On July 23, 2025, the White House unveiled its “Winning the Race: America’s AI Action Plan” (the “Plan”), a comprehensive roadmap outlining a series of policy goals and recommended policy actions intended “for near-term execution by the federal government.”1 The Trump administration is expected to implement the Plan across economic, national security, and technological domains with the aim of achieving “global dominance in artificial intelligence (“AI”).”2 The Plan includes over 90 policy recommendations structured around three pillars: 1) Accelerating AI Innovation; 2) Building American AI Infrastructure; and 3) Leading in International AI Diplomacy and Security.3 Simultaneous with the release of the Plan, the Trump administration issued three executive orders (“Preventing Woke AI in the Federal Government,” “Accelerating Federal Permitting of Data Center Infrastructure” and “Promoting the Export of the American AI Technology Stack”) that aim to operationalize the Plan’s proposed policy recommendations. This Alert summarizes the key elements of the Plan’s three pillars and highlights practical and legal implications for intellectual property attorneys, AI developers and enterprise users to consider.
For background on recent federal procurement guidelines and the One Big Beautiful Bill Act, which similarly emphasize American-sourced AI and supply chain integrity, please refer to our prior alerts (available here and here).
Overview of the Action Plan’s Three Pillars
Pillar I: Accelerating AI Innovation
The first pillar of the Plan is focused on fostering U.S. leadership in the development, deployment, and application of AI technologies. The Plan directs federal agencies to cut back on regulations that “unnecessarily hinder AI development or deployment”4 and to review and evaluate any enforcement actions that could slow AI innovation.5 The Plan suggests that federal funding may be restricted for states that have “burdensome AI regulations”6 in place, signaling a preference for less restrictive regulatory environments. In addition, it advocates for and prioritizes open-source and “open-weight”7 AI models, regulatory sandboxes8 for real-world testing, and workforce training and “upskilling ”9 to prepare the American workforce for AI-driven economic shifts.
Pillar II: Building American AI Infrastructure
The second pillar of the Plan addresses the need for a robust physical and digital foundation to support greater U.S. AI leadership. The Plan is designed to encourage a more streamlined permitting process for data centers, semiconductor manufacturing, and energy infrastructure, including new environmental exemptions and increasing the availability of federal lands for data center and power generation infrastructure.10 The second pillar places a strong emphasis on supporting U.S. semiconductor manufacturing, building high-security data centers for military and intelligence use, and developing a skilled workforce to support these efforts.11 The Plan further calls for enhanced cybersecurity for critical infrastructure and the creation of an AI-specific incident response ecosystem.12
Pillar III: Leading in International AI Diplomacy and Security
The third pillar of the Plan is designed to extend U.S. AI leadership globally, protect critical AI technologies, and counter foreign adversarial influence, particularly from China.13 The Plan recommends establishing a “full-stack” AI export strategy14 that provides hardware, models, software, applications, and standards to allies while restricting the flow of AI compute to “rivals.”15 Under the Plan, federal agencies will be encouraged to work on developing new export controls on chips and “semiconductor manufacturing subsystems,” while aligning protection measures globally through “policy levers.”16
Key Takeaways and Considerations
- Benefits and risks of open-source and open-weight AI models: The Plan’s endorsement of open-source and open-weight AI models presents both opportunities and risks for IP stakeholders. By encouraging the release and adoption of these open models, the federal government is signaling a shift toward greater transparency and interoperability in AI, which on the one hand may accelerate innovation, but on the other hand may complicate IP protection and licensing strategies. Companies will need to consider and navigate through a jumble of open-source and open-weight AI licenses that will govern AI components, each potentially with varied requirements around attribution, redistribution, and modification obligations.17 As is a common consideration in open-source models, the integration of open-source components into proprietary products could trigger obligations to disclose proprietary code and could extend open-source terms to downstream products.18 Consequently, companies should take care to ensure that proprietary algorithms, data, or model weights not intended for public release are clearly identified and protected in contract terms. This is particularly challenging in the AI context, where models may be trained on datasets with unknown provenance or unclear or conflicting licensing terms, increasing the risk of inadvertent IP infringement or breach of license terms.19 Finally, the global availability of these models also means that companies must consider international variations in IP law and enforcement. All together, these layers of complexity increase compliance, legal and reputational risks.
- Gaps, Ambiguities, and Implementation Challenges. Overall, the Plan provides developers with greater freedom to build and deploy advanced AI systems. However, this is offset by existing state-level regulations and tightening export controls that will require companies to increase compliance and supply chain oversight. For many companies, the increasingly complex changes to federal requirements, combined with new documentation and certification obligations, will require ongoing monitoring and the proactive implementation of appropriate compliance strategies. Furthermore, while the Plan is far-reaching in its scope and scale, it leaves several critical questions unanswered and raises uncertainty about tangible impacts—many of the recommended policy actions lack specific details, such as timelines for implementation, expected sources of funding, and identification of the applicable agency responsible for certain initiatives.20 Additionally, the Plan’s emphasis on agency rulemaking and interagency coordination may have the counterproductive effect of slowing down progress, particularly amid ongoing personnel and budget changes at both the federal and state level.21
- Effects on the U.S. AI Industry and Cross-Border Implications. The Plan’s heavy emphasis on deregulation and infrastructure investments is designed to help accelerate the commercialization and deployment of AI technologies across sectors. The Plan’s focus on workforce training and “upskilling”22 also presents opportunities for companies to leverage federal resources to build AI talent pipelines. Companies operating in the data center, semiconductor, and energy sectors in particular should be on the lookout for upcoming reforms to permitting, power grid optimization, and cybersecurity requirements.23 However, the introduction of new compliance hurdles—especially surrounding export controls—may create operational challenges.24 Companies that contract with the federal government should expect new bid requirements focused on the absence of “ideological bias,”25 and may need to update their governance, documentation, and vendor selection practices as a result. The Plan’s focus on supply chain integrity and domestic sourcing—especially for federally supported projects—will require robust documentation and due diligence to ensure adherence to new restrictions on foreign influence and inputs. As a result, companies with multinational AI supply chains may need to reshape their chip import and export strategies, technology licensing practices, and foreign partnerships, particularly with Chinese entities.
- Break from Biden Administration AI Policies. The Plan represents a notable shift from the previous administration’s approach to AI, which emphasized collaborative efforts across multiple government agencies, prescriptive regulation, and safeguards against AI-enabled harms, such as fraud, discrimination and privacy violations.26 The Plan rolls back these measures in favor of market-driven growth, deregulation, and private sector momentum.27 Although there is continuity in areas such as advancing model evaluation capabilities and expanding access to compute resources, the new approach prioritizes “promoting open models, accelerating infrastructure development, and expanding global adoption of U.S. AI models.”28 This shift reflects a broader trend toward decentralization and industry-led governance in the current administration’s U.S. technology policy.
Conclusion
America’s AI Action Plan presents a rigorous outline to promote U.S. “dominance”29 in AI through a combined emphasis on deregulatory actions, infrastructure modernization, and increased U.S. AI diplomatic leadership throughout the world. Stakeholders should closely monitor the implementation of these policies and proactively align compliance, investment, and partnership strategies to capitalize on emerging opportunities and mitigate associated risks.
