Inside America’s AI Strategy: Infrastructure, Regulation, and Global Competition

The United States stands at the forefront of the global AI race—not through top-down mandates, but by betting on private-sector speed, massive physical buildout, and a deliberately light regulatory touch.

President Trump’s America’s AI Action Plan, released in July 2025, crystallizes this approach. Structured around three pillars—accelerating innovation, building American AI infrastructure, and leading in international diplomacy and security—the plan’s explicit goal is “unquestioned and unchallenged global technological dominance.”

It rescinded the Biden-era Executive Order 14110 on AI safety and replaced it with Executive Order 14179 (“Removing Barriers to American Leadership in Artificial Intelligence”) and a December 2025 order establishing a national policy framework that preempts many state-level rules.

The message is clear: America wins by building faster, regulating less, and denying rivals the tools to catch up.

Pillar II in Action: The Infrastructure Imperative

AI is no longer just software—it is the most energy- and capital-intensive technology in history. Training and running frontier models demands clusters of GPUs that consume power on a scale once reserved for small cities. U.S. data centers already accounted for roughly 4% of national electricity consumption in 2024 (about 176–183 TWh).

Projections for 2028 range from 325–580 TWh (6.7–12% of total U.S. electricity), with AI-specific demand potentially reaching 123 GW by 2035 according to Deloitte—more than thirty times 2024 levels. Grid interconnection queues stretch years in key markets; some hyperscalers have turned to on-site natural-gas generation or direct power contracts to bypass delays.

The Trump administration’s response is aggressive “build, baby, build.” Executive orders signed in July 2025 accelerate federal permitting for data centers, energy infrastructure, and related components (transmission lines, transformers, semiconductors). New NEPA categorical exclusions, expanded FAST-41 processes, and nationwide Clean Water Act permitting options aim to slash review times.

Federal lands—managed by Defense and Energy—are being offered via competitive solicitations for frontier AI data centers paired with co-located clean (or at least dispatchable) power.

The CHIPS and Science Act continues, but with streamlined rules: the Commerce Department’s revamped program prioritizes taxpayer ROI and removes “extraneous policy requirements,” fueling over $640 billion in announced private semiconductor investments across 30 states since 2020, creating or supporting more than 500,000 jobs.

The plan explicitly calls for stabilizing the existing grid, optimizing resources, and embracing frontier energy sources—enhanced geothermal, nuclear fission, and even fusion—while reforming power markets to reward reliability. High-security data centers for military and intelligence use are prioritized with new NIST/DOD standards to protect against nation-state attacks.

Insight: This is infrastructure policy as industrial strategy. The U.S. is treating energy abundance and compute capacity as the new chokepoints, much like semiconductors themselves were in the 2010s. By clearing regulatory underbrush and leveraging federal assets, Washington is trying to ensure American companies can scale models and inference at a pace China’s grid-constrained, coal-heavy buildout cannot sustainably match.

The risk is real grid strain and local opposition, but the alternative—ceding scale to rivals—is viewed as unacceptable.

Regulation: From Safety Theater to National Velocity

The regulatory pillar is defined by what it rejects: the “onerous and excessive” patchwork that emerged under the prior administration and in blue states. Biden’s 2023 EO, with its reporting requirements for frontier models and safety testing mandates, was revoked on day one of the second Trump term.

The December 2025 national framework EO directs the Justice Department to create an AI Litigation Task Force targeting state laws deemed inconsistent with federal policy of “minimal burden.” It conditions certain federal funding (e.g., broadband) on alignment and pushes Congress for uniform national standards.

The Action Plan revises the NIST AI Risk Framework to strip references to “misinformation,” DEI, and climate considerations, replacing them with emphasis on objective truth-seeking and bias-free systems. Procurement rules now prioritize “non-woke” models. Regulatory sandboxes and Centers of Excellence at agencies like FDA and SEC encourage responsible experimentation rather than pre-approval. Open-weight and open-source models are actively promoted through compute access initiatives like the NAIRR pilot.

Insight: This is not deregulation for deregulation’s sake—it is a deliberate choice of velocity over precaution. The administration argues that excessive rules favor incumbents, stifle startups, and hand advantages to less-regulated adversaries. Early evidence: AI adoption in federal agencies and enterprise is accelerating, with agentic systems moving from pilots to production.

Critics worry about safety gaps (e.g., uncontrolled deepfakes or autonomous agents), but the plan counters with voluntary industry commitments, NIST evaluations, and market discipline—plus targeted protections for national-security use cases.

The preemption fight with states (California’s SB 53 transparency law, New York’s RAISE Act) will test federal authority, but the underlying bet is that innovation velocity itself is the best defense.

Global Competition: Export Controls, Diplomacy, and the China Challenge

The third pillar frames AI as a geopolitical contest America must win. The plan seeks to export the full “American AI technology stack” (models, hardware, infrastructure) to allies while tightening controls on adversaries.

Compute export controls remain central: advanced chips face licensing, with recent shifts to case-by-case reviews for certain H200-class GPUs accompanied by 25% tariffs on non-U.S.-supply-chain imports—an indirect revenue mechanism for sales to China.

Frontier chips like Blackwell remain restricted, yet enforcement challenges persist; a senior administration official recently noted that Chinese startup DeepSeek appears to have trained its latest model on Blackwells despite the ban, highlighting smuggling or stockpiling risks.

Diplomacy emphasizes plurilateral alliances, standards-setting in forums like the G7 and OECD, and security guardrails on exports. The goal: make American AI the global default while denying rivals the compute needed to close the gap. Benchmarks like GPQA show the U.S. still leads decisively on frontier performance, but China’s rapid catch-up via models like DeepSeek-R1 underscores that controls must evolve.

Insight: The U.S. strategy is hybrid—part “run faster,” part “restrict.”

By loosening some mid-tier exports with tariffs and conditions, the administration extracts revenue and maintains leverage without fully ceding the market; by protecting the true frontier and investing domestically, it preserves the qualitative edge. This pragmatic approach contrasts with pure decoupling hawks in Congress (e.g., the AI Overwatch Act) and pure openness advocates.

Success depends on enforcement credibility and allied coordination—Japan and the Netherlands remain key partners on semiconductor equipment. The deeper insight: in the AI era, dominance flows from the entire ecosystem (talent, capital, energy, data), not any single choke point. America’s private-sector dynamism and rule-of-law predictability give it structural advantages that state-directed models struggle to replicate.

Outlook: A High-Stakes Bet on American Dynamism

America’s AI strategy in 2026 is coherent, ambitious, and unabashedly competitive. It treats infrastructure as the new battlefield, regulation as a throttle to be loosened, and global competition as a race America intends to win decisively.

The payoffs could be transformative: accelerated scientific discovery, productivity surges, and a new industrial renaissance. The risks—grid overload, safety incidents, enforcement leaks, or congressional pushback—are real and will test execution.

Yet the bet is clear: the fastest path to safe, beneficial AI is the one where American ingenuity is unleashed, not hemmed in. If the Action Plan’s pillars deliver—abundant clean(ish) power, streamlined rules, and controlled technology diffusion—the United States will not merely lead the AI era; it will define it. The world is watching whether “build faster, regulate smarter, compete harder” proves to be the winning formula for the 21st century.