White House AI Action Plan: Deregulation, Infrastructure, and Potential Risk
Accelerating the AI industry could bring additional confidentiality concerns
The White House has released a comprehensive strategy document, "America's AI Action Plan," outlining a national agenda to secure and maintain "unquestioned and unchallenged global technological dominance" in artificial intelligence (p. ii). Published in July 2025 by the Executive Office of the President's Office of Science and Technology Policy, the plan, developed under the direction of Executive Order 14179, articulates a vision for winning the global "AI race" through a three-pronged approach: accelerating innovation, building domestic infrastructure, and leading in international diplomacy and security (p. 1). For technology owners, investors, and counsel, it is vital to understand the nature of this planning document.
It is not a self-executing law or executive order in itself; rather, it is a comprehensive set of "Recommended Policy Actions" (p. 3) intended to guide federal agencies. Its "teeth" will be the ensuing regulations, funding priorities, and enforcement actions undertaken by federal departments ranging from Commerce to Defense and beyond.
The document presents a significant shift in federal policy, emphasizing deregulation and private-sector leadership to create what it calls "a new golden age of human flourishing, economic competitiveness, and national security for the American people" (p. 1).
The plan is built on a philosophy of aggressive innovation, fueled by deregulation, a massive infrastructure build-out, and a focus on the American workforce. While optimistic about technology's potential and the executive branch’s support, a closer look reveals areas that warrant caution for IP-focused professionals and a few noteworthy risks that will require careful strategic planning.
Pillar I: Fostering Innovation by Removing Barriers
A central theme of the Action Plan is the aggressive removal of perceived obstacles to innovation. The administration asserts that America's private sector must be "unencumbered by bureaucratic red tape" (p. 3) and has already taken steps like rescinding the previous administration's Executive Order 14110 on AI, which it claims "foreshadowed an onerous regulatory regime" (p. 3).
The plan recommends a government-wide effort to "identify, revise, or repeal regulations, rules, memoranda, administrative orders, guidance documents, policy statements, and interagency agreements that unnecessarily hinder AI development or deployment" (p. 3). It even suggests a review of all Federal Trade Commission (FTC) investigations and consent decrees from the prior administration to potentially "modify or set-aside any that unduly burden AI innovation" (pp. 3-4).
While a deregulatory environment may be welcomed by many in the tech sector, it introduces a level of uncertainty. IP professionals may see a shifting compliance landscape, where established rules are re-evaluated.
A particularly complex issue arises from the plan's approach to state-level AI laws. It proposes that federal agencies should "consider a state's AI regulatory climate when making funding decisions," potentially limiting funds to states with "burdensome AI regulations" (p. 3).
Rather than discouraging state regulation, this could create a fractured legal environment, forcing companies with national operations to navigate a patchwork of state laws, complicating product development and go-to-market strategies. For instance, California may push back here.
The Open-Source Push and Data Disclosure
The Action Plan strongly encourages the use of "Open-source and open-weight AI models," citing their value for startups, academic research, and government adoption (p. 4). The plan aims to create a "supportive environment for open models," viewing them as a geostrategic tool that could become global standards (p. 4).
This pro-open-source stance presents a classic tension for IP owners. While open models can accelerate development and adoption, they also challenge traditional proprietary business models. Companies that have invested heavily in creating unique, closed-model AI systems may face new competitive pressures. IP counsel will need to be adept at advising on hybrid licensing strategies and protecting core trade secrets while participating in a more open ecosystem.
A related area of concern involves data rights. The plan calls for the creation of "world-class scientific datasets" (p. 8) and proposes a requirement for "federally funded researchers to disclose non-proprietary, non-sensitive datasets that are used by AI models during the course of research and experimentation" (p. 8).
The distinction between "proprietary" and "non-proprietary" data can be ambiguous. Technology companies collaborating on federal projects or using these public datasets will need clarity on several fronts:
Copyright and Licensing: Who owns the copyright to AI-generated content derived from these datasets? What are the usage rights and restrictions? Courts are considering these questions right now.
Data Provenance: There is a risk that these large-scale datasets could inadvertently contain copyrighted text, images, or code scraped without permission. Companies using this data to train their models could face downstream infringement liability.
Confidentiality: The plan calls for building secure compute environments for restricted data (p. 9), but the push for disclosure will require robust legal frameworks to protect confidential or trade-secret information embedded within datasets.
Pillar II: A Mandate to "Build, Baby, Build!"
The second pillar of the plan is a massive buildout of American AI infrastructure, driven by the declaration that "we need to 'Build, Baby, Build!'" (p. 1). This includes streamlining permitting for data centers and semiconductor manufacturing facilities and developing a more robust energy grid to power them (pp. 14-15).
For technology companies, a key directive in this section is the focus on supply chain security. The plan mandates that the "domestic AI computing stack is built on American products" and that supporting infrastructure is "free from foreign adversary information and communications technology and services" (p. 15). This will likely translate into more stringent compliance and verification requirements for any company in the hardware or software supply chain.
The plan also emphasizes the need for "Secure-By-Design AI Technologies and Applications" (p. 18). While a prudent goal, this signals a potentially higher standard of care for AI developers. In the event of a system failure or cyberattack, demonstrating adherence to "secure-by-design" principles could become a critical factor in mitigating liability.
IP lawyers should anticipate the need for stronger contractual warranties and disclaimers related to AI system security and robustness. The need for speed to market will have to be balanced with any requisite security standards.
Fueling the Future: Energy and Infrastructure
The Action Plan makes a stark connection between AI dominance and energy production. It asserts that "AI is the first digital service in modern life that challenges America to build vastly greater energy generation than we have today" and notes that "American energy capacity has stagnated since the 1970s" (p. 14).
To address this, the plan rejects climate change questions and calls for a massive infrastructure initiative (p. 1).
The core of this strategy is to streamline permitting for data centers and energy projects by creating new categorical exclusions under the National Environmental Policy Act (NEPA) and expediting processes under laws like the Clean Water Act (p. 14). The plan advocates for a three-phase approach to grid development:
Stabilizing the current grid by preventing the "premature decommissioning of critical power generation resources" (p. 15).
Optimizing existing infrastructure with advanced management technologies (p. 15).
Growing the grid for the future by prioritizing "reliable, dispatchable power sources" and embracing nuclear and geothermal energy (p. 16).
For technology companies, the promise of faster data center and semiconductor facility construction is appealing. However, this approach also creates potential headwinds.
A national strategy that de-emphasizes certain environmental regulations may face legal challenges and public opposition, which could introduce unforeseen delays and reputational risks for companies building the energy-intensive infrastructure required for their AI innovations. There is no doubt AI needs significantly more energy.
A Dual Focus on the American Workforce
The plan aims to dedicate significant attention to the human capital required for the AI era, framing its agenda as "worker-first" (p. 6). The strategy addresses the workforce from two distinct angles.
First, it seeks to empower workers for an AI-driven economy. Acknowledging that AI will "transform how work gets done," the plan outlines actions to manage this transition (p. 6). Recommendations include prioritizing AI skill development in career and technical education (CTE), clarifying tax rules to encourage employer-reimbursed AI training, and leveraging the Bureau of Labor Statistics to study AI's impact on jobs and wages (p. 6). The plan addresses the risk of displacement by recommending guidance for states on using Rapid Response funds to "proactively upskill workers at risk" and retrain those impacted (p. 7).
Second, the plan confronts the critical need for a skilled workforce to build the physical infrastructure of AI. It calls for a national initiative to identify high-priority occupations like electricians and advanced HVAC technicians, develop national skill frameworks, and fund industry-driven training programs (p. 17). A key part of this strategy is to expand early career exposure, pre-apprenticeships, and Registered Apprenticeships to create a sustainable pipeline of talent for these essential roles (p. 17).
For business leaders and IP owners, these workforce initiatives are a double-edged sword. A highly skilled, AI-literate workforce is essential for growth. However, the plan's success hinges on the effective execution of these ambitious education and retraining programs. Any failure to close the skills gap could become a primary bottleneck, limiting a company's ability to innovate and expand.
Pillar III: An Assertive International Strategy
The final pillar outlines a foreign policy designed to "export American AI to allies and partners" and "counter Chinese influence in international governance bodies" (p. 20). A significant portion of this section is dedicated to strengthening and enforcing export controls on sensitive technologies.
This presents one of the most direct challenges for technology owners and their legal teams. The plan recommends:
Enhanced Compute Controls: Exploring "location verification features on advanced AI compute to ensure that the chips are not in countries of concern" (p. 21).
Plugging Loopholes: Developing "new export controls on semiconductor manufacturing sub-systems," which are not currently controlled to the same degree as major systems (p. 21).
Forcing Global Alignment: Using tools such as the "Foreign Direct Product Rule and secondary tariffs" to compel international partners to adopt complementary protection measures (p. 21).
These measures suggest a future of highly complex and rigorously enforced export regulations. Companies dealing in advanced computing hardware, semiconductor components, or even sophisticated AI software will need specialized legal guidance to navigate this maze and avoid severe penalties.
Amother point of caution relates to national security reviews. The plan states that the government will partner with developers to "evaluate frontier AI systems for national security risks," particularly concerning CBRNE weapons development and cyberattacks (p. 22).
This security measure creates a profound confidentiality risk. Companies will be asked to share their most valuable IP—the architecture and weights of their frontier models—with government agencies. Establishing clear legal protocols to prevent the leakage or compelled disclosure of these crown-jewel trade secrets during such reviews will be a paramount concern for IP counsel.
A Roadmap Demanding Vigilance
America's AI Action Plan is a bold roadmap, not a final destination. Its pro-innovation, pro-growth orientation is a welcome signal for many in the technology sector. However, its implementation will create a dynamic and potentially turbulent environment.
Again, America's AI Action Plan does not function as a self-executing law or an executive order. Instead, it operates as a comprehensive guide for federal agencies, outlining a series of "Recommended Policy Actions." The plan's real-world impact will be realized through the specific regulations, funding priorities, and enforcement activities that departments from Commerce to Defense are directed to implement.
Still, the document signals a clear and aggressive national direction. Its focus on unleashing private sector innovation and building domestic capacity offers tremendous upside for the technology industry. IP owners and their counsel must remain vigilant, carefully tracking the specific regulations that emerge from this plan and preparing for the practical challenges associated with the nation's ambitious energy, workforce, and international policy goals.
The path to AI dominance envisioned by the plan is accompanied by a host of complex challenges, including a shifting regulatory framework, unresolved questions about data rights in an open-source era, a tightening export control regime, and potentially a plethora of brand new confidentiality and cybersecurity risks.
The success of this national endeavor will depend not only on technological advancement but also on the careful development of legal and policy frameworks that foster innovation while managing its inherent risks.
Disclaimer: This is provided for informational purposes only and does not constitute legal or financial advice. To the extent there are any opinions in this article, they are the author’s alone and do not represent the beliefs of his firm or clients. The strategies expressed are purely speculation based on publicly available information. The information expressed is subject to change at any time and should be checked for completeness, accuracy and current applicability. For advice, consult a suitably licensed attorney and/or patent professional.
Reading this made me think about how uneven AI policy is depending on where you work. In my own projects, the legal uncertainty ends up slowing things down more than the tech itself.