Korea’s Strategic Role in the Data-Over-Oil Era

Throughout history, hegemony has always been determined by who controls the core resource of the era. In the age of industrialization, that resource was oil. Oil powered factories, factories produced goods, and goods created wealth. Nations went to war to secure energy, and the global order was reorganized around the flow of oil.

Today, that order is quietly—but unmistakably—changing. A resource more important than oil has emerged. That resource is data.

Data is not merely a collection of information. It is the source of the ability to predict future demand, anticipate behavior, and automate decision-making. In the past, value was created by burning oil to drive physical production. Today, value is created by training data to generate new products and services. What matters now is not the quantity of data, but its quality: how close it is to real-world activity, how repeatable and accumulative it is, and how deeply it is connected to actual industries. At this point, data ceases to be a private asset and becomes a strategic national resource.

This is why states are now fighting to collect data. This is not about digital governance or platform policy. In the age of AI, nations can no longer sustain competitiveness through laws and institutions alone. Which data they possess—and on what computational infrastructure that data is trained—determines both industrial power and national security. China has pursued this reality most explicitly.

China treats data as fundamentally state-owned. Administrative, consumer, mobility, production, and surveillance data are first collected by the government, then selectively shared with private enterprises. From a free-market perspective, this may appear inefficient. Yet in AI—where large-scale learning and experimentation are essential—this structure is remarkably effective. China’s rapid progress in autonomous driving, smart cities, and industrial automation reflects this reality. From a data perspective, China is already well supplied.

The United States occupies a very different position. It has algorithms, capital, platforms, and talent—but it lacks one critical element: real-world data. Manufacturing processes, defect logs, micro-error data, and the tacit knowledge embedded in skilled labor scarcely exist within the U.S. Digital data is abundant, but data that explains the physical world is not. To push AI to the next level, the U.S. must look beyond its borders.

This is where America’s strategy becomes clear. Rather than isolating China alone, the U.S. has chosen to elevate the industrial level of its allies. At the center of this strategy stands Korea. Korea possesses real-world manufacturing data comparable to China’s, yet remains fully integrated into the U.S.-led technology and security alliance. From Washington’s perspective, Korea becomes a substitute source of “reality-based data” that China once provided.

In this context, Nvidia CEO Jensen Huang’s recent remarks in Korea—referencing the provision of approximately 260,000 AI chips—should be understood strategically. This was not diplomatic courtesy or symbolic generosity. Compute is the new energy of the AI era. At this scale, GPUs enable national-level data center capacity and represent the threshold at which an entire economy can be transformed into an AI learning system.

The implication is straightforward. Korea is not merely being asked to supply data. It is being enabled to train, process, and evolve that data domestically. U.S. big tech gains access to real-world data, while Korea acquires the computational infrastructure to convert that data into industrial competitiveness. This is not dependency; it is a calculated win-win structure.

Crucially, the United States does not need to own the data. Access is sufficient. The models and platforms remain American, and global value capture continues to occur at the platform level. Korea, however, faces a different reality. If its data is extracted, the opportunity is lost. But if that data is trained and accumulated domestically, the qualitative level of its industries changes entirely. This is precisely why GPUs are being “given.” Ensuring that computation occurs inside Korea also serves U.S. interests.

China faces a different challenge within this structure. Data is abundant, but hardware is constrained. Access to advanced GPUs and leading-edge semiconductor processes is blocked by export controls. As a result, China has no choice but to pursue internal technological substitution. The problem is that in AI competition, time is the most unforgiving variable. Constraints on compute directly limit learning speed, and slower learning inevitably translates into widening competitive gaps. China must overcome its hardware bottleneck to advance further.

Korea’s task, however, lies elsewhere. While its manufacturing data is world-class, data from non-manufacturing sectors remains underdeveloped. Healthcare, biotech, finance, consumer behavior, urban systems, and public-sector data are still fragmented and underutilized. Yet given structural constraints—aging demographics, shrinking labor supply, and intensifying global competition—the path forward is clear. Korea must datafy its entire economy and transform every sector into an AI learning domain.

All these forces converge toward a single conclusion. The U.S.–China rivalry is no longer about tariffs, trade balances, or exchange rates. It is a competition of AI capability. China must solve its hardware constraints. The United States must secure real-world data. Korea must expand data coverage across its entire economy. Their challenges differ, but the nature of the contest is the same.

In the age of oil, control over oil fields determined power. In the age of data, power belongs to those who can train data and reconstruct industries upon it. Korea now stands at the center of this struggle. This moment is both an opportunity and a test. If computational infrastructure is treated as a strategic asset and governed accordingly, Korea can evolve beyond a manufacturing powerhouse into a true AI industrial nation. If not, another historic inflection point will quietly slip away.

None of what is happening is accidental. Every road now leads to AI.