The U.S. Government's Evolving Outlook and Approach to AI

February 13, 2025

In recent years, the United States federal government's policies on artificial intelligence (AI) have shifted considerably. From high-level executive orders under the previous administration to new policy directions under the current leadership, the impact on AI development spans technological innovation, regulatory compliance, and privacy considerations. For both private and public sector professionals seeking strategic guidance on their AI and Large Language Model (LLM) workflows, it is imperative to understand these shifting regulatory landscapes.

Put simply, this administration wants the US to dominate the global AI market. This post examines four key developments shaping America's AI trajectory, with considerations for compliant next steps as the agenda unfurls.

1. Executive Order 14179: "Removing Barriers to American Leadership in Artificial Intelligence"

The Trump administration rescinded most previous AI-related executive orders, except for one dealing with the use of public lands for data centers. In their place emerged Executive Order 14179, entitled "Removing Barriers to American Leadership in Artificial Intelligence."¹ This order represents a major pivot in federal AI policy, signaling the government's prioritization of U.S. dominance in AI technology and its commitment to removing ideological biases in AI systems.

The order imposes specific mandates on federal agencies, including requirements for the Assistant to the President for Science and Technology (APST), the Special Advisor for AI and Crypto, and the Assistant to the President for National Security Affairs (APNSA) to collaborate on an action plan within 180 days of the order's issuance.³ These directives emphasize:

• Enhancing and sustaining U.S. global AI dominance to promote economic competitiveness and national security.
• Ensuring agency-developed AI systems remain free from ideological bias or engineered social agendas.³
• Revoking certain existing AI policies and directives deemed barriers to American AI innovation.
• Coordinating inter-agency efforts to maintain U.S. leadership in AI.

From a compliance perspective, businesses and public agencies must watch for deregulation measures that could alter procurement guidelines and reduce oversight requirements. While a lighter regulatory touch might accelerate innovation, it also elevates responsibility for organizations to self-govern ethical and privacy standards in AI development and implementation for both the development of best practices and mitigation of civil litigation exposure.

2. VP Vance's "America First" Vision for AI Development

At an AI summit in Paris, Vice President JD Vance presented an "America First" perspective on AI, emphasizing U.S. dominance in both AI hardware (particularly chips) and software development.¹ He urged European nations to scale back digital regulations in favor of a more laissez-faire U.S. approach.⁴ Vance described AI as a worker-first productivity engine, where humans stand to benefit by harnessing AI for more efficient workflows.

Key takeaways from his speech include:

• Maintaining Leadership: The United States is depicted as the current and future leader in AI, bolstered by American-designed chips and advanced software.¹³
• Deregulation Advocacy: Overregulation is viewed as a threat to innovation. Vance's stance encourages international cooperation that stimulates AI growth rather than constrains it.²⁵
• Ideological Freedom: Vance insisted American AI platforms would avoid ideological biases and remain open to free speech.²
• Global Security Concerns: He underscored the potential misuse of AI by authoritarian regimes, highlighting a global need for balanced yet innovation-friendly frameworks.³

For commercial practitioners, these remarks signal potential friction with regions like the EU, which generally favor stricter privacy and safety rules. Companies operating internationally should anticipate regulatory patchworks and plan for robust compliance strategies that accommodate divergent data governance standards. This framing also highlights potential advantages in the procurement or funding process for companies that can demonstrate a strong commitment to US-based development and manufacturing, as well as an attention to the humans-in-the-loop.

3. The Stargate Project: Massive Investment in AI Infrastructure

Announced from the White House, the Stargate Project commits $500 billion over four years to bolster the United States' AI infrastructure. This private venture aims to construct numerous advanced data centers across the nation and significantly ramp up the computing capacity needed for AI and LLM initiatives.¹

Key focal areas of the Stargate Project include:

• Data Center Construction: Twenty new facilities, each roughly half a million square feet, will be built to house cutting-edge computing systems powered by NVIDIA chips and Oracle's cloud technologies.²⁴
• Expanded Computing Power: By linking these advanced data centers, Stargate aims to enable AI research on more complex models, including explorations into Artificial General Intelligence (AGI).¹
• Job Creation: Immediate job growth in construction, operations, and related fields is projected to surpass 100,000 positions.²⁶
• Technological Leadership: America's aim is to solidify its status as a global AI powerhouse, preventing critical investments from moving overseas.³
• Collaborative Model: Involving multiple competing organizations within a shared framework, this project exemplifies the capital-intensive nature of modern AI development and the necessity of strategic alliances.⁴

Organizations designing implementations of new AI or LLM workflows should carefully assess how Stargate's high-capacity computing resources might streamline iterative processes of LLMs with considerably greater computational power, and thus how they might stay nimble and competitive in modular integrations.

4. OMB Guidance: Balancing Innovation with Compliance and Privacy

While many AI-related policies from prior administrations have been rescinded, the Office of Management and Budget (OMB) guidance issued in March 2024 remains a key regulatory touchstone for federal agencies. This guidance mirrors EU definitions of "rights-impacting" and "safety-impacting" AI, aligning with the European Union's framework for high-risk AI categories.⁵

According to the OMB, federal agencies must:

• Promote Responsible AI Adoption: Agencies are required to use AI in ways that safeguard public rights and wellbeing.¹¹
• Implement Robust Privacy Measures: Special warnings highlight risks of unintended disclosure of training data, prompts, or user inputs in generative AI systems.³
• Integrate Privacy Protections in Every Stage: From procurement to deployment, AI processes must comply with existing privacy laws and policies.¹¹

For businesses working with federal agencies—or simply drawing from federal standards—the OMB guidance illustrates the growing imperative to manage data responsibly. Maintaining end-to-end privacy safeguards is essential, particularly as generative models become more sophisticated and susceptible to inadvertently exposing sensitive information.

Conclusion: Whether you're a company decisionmaker looking to revamp operations, a startup with a bold vision on how to harness these developments, or a public-sector organization seeking to refine AI strategies, this unfolding U.S. policy landscape underscores the need for both technical innovation and measured compliance. By staying informed about the latest executive orders, international partnerships, infrastructure investments, and federal guidelines, you can proactively align your AI and LLM workflows to meet emerging regulatory standards—and seize the opportunities these advancements offer.