America's AI Gold Rush: Speed, Power, and the Art of Playing with Fire

The Race for AI Dominance

The White House dropped its AI Action Plan in July 2025, and reading through its pages feels a bit like watching someone rev a Ferrari engine while the brakes are disconnected. The document positions America as locked in 'a race to achieve global dominance in artificial intelligence'—a zero-sum competition where whoever builds the largest AI ecosystem gets to set global standards and reap the spoils of economic and military supremacy.

This isn't your typical Washington policy paper filled with bureaucratic hedging. The Trump administration has crafted something that reads more like a war declaration than a technology strategy. The central thesis hits you immediately: America must 'achieve and maintain unquestioned and unchallenged global technological dominance' because AI represents simultaneously an industrial revolution, an information revolution, and a renaissance rolled into one explosive package.

Deregulation as Strategy

The plan explicitly rejects what it characterizes as the Biden administration's 'dangerous' and 'onerous regulation' that would benefit incumbents and paralyze technological development. Instead, we get a full-throttle embrace of deregulation and private sector innovation. The administration wants to rescind Executive Order 14110 on AI, launch sweeping reviews of federal regulations that hinder AI development, and ensure that AI-related federal funding considers how friendly state regulatory climates are to innovation.

Here's where things get interesting from an ideological standpoint. The plan mandates removing references to 'misinformation, Diversity, Equity, and Inclusion, and climate change' from federal AI standards. Government procurement can only contract with AI developers whose systems are 'objective and free from top-down ideological bias.' The administration is essentially declaring that certain topics are political rather than technical concerns—a position that just might prove catastrophically naive.

Infrastructure: The Energy Reality Check

The infrastructure section reads like someone finally grasped that AI development requires more than just clever algorithms. The document notes that 'AI is the first digital service in modern life that challenges America to build vastly greater energy generation than we have today.' This represents a rare moment of Washington acknowledging physical reality: you can't run massive AI systems on good intentions and regulatory frameworks.

The plan calls for streamlined permitting through NEPA (National Environmental Policy Act) reforms, making federal lands available for data center construction, and ensuring the domestic AI computing stack runs on American products free from foreign adversary technology. The energy strategy involves stabilizing existing grid resources, optimizing current capacity, and embracing new generation technologies like enhanced geothermal, nuclear fission, and fusion.

This infrastructure focus hits the actual bottleneck rather than getting lost in abstract policy discussions. Data centers will more than double electricity consumption by 2030 to 945 TWh (Terawatt hours) globally—equivalent to Japan's entire current consumption. A typical AI data center consumes as much electricity as 100,000 households, with the largest consuming twenty times that amount. The plan's 'Build, Baby, Build' mentality does match the scale of what's needed.

The China Competition Strategy

The international strategy section reveals the administration's view of AI as fundamentally reshaping global power structures. The plan seeks to export the full American AI technology stack—hardware, models, software, applications, and standards—to allied nations willing to join America's AI alliance. It explicitly targets Chinese influence in international governance bodies and strengthens AI compute export controls through enhanced monitoring of chip diversion.

The document takes direct aim at Chinese advancement, acknowledging that despite export controls, China's DeepSeek showed they can create competitive AI models at lower cost while potentially having access to 50,000 Hopper GPUs worth over $500 million. The response involves plugging loopholes in semiconductor manufacturing export controls and developing new controls on manufacturing subsystems.

Workforce and Government Implementation

The workforce provisions represent one of the plan's more thoughtful elements. Rather than pretending AI won't displace jobs, the administration acknowledges the challenge and proposes concrete solutions. The 'worker-first AI agenda' includes rapid retraining programs for displaced workers, tax guidance for employer-funded AI training, and an AI Workforce Research Hub under the Department of Labor to evaluate market impacts.

For government implementation, the plan establishes the Chief Artificial Intelligence Officer Council for inter-agency coordination and mandates that federal employees whose work could benefit from frontier language models have access to and training for such tools. The Department of Defense gets particular attention with an AI & Autonomous Systems Virtual Proving Ground and streamlined processes for workflow automation.

What the Plan Gets Right

The plan succeeds in several important areas. The infrastructure focus addresses the real bottleneck - energy and data centers rather than just models. The workforce strategy actually acknowledges job displacement instead of pretending it won't happen. Export control tightening makes strategic sense given China's continued access to advanced chips. Finally pushing federal agencies to use AI tools instead of just regulating them could drive genuine efficiency gains.

The Problems and Contradictions

The problems emerge when you examine the plan's assumptions and timeline mismatches. The deregulation approach removes all references to misinformation and bias from AI standards, treating these as purely political rather than technical concerns. Many AI bias issues represent legitimate technical problems, not just ideological posturing.

The energy timeline creates a massive problem. The plan talks confidently about nuclear and geothermal but ignores the brutal timeline mismatch. Data centers can be built in 2-3 years; new nuclear plants take 10-15 years. Even small modular reactors take 4-5 years. This means massive natural gas build out as a bridge, which conflicts with climate goals the plan has already dismissed as political rather than practical concerns.

There are  export control contradictions as well. The plan wants to simultaneously restrict Chinese access and export American AI globally. These goals can conflict when tight controls push allies toward alternatives. The three-tier access system treats close allies like Israel and Singapore as potential threats, and risks pushing them toward Chinese alternatives.

Unfortunately, the plan also suffers from cost blindness. No serious discussion addresses who pays for this massive infrastructure build out. The private sector needs enormous capital, and the federal government already runs large deficits. The assumption that private sector leadership will automatically align with national interests isn't guaranteed, especially when economic incentives

diverge from security needs.

The Existential Risk Question

The existential risks deserve serious attention. The plan's 'move fast and break things' approach could prove catastrophic if AGI arrives on the accelerated timelines many experts predict. Treating AI development as a race to be won rather than a risk to be managed makes sense only if you believe AI alignment is solved, or Chinese AI dominance would be worse than rushed development risks.

The zero-sum framing with China creates genuine escalation risks. Military AI integration combined with competitive nationalism could trigger an arms race. Autonomous weapons systems developed under 'wartime' urgency could lower conflict thresholds. The plan treats AI dominance as essential for national survival—a mindset that, mirrored in Beijing, could lead to first-strike incentives.

Grid collapse represents another serious risk. Data centers now account for 4.4% of US electricity demand, up from 1.9% in 2018, with some states already over 10%. The plan's infrastructure timeline may not keep pace with AI deployment, risking brownouts, reliability issues during peak integration periods, and substantially higher energy costs.

The Final Assessment

The plan will likely succeed in accelerating American AI development short-term but may create longer-term strategic vulnerabilities by alienating allies and underestimating Chinese adaptability. It represents a high-risk, high-reward approach that could either cement American dominance or accelerate the emergence of alternative AI ecosystems.

The energy piece will provide the real test. If America can't solve the electricity supply problem quickly, all the other policies become irrelevant. The plan gets the scale and urgency right but suffers from typical overconfidence. The workforce provisions show surprising thoughtfulness, but the ideological deregulation components seem potentially counterproductive.

Most critically, the plan assumes America can simultaneously deregulate domestically while controlling technology globally. That's a difficult balance when China proves it can innovate around restrictions and allies get caught in the crossfire. It’s important to understand that this approach prioritizes short-term competitive advantage over long-term species survival—a gamble that may determine not just American technological leadership, but whether human beings remain in control of the systems that will soon govern their lives.

The plan represents either visionary leadership or dangerous overreach. Time will tell which assessment proves correct.

Sources:

The White House, July 2025, "Winning the Race: America's AI Action Plan"