How AI Has Granted America Vast New Power

Washington no longer treats artificial intelligence as a Silicon Valley curiosity. By mid-2026, AI infrastructure has become the organizing principle of US economic and foreign policy, and the AI geopolitical power the country has accumulated is now measured in gigawatts, GPUs, and trillion-dollar pledges. The Stargate Project, a joint venture between OpenAI, Oracle, SoftBank, and the UAE’s MGX, has already deployed more than $100 billion of a planned $500 billion buildout, with hyperscalers collectively set to spend close to $700 billion on data centers in 2026 alone. That capital, concentrated almost entirely on American soil, is reshaping who sets the rules of the next industrial era.

The shift didn’t happen by accident. It’s the product of a deliberate fusion of state power and private capital that has no precedent since the postwar military-industrial buildout — and it’s producing leverage Washington is already using, from chip export controls to AI diplomacy with the Gulf states.

The Compute Gap Is the New Power Gap

The clearest evidence of America’s new advantage sits in raw computing capacity. According to analysis from the Institute for Progress, if the United States exported no advanced chips to China at all, its compute capacity in 2026 would run more than ten times China’s. Even with looser export policy, including the controversial sale of Nvidia’s H200 chips, the gap narrows but doesn’t disappear — and Chinese firms have already ordered more than two million H200 units, far beyond what domestic manufacturers like Huawei can currently produce (Foreign Affairs).

• Stargate’s scale: nearly 7 gigawatts of planned capacity confirmed across sites in Texas, Michigan, and beyond, with a path toward 10 gigawatts by 2029 (OpenAI).
• Capital commitment: roughly $400 billion already committed across Stargate’s first wave of sites, part of a broader $1.4 trillion compute-spending trajectory Sam Altman has floated for the project’s lifetime (Data Center Dynamics).
• Industry-wide spend: hyperscalers — Microsoft, Google, Amazon, Meta, and Oracle among them — are on track to spend close to $700 billion on data centers in 2026 (TechCrunch).

That’s not abstract market enthusiasm. It’s the physical infrastructure of a power base — and it’s why allies and rivals alike are recalibrating around it.

Why America’s AI Lead Is Becoming a Geopolitical Lever

How is AI changing America’s global influence in 2026?

AI has expanded US influence by turning compute and chip access into instruments of statecraft. Washington now uses export controls, data-center partnerships, and AI alliances with countries like the UAE to extend American technological standards abroad, much as it once did with finance and military hardware in the Cold War.

That’s not theoretical. The Trump administration’s “Winning the AI Race” action plan, released last July, frames AI leadership explicitly in terms of “overwhelming economic, military, and geopolitical advantages” for whichever country secures it (Foreign Affairs). Analysts at the Institut Montaigne describe the resulting arrangement as a “Hamiltonian” pact: in exchange for deregulation and privileged access to public contracts, major tech firms have effectively aligned themselves with the White House’s industrial strategy, promising to advance US interests abroad as they expand overseas (Institut Montaigne).

The UAE relationship is instructive. Under the Stargate framework, every dollar Abu Dhabi invests in its own domestic AI buildout is matched by an additional dollar flowing into American AI infrastructure — a structure that effectively recruits Gulf capital to underwrite US technological supremacy while tying a strategically vital region closer to Washington (Built In).

The Second-Order Effects: Energy, Markets, and Smaller Economies

The downstream consequences of America’s AI buildout extend well past Silicon Valley boardrooms. Three are already visible.

Energy demand is becoming a national security variable. The same data-center expansion that’s cementing US compute dominance is also straining power grids, pushing utilities toward new nuclear and gas commitments, and turning electricity capacity into a bottleneck as consequential as chip supply itself. EFG International’s 2026 outlook flags this directly, noting that the AI investment cycle is driving “unprecedented demands for data centre capacity” worldwide, with the US at the center of that surge (EFG International).

Capital markets are absorbing historic levels of leverage. Much of the Stargate buildout is debt-financed. The Abilene, Texas flagship site alone drew roughly $9.6 billion from JPMorgan across two loans, part of a broader pattern of hyperscalers and their financing partners taking on debt at a pace that’s reportedly making bank CFOs uneasy even as tech executives stay bullish (TechCrunch).

Middle powers are left negotiating from a weaker position. Countries without the capital or chip access to compete on frontier AI are increasingly pursuing “sovereign AI” strategies — smaller, nationally controlled systems built to preserve some independence from both Washington and Beijing. Chatham House research describes this as a defensive posture rather than genuine competition, reflecting how thoroughly the US-China duopoly has reshaped the playing field for everyone else (Chatham House).

For Pakistan and other emerging markets watching this from the outside, the implications are direct: access to frontier compute, AI talent pipelines, and chip supply chains is increasingly gated by alignment with one of two blocs, not by market merit alone.

Not Everyone Agrees America’s Lead Is Durable

That said, the picture is more complicated than triumphant headlines suggest. A growing body of analysis pushes back on the idea that AI dominance functions like a winner-take-all race at all.

Writing in Foreign Affairs, analysts argue that the US and China aren’t actually competing on the same track. China’s compute disadvantage is real, but its domestic chip production is constrained primarily by manufacturing bottlenecks rather than by lack of demand or talent — meaning export restrictions slow Beijing’s access to foreign chips without necessarily slowing its long-term self-sufficiency drive (Foreign Affairs). DeepSeek’s early-2026 research on more efficient training methods reinforced the point: China has repeatedly found ways to close capability gaps through algorithmic efficiency rather than raw chip volume, narrowing the practical advantage of America’s compute lead (Atlantic Council).

There’s also a structural risk inside America’s own strategy. The Stargate model relies on an unusually tight alignment between the federal government and a handful of private firms — a “let them cook” approach, in former administration adviser David Sacks’ phrasing — that concentrates enormous policy influence in companies whose interests won’t always match the national interest (Institut Montaigne). If that alignment frays, or if the debt financing underpinning the buildout sours, the foundation of America’s AI-driven leverage could prove less stable than its current scale suggests.

The Power Is Real, But So Is the Bet

America’s AI lead has translated into something unmistakably tangible: physical infrastructure, chip-supply leverage, and a deregulatory partnership between Washington and its largest tech firms that’s already reordering alliances from Abu Dhabi to Ann Arbor. Still, that power rests on continued capital flows, stable energy supply, and a compute advantage that rivals are working hard to erode through efficiency gains rather than brute-force matching.

What’s emerging isn’t a settled hierarchy. It’s a high-stakes bet that scale itself — gigawatts, trillions in committed capital, and chip-export control — will outpace whatever workarounds competitors devise. Washington is wagering the country’s economic future on that bet holding.