The AI Bubble in 2026 (1/4)

Part 1: On the coming geopolitics of the compute stack, or Our New Imperial Strategy

Agostino Carraci, The Harmony of the Spheres, 1589-92

My final essay of the year will be split into four parts, laying out areas of the AI bubble I want to focus more on next year. They’re overshadowed by a myopic focus on equity prices, valuations, and capital expenditures—an overcorrection by commentators and talking heads who stubbornly dismissed early AI skeptics. These are all important topics, of course, as they consist of the financial frontier of an AI bubble that is consuming more and more of our economy, but nonetheless are contributing to an obfuscation of the geopolitical and industrial dimensions that’ll have a decisive impact on what our world looks like regardless of whether the bubble bursts or not.

Part One focuses on: how geopolitical ambitions will factor into various actors trying to stabilize or take advantage of the AI bubble in 2026 and beyond. Across the Biden and Trump administrations, the United States has made clear that it views artificial intelligence as integral in its dream of securing hegemonic primacy in the 21st century. Can we anticipate some of the ways that will present itself next year?

From Oil Diplomacy to Compute Diplomacy

One development I expect to see is advocacy (and even some steps) for a transition from the Petrodollar system of the 20th century to what we might call a Compute-Dollar system in the 21st century.

In Le Monde Diplomatique, Evgenvy Morozov reframes “sovereign AI” offerings as “the final act of a three-act play” of US imperial management, featuring an evolution from “dollar diplomacy” to “oil diplomacy” to “compute diplomacy” centered around deploying our state apparatus and capital to preserve global hegemony:

Act I opened in the early 20th century, when the US promoted dollar diplomacy to Latin American governments as a path to political stability through economic prosperity and sound finance; Theodore Roosevelt used this as a pretext to gain control of the Dominican Republic’s customs collection. By 1912 Brown Brothers bank controlled Nicaragua’s customs collection through loan receivership. The majority of the revenue was collected in New York. When Nicaraguans objected, US marines occupied Nicaragua for 21 years (1912-33), with peak deployment reaching nearly 4,000 troops. In 1922 The Nation called it the ‘Republic of Brown Brothers’.

Act II began in 1974. Nixon had killed the gold standard and the dollar was wobbling. Kissinger flew to Riyadh with an offer: charge whatever price you like for oil, as long as it’s in dollars, and invest your profits in US Treasury bonds – a deal backed by implicit security guarantees and the unmistakable threat that deviation would be treated as hostile to US strategic interests. And between 1974 and 1981, a substantial part of OPEC’s approximately $450bn in accumulated surpluses was reinvested in US Treasuries. No marines required; the threat of capital exile was enough.

Act III is still being written, but the scale of operations exceeds everything we have seen so far. The commodity isn’t bananas or barrels but the raw processing power that lets machines calculate faster than central banks can print money.

In Act III, Morozov envisions that the United States could manufacture a “sovereignty crisis” with some hysteria about compromised datacenters and Chinese chips—the only cure, then, is the American option: US-made chips (Nvidia), US-controlled cloud architecture (Microsoft/Amazon), US-controlled financing (BlackRock, Emirati investment firm MGX), and so on. Export controls, like those that have forced ASML to stop serving Chinese customers with extreme ultraviolet lithography machines necessary to make advanced chips

Navin Girishankar, president of the Economic Security and Technology Department at the Center for Strategic and International Studies (CSIS), is a bit more explicit in advocating for what Act III should look like:

The Trump administration aims to ensure that “American AI technology continues to be the gold standard worldwide,” according to Vice President JD Vance. But these agreements miss an essential ingredient of American power: a guarantee that AI-enabled exports generated using American chips will be invoiced and settled in dollars. Giving other countries access to compute gives them the ability to export AI-enabled goods and services globally. That throws up a critical question: in which currency will they settle that trade—dollars, renminbi, or another currency?

Claims that compute is the new oil are now commonplace, but they often overlook what makes this comparison truly powerful. A country might spend $10 billion on data-center infrastructure using American chips—a one-time capital cost. Those chips can then generate $50–100 billion annually in AI-enabled exports to third countries, including China and the Global South: for example, they may contribute to the autonomous vehicle systems that end up on tens of thousands of vehicles, or they may help a drug discovery algorithm locate a new multi-billion dollar therapeutic. The currency used to invoice and settle these exports is a critical source of global influence.

Failing to deliver a solution to this problem would be tantamount to letting the gold standard collapse without a replacement. Fortunately for Americans, in 1974, U.S. Secretary of State Henry Kissinger and U.S. Treasury Secretary William Simon helped engineer the petrodollar system as a replacement for the gold standard in 1974. The United States didn’t just sell military equipment to Saudi Arabia—it anchored global energy markets to the dollar through an implicit agreement with lasting effects and provided the fiscal capacity that helped the United States win the Cold War.

Girishankar concedes are some fundamental differences between the commoditized foundations of a petrodollar arrangement (”oil is a physical commodity with clear delivery points and standardized pricing) and a compute-dollar system (Ai-enabled services—measured in compute units like FLOPS or AI tokens—are digital, distributed, and harder to track”), but believes that if the compute-dollar system is built upon three explicit principles and enforcement mechanisms—as opposed to the implicit understanding of the petrodollar system—then the dream of global supremacy is still alive.

First, the United States should condition access to leading-edge chips on binding commitments to settle AI-enabled exports in dollars.

Girishankar points to trade deals with Malaysia, Cambodia, Ecuador, Argentina, and Thailand that “already require alignment” with export controls, sanctioned entity restrictions, and investment screening.

Second, the United States should use dollar-backed stablecoins as the settlement mechanism.

Trump has already signed the Genius Act, which created a regulatory framework for the issuance of “payment stablecoins” or digital assets that are backed 1:1 by USD or short-term Treasuries. A compute-dollar system could build on this with digital assets that are pegged to the dollar, provide instant settlement, transparency through a distributed ledger and verifiable records, and sustain dollar dominance instead of yuan adoption.

Third, provide an economic security umbrella—a modern complement to the Cold War-style defense umbrella.

We already provide arms, preferential licensing, trade protections, and other benefits in exchange for export control alignment, so the next step should be to formalize them. Do you want priority access to critical mineral reserves we are stockpiling years too late? Do you want protection from Chinese economic coercion? So long as you join the compute-dollar system, we’re in business.

For Girishankar and others, the choice is clear. Either we use the moment slipping from us to create the foundations for permanent monetary and technological advantage, or we allow AI services to be settled in digital yuan, for the US to lose sustained dollar demand, for Treasury borrowing costs increase, and our ability to fund ambitious national projects.

Sovereign AI (which we will talk more about later), technodollars/compute-dollars, synonyms for: making an American tech stack that allies and clients will be forced to become dependent on, one way or another. These desperate bids will have increasingly central roles in shaping trade agreements, cryptocurrency legitimation efforts, arms deals, security partnerships, foreign investment, and the evolution of how we overbuild, overvalue, and overinvest in AI infrastructure.

The Compute Axis: Trump, Altman, and the Gulf

What political vehicle will meet the task for building this new order? One candidate is the burgeoning coalition that we can describe as the Compute Axis: 1) Silicon Valley and its capital-intensive dream of building God out of sand; 2) Trump and his brigands—concerned with transactional relationships, deregulation, and imperial plunder; 3) the sovereign capital of Gulf sovereigns.

One analysis I cohere with is at American Affairs, where Guy Laron wrote a lengthy essay using Trump’s Gulf tour in May 2025 to try and explain the coming political-economic order and what role our various tech overlords, Gulf monarchs, and domestic oligarchs will play in it.

Art of the Deal

It was to the Gulf monarchies that Sam Altman, chief executive of OpenAI, first pitched his $7 trillion plan to build the physical and digital infrastructure for the coming Age of AI. Such an energy supply and compute capacity buildout simply cannot be done in the United States or Europe, where regulatory constraints and political backlash would kill it at conception. There was a place, however, where he could cobble together the capital, land, and “dispatchable power” (e.g. fossil fuels and nuclear).

In the Compute Axis, one key interlocutor proves to be Sheikh Tahnoun bin Zayed—the UAE’s National Security Advisor, the head of its $100 billion MGX sovereign wealth fund, and G42. Tahnoun seeks to leverage the Gulf’s inordinate oil wealth as part of its own transition from Petrostates to PetroCompute hubs. Zayed’s strategy slots into the longstanding strategy by Gulf states to pivot into the (post-oil) future by citing its fruits—oil wealth, cheap energy, authoritarian governance—as attractions to entice foreign investment.

Back in September, I dove into Saudi Arabia’s particular obsession with this post-oil pivot as exemplified by Vision 2030 and its various tensions as an attempt to centralize the Kingdom around MBS while overhauling its economy, civil society, political system, and the international order in ways that advance his interests.

Whether you believe in the transformative potential of AI or McKinsey’s initial Vision 2030 reports, Saudi Arabia will play a central role in the years to come. Trump’s “Road to Riyadh” tour resulted in $2 trillion worth of announced deals that were pure pay-to-play: we rollback Biden-era export controls on the UAE and provide unrestricted access to advanced chips to Gulf clients, while the monarchies provide the capital necessary to build out AI infrastructure operated by American firms.

Open Veins of the Gulf

Unveiled at the September 2023 G20 Summit in New Delhi, the India-Middle East-Europe Corridor (IMEC) had been initially conceived as the West’s response to China’s Belt and Road Initiative—years too late, but a response of some kind.

Under the Trump administration, it has been aggressively repurposed away from a trade corridor to a digital corridor. Gulf-based energy and compute centers (where models are trained and hosted) will be linked with India’s vast pool of digital labor (where models are refined, debugged, and integrated into services). New high-capacity fiber optic cables will cement India as the AI economy’s “back office,” a role it has already had in other sectors.

As Larson puts it, “India long been seen as the world’s back office: a land of coders, clerks, and call centers” but today it is also home to 1,600 Global Capability Centers (GCCs) which employ 1.66 million professionals involved in “software engineering, data analytics, AI research, cybersecurity, and even core product development.” These GCCs are key to the West’s “digital ambitions at scale and at lower cost” and are a rapidly growing part of India’s services exports (well over a third).

In some ways, however, the IMEC is now truly a response to BRI: the latter is state-led, while the former is a “privatized artery of power,” governed by contracts between sovereign wealth funds, tech monopolies, and family offices (i.e. the Trump Organization) that allow participants to bypass traditional diplomatic bureaucracy.

What emerged from this fusion of corridor geopolitics and digital ambition was not just a policy shift but an operational triangle of power, capital, and access. The Trump-Altman vision depended on the coordination of three actors: U.S.-based AI firms in search of infrastructure and funding, Gulf monarchies eager to reposition themselves as indispensable nodes in the global tech economy, and a Trump family empire that straddled both politics and business.

This alliance has achieved staggering velocity. Gulf sovereign wealth funds now bankroll data centers, chip deals, crypto ventures, and real estate branded by the Trump Organization. AI firms gain capital and regulatory havens. Gulf monarchs secure access to otherwise restricted technology. And Trump reaps the political and financial rewards of acting as matchmaker-in-chief. The strategy delivers for all three sides of the triangle, but the very speed and flexibility that make it so effective also expose its limits. Beneath its coherence lies a deeper fragility: a system defined by speed but hollowed out in its capacity to govern.

Most striking is the contradiction between the coalition’s ambitions and its institutional tools. The entire model is built on bypassing the state: private equity replaces diplomacy, crypto transactions circumvent the banking system, fiber cables and next-generation data centers stand in for treaties and embassies. The coalition runs on velocity, but infrastructure requires durability. Ports, corridors, cables, and compute campuses cannot be run on Signal chats and licensing contracts alone. They demand oversight, regulation, dispute resolution, and long-term coordination, which are all functions that the Trump coalition not only neglects but often openly disdains.

More on PetroCompute

Abdullah Alzabin’s recent essay, PetroCompute, provides the blueprint for how the G.C.C. plans to execute a maneuver that essentially swapping potential energy (oil) for digital work (inference).

The core of the “PetroCompute” thesis is simple. The United States is hitting a wall: global AI data centers will require an additional 130 GW of power by 2030, the US gas-power generation capacity is projected to increase by only 30 GW. The American grid is old, litigious, and maxed out. Across both parties, backlash to the AI infrastructure overbuild and Silicon Valley’s so-called reactionary turn (in truth, it has always been a bastion of reactionaries).

Central to the logic of the PetroCompute pivot strategy offered by Alzabin is what he calls a “triple advantage” that could let the GCC outmaneuver Washington and Beijing when it comes to deploying inference infrastructure.

The first is an energy advantage. Europe pays $0.29 per kWh, the U.S. averages $0.17, but the Gulf’s unsubsidized power costs average $0.10 per kWh. Through “centralized planning and execution” the GCC might be able to build out power infrastructure rapidly: the Kingdom plans to add 42 GW of gas capacity by 2030, outpacing the United States by 40 percent.

Second is by a geographical advantage. The Gulf sits at the crossroads of three continents and an extensive submarine cable network, meaning it can service four billion internet users within 100 millisecond latency—the threshold that lets AI interactions feel “instantaneous.” If that is not enough, the region has the world’s largest desalination infrastructure (40 percent of global desalinated water). Geographically, it’s well suited to serve the world’s inference workloads and provide more than enough water to cool power-intensive A.I. data centers as the overbuild continues along.

There’s also a financial advantage: a nearly $5 trillion sovereign wealth fund war chest that is a bit more patient than ravenous Western financiers while also having, as Alzabin points out, a “proven capital deployment capability.”

This rare combination of patient capital and execution agility at large scale, enabled by centralized decision-making and compounding capital endowment, allows this group of states to pursue strategic infrastructure at a scale and speed that few other countries and regions can match.

(So long as one ignores the region-wide failures of megaprojects and Vision 20XX plans foisted upon Gulf monarchies by Western consulting firms)

Still, the advantages laid out here are real, as are the four distinct structural traps that might make the Gulf even more subservient to Washington (or Beijing) in the course of attempting a PetroCompute pivot.

The first risk lies in value capture: how to move up the value chain to higher layers of the tech stack. Alzabin invokes the example of AT&T and Apple: when the former became the exclusive partner for the iPhone launch in 2007, it was valued at double Apple’s market cap ($250 billion vs $105 billion). At the time of the essay’s publication, Apple reached a market capitalization of $3.5 trillion while AT&T has stagnated at $165 billion.

As Malaysia, India, and other nations construct gigawatt-scale A.I. infrastructure, G.C.C. states risk investing in infrastructure that, while necessary, lacks differentiation - a potentially commoditised asset with high fixed costs and limited pricing power.

Hyperscalers secure commercial benefits (preferential terms on power, land, and tax) as well as financial advantages (they capitalize the cloud infrastructure they own). This grows their customer base, captures greater value from proprietary apps atop the stack, and in return the Gulf gets “modest foreign direct investment, jobs, and workforce training.” At the moment the Gulf is merely a landlord for intellectual property and, as we’ve talked about and will add on in the next section, an appendage of US imperial management and extraterritorial control.

The second trap is sovereignty. Anchoring the Gulf’s future to America’s bet on A.I. could conjoin the region to American foreign policy even more tightly than under oil diplomacy. In 2020, U.S. senators threatened to block military sales to the Kingdom unless it cut oil production as part of a bid to save U.S. shale producers. Sacrifice your market share to benefit us (your competition). What will be asked of the Gulf in the coming years as the region grows more dependent on U.S. chips and export licenses?

The third trap is the technological obsolescence of physical infrastructure. AI hardware cycles are ruthless: chip capabilities improve year over year, model demands increase year over year, server racks burn out year after year, and so on and so on. This introduces a massive capital expenditure risk: what if the Gulf pours billions into AI infrastructure that quickly becomes obsolete, dotting the map with stranded assets instead of silicon money printers.

Lastly, we have the cannibalization trap and the Jevons Paradox. From 2023 to 2030, AI infrastructure power consumption could grow from 12 terawatt-hours (TWh) of electricity (2 percent of the GCC’s yearly power consumption) to 330 TWh (half of the GCC’s yearly power consumption)—a conservative estimate that excludes inference demand growth. Inference costs do not seem to be coming down but demand will grow, regardless of whether power consumption costs come down or not. Will the GCC start eating into its hydrocarbon exports to power domestic AI infrastructure (eating into its financial advantage)? Would this pivot turn its energy surplus into an energy crisis?

Alzabin offers some paths around these various traps through a few methods:

• Compute-for-Equity: Instead of servers being rented for cash, Gulf states should offer deals to top AI startups where compute is subsidized in exchange for equity (we already see this with CoreWeave & Microsoft/OpenAI).

• Energy diversification: To prevent AI from cannibalizing oil exports, the Gulf should aggressively build out solar and nuclear to power its data centers

• Ecosystem building: Replicate Ireland’s model where data centers aren’t just rental properties, but anchors and hubs used to build local technical talent alongside specialized contracting industries.

The Most Serene Republic of Nvidia

This brings us back to Morozov’s initial essay on Nvidia chief executive Jensen Huang aggressively promoting “Sovereign AI” as part of a marketing strategy to entrench US dominance. Huang’s pitch is that nations must “own the production of their intelligence,” but that the only way to do so is by purchasing billions of dollars worth of Nvidia hardware.

Who volunteers to run this machine for Washington? It’s no longer soldiers (they are only sent to poor countries), but local elites, who show an enthusiasm that would put colonial administrators to shame. Their logic is irrefutable: in a monopolistic world, diversification is tantamount to suicide, and the only sensible choice is to become the monopoly’s accredited agent. Mao used the term ‘comprador bourgeoisie’ to describe Chinese merchants who lived handsomely inserting themselves between foreign capital and the domestic economy. Today, computing power has replaced opium, but the margins are just as fat.

A key part of Morozov’s framework is Mao’s description of “comprador bourgeoise,” used to describe “Chinese merchants who lived handsomely inserting themselves between foreign capital and the domestic economy.” In the Republic of Nvidia, national sovereignty boils down to the privilege of writing checks to US corporations and facilitating foreign capital flows. Local elites in Europe and Asia climb over each other for the chance to make their countries subservient in hopes that it’ll secure their position in the value chain.

One example Morozov points to is French President Macron’s “sovereign AI” strategy which involves a €109 billion investment plan flowing primarily to Nvidia for its chips and Microsoft for its cloud infrastructure. French firms like Mistral, however, are relegated to the role of junior partner.

Other examples abound:

SoftBank has travelled furthest: once channeling Japanese savings into domestic startups, it’s now investing $48bn in US AI companies (OpenAI, Ampere, Nvidia), though it has only $31bn in cash reserves. It will borrow to make up the shortfall. When SoftBank asked Japanese banks for $13.5bn to finance its next US splurge, they volunteered $27bn.

Deutsche Telekom, once Deutsche Bundespost laying copper for German factories, now markets an ‘industrial AI cloud’ powered by 10,000 Nvidia Blackwell GPUs – designed in Santa Clara, fabricated in Taiwan, booked through Delaware. Berlin owns 32%, but 68% belong to global funds. This is sovereignty in name alone, with the bulk of profits flowing westwards.

Even the most stubborn have given in. Chinese giants such as ByteDance, Alibaba and Tencent, thought to share Beijing’s strategic priorities, are quietly amassing contraband Nvidia chips, despite government pressure, national security concerns and the availability of cheaper (though always inferior) equivalents from Huawei.

Another key pillar proves to be how the United States realizes extraterritorial control through legal mechanisms:

• The Clarifying Lawful Overseas Use of Data (CLOUD) Act, which sets up a legal framework for U.S. access of data stored overseas as well as foreign access to data held by U.S. firms.

• The Foreign Direct Product Rule (FDPR), an export control rule that allows the U.S. to prohibit the sale of products made with American tech, even if made in a foreign country. U.S. sovereignty now extends into the “atoms” of any “chip, wafer or screw that has brushed up against American software or research dollars”

• The Chip Security Act, proposed this may, which would “make it compulsory to fit Nvidia’s H11 and B200 chips with location-tracking system[s]. The same kind of surveillance architecture that the West accused Huawei of building into its products would become federal policy, but only applying to American chips.“ (emphasis added)

The end result being, of course, an offer you can’t refuse:

Access to China’s market, rare earth metals and AI models means not only rejecting the binary choice Washington offers – us or them, dependence or isolation, integration or exile – but also risking capital flight, the possibility of having assets frozen, a hostile security architecture, sticks instead of carrots. In many countries, it’s not the ability to say no that’s lacking, it’s the will to endure what follows.

Final Thoughts

So in the year to come: on the geopolitical front I’m going to be interested in attempts to concretize a compute-dollar system, moves made by the Compute Axis, the Gulf’s attempts to manage its role in the global AI value chain, and how “Sovereign AI” will be used to lock allies and clients into dependence on our tech stack. These projects overlap and contradict. Some require vertical integration under U.S. control, some require horizontal outsourcing to private actors and client states. Some require decisive action and speed and flexibility. But all do require permanent and durable institutions to build some sort of global technological system, even if it is just an appendage of a desperate gambit to preserve geostrategic primacy. Is any of this going to work? I hope not. Do you want to live in a world where America manufactures sovereignty crises to graft its national champions onto various countries? Do we want to have a global competition among elites racing to offer up their nations’ digital futures on a platter in hopes for crumbs? Probably not. Which parts of this vision will succeed, which will fail, and which will transform into something more ugly?