Dr. Luis O. Noguerol from Miami Strategic Intelligence Institute for FinGurú
The "U.S. AI Action Plan" from the Trump administration, a far-reaching policy roadmap, defines a new approach to this competition. Its central theme: "win the AI race" by promoting deregulation, infrastructure, and fostering American innovation both domestically and internationally.
In this article, I will examine the fundamental pillars of the plan, the logic behind each one, and the deeper implications for the future of the United States in the hyper-competitive world of AI.
Pillar I: Accelerate Innovation in AI
● Eliminate bureaucracy and burdensome regulation: At the center of Trump's approach lies the promise to "eliminate bureaucracy," which the administration believes stifles innovation and gives competitive advantage to global rivals. The plan:
● Revoke previous executive orders (particularly those from the Biden administration) deemed restrictive or overly cautious regarding AI.
● Direct federal agencies to identify, review, or repeal regulations that are considered obstacles to the development and implementation of AI.
● Propose to restrict federal funding for AI projects in states that establish burdensome regulatory regimes.
This sharply contrasts with the EU's regulatory path for AI, which prioritizes innovation over risk aversion.
Ensure Cutting-Edge AI Reflects Free Speech and American Values
Trump's plan emphasizes the idea that AI must support free speech and avoid ideological bias.
Key policies include:
⮚ Requiring that all large language models (LLMs) contracted for federal use be neutral, according to government criteria, and not designed for social or political agendas.
⮚ Remove references to disinformation, Diversity, Equity, and Inclusion (DEI), and climate change from the National Institute of Standards and Technology (NIST) AI Risk Management Framework.
⮚ The government claims these measures will foster trust and objectivity in state-provided AI tools, although critics warn these policies could marginalize important debates on equity, harm, and inclusion.
Promote Open-Source and Open-Weight AI
Open-source and open-weight models, where the public can access, review, and potentially contribute to AI's core algorithms, are considered vital for democratizing AI and consolidating U.S. leadership as an innovation hub. Measures include:
❖ Improving access to affordable computing for startups and academia, often excluded due to the high costs of "hyperscaling" commercial solutions.
❖ Strengthening the National AI Research Resources (NAIRR) pilot program with public-private partnerships to broaden access to computing and research opportunities.
❖ Promoting the adoption of open-source AI among SMEs to expand the technology's reach.
❖ Facilitating the adoption of AI across all sectors.
While models and software exist in various industries, the adoption rate, especially in complex sectors like healthcare and energy, lags behind AI's potential. To address this, the plan recommends:
✔ Creating regulatory testing environments and "Centers of Excellence in AI" to accelerate safe experimental implementation.
✔ Launching specific (federal and private) partnerships to drive national AI standards and objectively assess productivity improvements.
✔ Conducting periodic reviews and benchmarking of the U.S. progress compared to other powers, particularly China, to ensure the adoption of AI in the U.S. keeps pace.
✔ Empowering the U.S. workforce for the AI era.
An important thread of the plan is the emphasis on workers: ensuring AI complements, not replaces, the American workforce. This addresses recent and growing concerns and seems to indicate that the president's plan addressed such public anxieties. Through new executive orders and initiatives from the Department of Labor, the plan aims to:
Integrate AI skills into education, apprenticeship programs, and workforce training, from high school through to re-skilling.
Establish federal monitoring of the impact of AI on employment, wages, and layoffs, with special programs to rapidly retrain workers in affected sectors.
Implement innovative approaches to training and employment insertion, focusing on adaptability to evolving labor demands.
The administration defines this as an AI revolution that prioritizes the worker, seeking to avoid a future where technology outpaces human opportunities.
Other initiatives in this pillar include funding for automated research infrastructure, requiring that data from federally funded research be shared more widely, and immediate investment in advanced fields like robotics and next-generation manufacturing.
Pillar II: Building U.S. AI Infrastructure
Recognizing that AI supremacy demands cutting-edge hardware, the action plan seeks:
⮚ Streamline permitting processes and federal reviews for data centers, semiconductor factories, and supporting energy infrastructure. We all know how bureaucratic and discouraging prior regulations can be.
⮚ Relax environmental regulations related to AI construction, including possible exemptions for data center projects on federal land or with significant energy demand. Data centers are associated with high energy consumption.
By focusing on physical (not just digital) infrastructure, the administration seeks to overcome bottlenecks in computing power, a key resource in the global development of AI.
The president's plan acknowledges the importance of expanding and modernizing the national power grid, data centers, and energy-intensive advanced AI workloads. Therefore, the plan:
● Recommends policies to prevent the premature closure of existing power plants (which often use fossil fuels).
● Prioritizes connecting new reliable energy sources, especially nuclear and geothermal, to the U.S. power grid, demonstrating its support for AI-adapted energy versus a rapid transition to renewable energy.
Another consideration of the recently issued order is the restoration of semiconductor manufacturing companies and workforce development. The government considers chip manufacturing not only as an economic engine but also as critical infrastructure for national security. Some targeted measures include:
✔ Launching new programs to reactivate domestic chip manufacturing, reducing dependence on foreign suppliers and strengthening the U.S. supply chain. In other words, digital sovereignty: nothing can be better.
✔ Investing in hiring staff for electricians, HVAC technicians, and specialized trades essential for building data centers and factories.
✔ Federal support for critical and secure infrastructure.
Special provisions describe the construction of high-security data centers to meet military, intelligence, and federal needs. The Department of Defense is instructed to prioritize access to computing resources in case of national emergency to ensure readiness and rapid deployment of military AI capabilities.
Given the government's sensitivity and critical infrastructure (and to improve cybersecurity and resilience), the plan proposes:
▪ New cybersecurity initiatives for data centers and nodes of the national power grid.
▪ AI-specific incident response and resilience programs to prevent catastrophic technological failures or hostile actions (this could be more complex in a real scenario than on paper).
Pillar III: Leadership in International AI Diplomacy and Security
A central aspect of Trump's strategy is not only domestic dominance but also promoting U.S. AI systems, hardware, and standards among global partners and allies. The plan aims to:
Bundle hardware, software, models, and technical support into comprehensive export packages for allied countries.
Support U.S. companies, especially in manufacturing and software, by establishing U.S. technology as the backbone of allies' AI infrastructure.
This opens broad markets for the U.S. industry while also tightening the ties between global partners and U.S. technology.
To effectively counter Chinese influence, the plan defines the competition between the U.S. and China as existential, with explicit measures to:
✔ Counter China in international governance bodies and technical standards forums.
✔ Combat legal loopholes and potential exports of advanced chips or software to China, which could be used for military or surveillance purposes, in the grey market.
By focusing on diplomatic and export control initiatives, the document demonstrates the belief that technological leadership conveys strategic influence far beyond the commercial realm.
To ensure compliance with unified federal standards, national competitiveness is considered inseparable from national unity on technology policy, and federal standards will prevail over the existing regulatory patchwork across the 50 states, aiming to curb the fragmentation of innovation channels. This is presented as imperative for global success and competition against centralized rivals like China.
But, as expected, the plan comes at a cost: it sparks debate, raises support, and is not without criticisms.
Major tech corporations and most industry advocates have backed the plan's focus on accelerated infrastructure, deregulation fervor, and expanded export markets. They argue it gives U.S. companies the tools to innovate, expand, and lead globally, especially against Chinese competitors benefiting from state strategies. However, criticisms are harsh and sustained from various fronts, such as:
❖ Environmental groups argue that the marginalization of environmental regulations and the plan's embrace of fossil fuels risk exacerbating the climate crisis and local pollution (which is not surprising at all).
❖ Consumer advocacy and civil liberties defenders warn of the dangers of "freedom for all" in the loss of oversight over AI, which could entail untested products and the rapid implementation of potentially harmful systems without proper accountability. They may be right in their argument, as uncontrolled AI can easily be used against U.S. national interests.
❖ Some labor organizations fear that the promises of rapid re-skilling and new jobs will not offset the scale or speed of the labor disruption that AI could bring.
On the international stage, geopolitical critics observe the risk of intensifying a global "AI arms race" without significant safeguards or international collaborations. There is also concern that the U.S. aggressive efforts to restrict Chinese participation in AI governance could lead to greater technological decoupling, fragmenting the global AI order. It must be recognized that these concerns are valid.
What's next? Implementation and open questions.
Implementing nearly 90 distinct policies will test federal bureaucracy, even with high-level directives. As
Key aspects to consider next year:⮚ How will the "ideological bias" in government AI hiring be operationally defined?
⮚ Will workforce training keep pace with labor market disruptions?
⮚ Will the push for speed and infrastructure affect security, equity, or the environment?
⮚ Will allies accept the new packages of U.S. exports, or will the "America First" rhetoric hinder further cooperation?
⮚ Can the government's approach to open-source AI models and open weights offer innovation and sufficient safety barriers?
The government's strong signal is clear: U.S. dominance in AI is non-negotiable. Whether this leads to lasting global leadership or generates new risks and rivalries will depend on its execution in the coming years.
In summary, the publication of President Trump's AI Action Plan marks a crucial moment in the technological trajectory of the United States. A moment that firmly prioritizes American innovation, deregulation, and infrastructure as pillars of future AI dominance. It is an ambitious and potentially transformative vision. However, as with any strategy of this scale, its success will depend not only on ambition but also on thoughtful execution and the will to adapt to international realities.
The global implications of uncontrolled AI development cannot be ignored, and the government would do well to complement its pro-growth agenda with a balanced understanding of the concerns expressed by allies, partners, and global actors. Only through this strategic foresight can the United States lead and govern responsibly in the era of artificial intelligence.
References
ABC News. (July 23, 2025). The Trump administration's new artificial intelligence plan focuses on deregulation. https://abcnews.go.com/Politics/trump-administrations-new-artificial-intelligence-plan-focuses-deregulation/story?id=124011520
Al Jazeera. (July 23, 2025). Trump's AI plan: Reducing technological restrictions. https://www.cnn.com/2025/07/23/tech/ai-action-plan-trump
White House. U.S. AI Action Plan. (July 2025). U.S. AI Action Plan [PDF]. https://whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf
U.S. Department of Labor. (July 23, 2025). U.S. Department of Labor praises President Trump's AI Action Plan for achieving global dominance in artificial intelligence. https://natlawreview.com/article/us-department-labor-applauds-president-trumps-ai-action-plan-achieve-global
CBS News. (July 23, 2025). The White House reveals the U.S. strategic plan on AI: Here’s what it includes. https://www.cbsnews.com/news/trump-uai-plan-data-centers-us-infrastructure/
CNET. (July 24, 2025). Trump's AI action plan is here: 5 key takeaways. https://www.cnet.com/tech/services-and-software/trumps-ai-action-plan-is-here-5-key-takeaways/
Defense One. (July 24, 2025). How the White House's AI plan benefits, and harms, the race against China. https://www.defenseone.com/technology/2025/07/how-white-house-ai-plan-helps-and-hurts-race-against-china/406944/
FedScoop. (July 24, 2025). Trump mocks copyright and state regulations in AI Action Plan launch. https://www.politico.com/news/2025/07/23/trump-derides-copyright-and-state-regs-in-ai-action-plan-launch-00472443
Reuters. (July 23, 2025). The Trump administration will boost AI sales to its allies and loosen environmental rules. https://www.reuters.com/legal/government/trump-administration-supercharge-ai-sales-allies-loosen-environmental-rules-2025-07-23/
Dr. Luis Noguerol is an IT executive with extensive experience in federal regulations (NIST 800, FIPS, FISMA) and data protection for public and private sectors. He identifies and addresses cybersecurity risks thanks to his Ph.D. in Management with a specialization in Organizational Leadership - Information Systems and Technology, a master's degree in Applied Mathematics and Information Systems, and multiple certifications (CEH, CHFI, Security+). He is a published author, academic, and frequent contributor to radio and television news programs.
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