sponsoring organization (Commerce in this case) to satisfy the criteria laid out in the Federal Acquisition Regulations (48 CFR 35.017-2) for creating a new FFRDC.
These include:
- Requirement: Existing alternative sources for satisfying agency requirements cannot effectively meet the special research or development needs.
- Meeting the Requirement: The special research or development need for improved understanding, measurement and reliability of AI models is clearly highlighted by the Trump Administration’s AI Action plan, and will only increase with more capable AI systems. As detailed in Appendix C, existing FFRDCs do not focus on problems central to Commerce’s mission, including the promotion of AI exports through model understanding and evaluation, model measurement to promote international standards, and identifying security issues central to export controls. Some work on this is done in industry and universities, but as noted, this is not comprehensive or sufficient to address Commerce’s mandate and the goals of the AI Action Plan.
- Requirement: There is sufficient Government expertise available to adequately and objectively evaluate the work to be performed by the FFRDC.
- Meeting the Requirement: CAISI would serve as a source of expertise within the government that can evaluate the work performed by the FFRDC.
- Requirement: A reasonable continuity in the level of support to the FFRDC is maintained, consistent with the agency’s need for the FFRDC and the terms of the sponsoring agreement.
- Meeting the Requirement: Satisfying this requirement may require ongoing support from Congressional appropriations committees, depending on the level of support needed.
- Requirement: The FFRDC is operated, managed, or administered by an autonomous organization or as an identifiably separate operating unit of a parent organization, and is required to operate in the public interest, free from organizational conflict of interest, and to disclose its affairs (as an FFRDC) to the primary sponsor.
- Meeting the Requirement: The DOC and NIST must identify the appropriate contractor to run the FFRDC. There are many non-profits and universities with relevant expertise, including non-profits devoted to AI measurement.
The establishment of an FFRDC must follow the notification process laid out in 48 CFR 5.205(b). The sponsoring agency must transmit at least three notices over a 90-day period to the GPE (Governmentwide point of entry) and the Federal Register, indicating the agency’s intention to sponsor an FFRDC, and its scope and nature, requesting comments. This plan must be reviewed by the Office of Federal Procurement Policy (OFPP) within the White House Office of Management and Budget (OMB).
A sponsoring agreement (described in 48 CFR 35.017-1) must be generated by Commerce for the new FFRDC. This agreement is required by regulations (48 CFR 35.017-1(e)) to last for no more than five years, but may be renewed. It outlines conditions for awarding contracts and methods of ensuring independence and integrity of the FFRDC. FFRDCs initiate work at the request of federal entities, which would then be approved by appropriate units within DOC. The proposed FFRDC should align its mission closely with Commerce and NIST, obtaining contracts from these sponsoring agencies that will determine its priorities. The FFRDC would hire top tier researchers who can both execute this research and provide bottom-up identification of important new research topics.
Even as companies and countries race to adopt AI, the U.S. lacks the capacity to fully characterize the behavior and risks of AI systems and ensure leadership across the AI stack. This gap has direct consequences for Commerce’s core missions.
As states take up AI regulation, they must prioritize transparency and build technical capacity to ensure effective governance and build public trust.
In the absence of guardrails and guidance, AI can increase inequities, introduce bias, spread misinformation, and risk data security for schools and students alike.
At a time when universities are already facing intense pressure to re-envision their role in the S&T ecosystem, we encourage NSF to ensure that the ambitious research acceleration remains compatible with their expertise.