From Petrodollar to Technodollar: How the U.S. Is Rebuilding Global Leverage Through AI
The petrodollar system is ending. For decades, oil priced in dollars and backed by U.S. security guarantees allowed America to sustain persistent trade deficits, dominate global capital markets, and maintain alignment across a network of energy exporters and surplus holders. But that architecture—reliant on military power projection, financial recycling, and industrial offshoring—has reached its limits.
The United States is beginning to organize a new system in its place. Influence through controlled access to the ‘stack’ that underpins artificial intelligence: compute, cloud infrastructure, models, and the applications that run on them. This system, still informal and in motion, is not built on security guarantees or reserve flows. It is being built on selective provisioning and state-backed industrial coordination.
It was already visible in deals like the 2024 U.S.-UAE chip clearance, where access to NVIDIA hardware was granted only after Abu Dhabi’s G42 cut ties with Chinese vendors, but became most apparent in May’s sweeping infrastructure and AI deals in Saudi and the Gulf. It is reinforced by the U.S. dominance in export-controlled chips, the gating of frontier models, and cloud region segmentation.
This emerging system is the technodollar. It is not yet a regime, but it is a strategy for broad economic and geopolitical alignment in the age of AI. A strategy with significant investment implications, with winners being the national champions of the various layers of the stack, protected, trusted and integrated into US policy.
1. The End of the Petrodollar Order
The petrodollar system was a response to the breakdown of Bretton Woods. After the gold window closed in 1971, the United States needed a new mechanism to stabilize the dollar and a way to fund deficits. That emerged through a set of bilateral understandings: oil would be priced in dollars, and the surplus revenue would be recycled into U.S. Treasuries. In exchange, the U.S. would provide military protection and access to its markets.
This arrangement proved remarkably durable. It allowed the U.S. to finance deficits, absorb global production, and underwrite the international order. But by the 2010s, the foundations had begun to crack.
First, the fiscal side deteriorated. Low interest rates and repeated stimulus—most notably after the COVID-19 shutdowns—exposed the limits of deficit finance, with national interest payments surpassing defence spending in 2024.
Second, strategic returns diminished. The U.S. military remains globally deployed, but its ability to compel behavior has declined. The withdrawal from Afghanistan, the limits of deterrence in Ukraine, and China’s rise across technology and trade all make the post-Cold War ‘unipolar’ security model look less credible.
Third, and most importantly, the technological basis of power has begun to shift. Influence is less about trade volume or military bases and more about control over the stack: chips, energy, data centers, and the models built on top.
American firms—particularly NVIDIA, Microsoft, Amazon, and OpenAI—control these inputs. And US policy is being organized around them. We are seeing not a new doctrine, but a series of deals, controls, and alignments that resemble a system.
2. The Technodollar as Strategic Pivot
The US government’s initial foray into geopolitical AI policy was in line with unipolar muscularity: in 2022 export limits on advanced chips explicitly intended to hold back Chinese AI research. By 2023, thought the United States had begun to shift its approach, offering selective access, provisioning AI capabilities under licensing terms and alignment conditions. ‘Provisioning’ is the theme of the technodollar: selectively granting access to critical capabilities like compute, models, or cloud infrastructure, under conditions of alignment, rather than through open markets.
The clearest early case was the UAE. Out in the cold in 2022 by 2024it could access NVIDIA’s most advanced chips but only after G42 (Abu Dhabi’s national champion) agreed to sever its partnerships with Chinese firms, including Huawei. The same year Microsoft committed to deploying OpenAI’s infrastructure through Azure in the Gulf, effectively bringing inference under U.S. compliance. In both cases, the principle was the same: access to the U.S. stack required strategic alignment.
Where the petrodollar system reinforced itself through recycling surplus, allowing producers to recycle dollars into U.S. capital markets, the technodollar reinforces itself through integration. Once a country builds its AI infrastructure on U.S. terms, the cost of exit will be high. Inference pipelines, cloud dependencies, and compliance layers are not easily replaced. Interoperability becomes lock-in.
3. How the Stack Holds Together
The technodollar system functions through a layered stack, each level governed by access, licensing, or service. Where the U.S. controls a layer directly, it sets the terms. Where it does not, it aligns adjacent layers to structure interdependence.
(i) Energy The US is the world’s largest LNG exporter and these exports are shaping the physical geography of AI infrastructure. In countries like Vietnam and Poland, long-term LNG deals are being bundled with investment in data centers. These arrangements make energy a platform—not just for electricity, but for alignment. In energy rich regions like the Gulf the US is looking to partner in physical infrastructure and of course control the digital infrastructure above.
(ii) Cloud InfrastructureCloud platforms like Azure and AWS function as jurisdictional control systems. Sovereign cloud zones embed policy into data residency, latency, and access. To build on these platforms is to inherit their governance.
(iii) Compute NVIDIA’s hardware—especially the H100 and forthcoming B100 chips—is a tightly gated resource. Access is regulated by the U.S. Commerce Department. Exports to China have been blocked, while access for allies is conditional.
(iv) Model providers operate under implicit governance. Access is mediated through APIs, compliant cloud platforms, and usage controls. The result is not just a product ecosystem but a compliance regime.
(v) Applications The application layer is dominated by American firms, themselves deeply tied to the US stack, and no doubt eyeing these recent Gulf deals and weighing the prospects of becoming national champions themselves.
The narrowness of the stack is strategic. It reflects a logic from earlier industrial transitions: protect the emerging layer, consolidate early, embed into policy. The priority is provisioning architecture rather than a competitive marketplace.
4. Capital and Alignment
The technodollar is not evolving toward open competition. It is moving toward state-backed consolidation, enforced through interoperability with the government allocator, gatekeeper, and enforcer.
As such we should see the emergent national champions not as tech incumbents of highly priced startups but as strategic infrastructure: trusted, embedded, and protected. And while there will still be returns to marginal software most value will accrue to those able to get to the heart of this convergence of energy, compute, models, and applications.
The most helpful historical guide will be past episodes of ‘infant industry’ support, whether in industrial Germany and North Asia, or the early days of US steel. The pattern is government promotion through ‘export discipline’ (those who can sell abroad get access to government support in various ways) leading to consolidation into a small number of very large national champions
The main challenge to this architecture is open source. Foundation models with permissive licenses may offer flexibility. But they still run on chips, clouds, and compliance. Even China’s DeepSeek, a sovereign open-source initiative, reflects this logic: DeepSeek is (now) a government backed open source project as an attempt to disrupt the stack, but the model layer is probably not sufficiently foundational to really do so.
Stack Overview
All these representative firms could make a case to be national champions, and the most likely contenders are those included in May’s Saudi and Gulf deals.
I suspect that over the next year we will be able to add a ‘robotics’ layer with strategic players in automated/ AI driven science, drones, and industrial manufacturing. At the moment these are areas without clear leaders (like automated/AI driven science) or (like drone and industrial manufacture) where the leaders are Chinese. But the prospect of these systems being built as or around ‘embodied agents’ will shake up these markets and their strategic importance will lend them to infant industry support national champions.
5. Conclusion
Grand pronouncements about changes to the global order always leave you hostage to fortune and subject to (very fair) accusations that ‘oh look, this week a VC has decided to be an expert on global trade deals’. It Is of course very possible that May’s Middle Eastern deals had more to do with secret deals over Ukraine or Iran, or some other thing, than a strategic pivot around AI. But they do seem to form part of a pattern in which the AI stack is becoming a tool for US strategy rather than just another stick to add to ever vaster and ever more used collection of sticks.
And the world’s most important industries and commodities have always been tightly managed. Tech, in its networked software incarnation of the late 1980s through 2020, may prove to be an exception. More a reflection of underestimation of the technology’s power and the financial privilege of the unipolar moment than a pattern for the future.
If we return to form it will mean a return to integration and to national champions, with investment themes (broadly – own the stack) flowing from that.