In late 2025, a Fox News op-ed argued that the next global arms race would not be measured in missiles or warheads but in computing power. The piece warned that the United States risks losing ground to competitors in what it called the “compute race”—the battle for supremacy in chips, data centers, and artificial intelligence infrastructure. Though the argument is cast in dramatic terms, it reflects a fundamental economic and geopolitical reality: compute has become both a source of national power and a determinant of future growth. What oil was to the 20th century, high-performance computing is to the 21st—fueling everything from scientific research and defense systems to the algorithms that govern commerce, transportation, and communications.
From a macroeconomic standpoint, compute is not merely a technological resource but a form of strategic capital stock. The infrastructure that supports machine learning—semiconductors, cloud platforms, edge networks, and data centers—has measurable effects on productivity and gross domestic product (GDP). Research from MIT’s Initiative on the Digital Economy (2024) found that countries with sustained compute investment grew 0.3–0.5 percentage points faster annually in total factor productivity than those with stagnant digital infrastructure. This advantage compounds: compute-rich economies attract foreign investment, enable advanced research, and generate positive externalities across industries.
The new economics of compute is grounded in three reinforcing mechanisms: scale, spillover, and sovereignty. Scale determines cost advantage; spillover drives innovation and diffusion; sovereignty ensures control over data and systems. When these align, nations achieve not only digital competitiveness but macroeconomic resilience.
Consider the United States, which currently hosts roughly one-third of global hyperscale data centers. According to the U.S. Bureau of Economic Analysis, investment in data center construction and equipment grew by 19 percent in 2024, outpacing all other categories of non-residential investment. J.P. Morgan analysts estimate that such spending added roughly 0.2 percentage points to GDP growth, driven largely by AI-related infrastructure build-out. These figures underscore the argument made in the Fox News article: compute expansion is not a niche phenomenon but a structural growth engine.
Case studies reinforce this trend. In the U.S. Midwest, Microsoft’s AI-focused data centers in Wisconsin and Iowa have catalyzed regional energy and real estate investments. The projects have created multi-year employment pipelines in construction, maintenance, and renewable energy supply chains. A University of Chicago study (2024) found that every $1 billion invested in regional cloud infrastructure generated nearly $750 million in secondary economic activity within three years—demonstrating how compute infrastructure acts as a multiplier across local economies.
Meanwhile, on the global stage, China’s National Integrated Computing Network Initiative has built data center clusters across 10 provinces, linking them via high-speed fiber into what officials call a “national computing backbone.” The project integrates cloud and edge processing for AI and industrial automation. According to Tsinghua University’s 2025 Digital Economy Yearbook, compute capacity in these regions has risen by 70 percent since 2020, contributing an estimated 1.2 trillion yuan to GDP and positioning China as a dominant node in global AI supply chains. The country’s model shows how state-directed capital and industrial policy can fuse compute expansion with national economic planning.
Europe offers a contrasting picture. The European Commission’s GAIA-X initiative aims to develop a federated cloud and data infrastructure that maintains sovereignty and interoperability. Yet despite strong regulatory frameworks, the continent still lags behind the U.S. and China in sheer compute scale. Researchers at the London School of Economics argue that fragmented investment and energy-cost disparities have constrained Europe’s ability to compete globally. In this sense, compute inequality is becoming a structural driver of regional economic divergence.
Academic research increasingly frames this divide as a macro-structural issue akin to capital accumulation. A 2025 OECD study, The Compute Economy: Capital Formation in the Digital Era, characterizes compute capacity as a fourth factor of production—alongside labor, land, and traditional capital. The study estimates that the elasticity of GDP with respect to compute capital is roughly 0.18 across advanced economies, meaning that a 10 percent increase in compute capacity yields a 1.8 percent boost in GDP, on average. These findings support the view that digital infrastructure has entered the realm of macroeconomic policy, warranting inclusion in long-term national accounting.
Yet the race for compute supremacy is not without complications. Data centers are enormously energy-intensive: the International Energy Agency projects that by 2026, global data centers will consume as much electricity as Japan. In the United States alone, AI-focused data facilities could account for up to 9 percent of total power demand by the decade’s end. The environmental trade-offs are acute. Policymakers now face a paradox—how to expand compute capacity without violating carbon-reduction commitments. Companies are experimenting with innovations such as liquid cooling, waste-heat recovery, and colocation with renewable-energy plants. Google’s Nevada facility, for instance, runs on 90 percent solar power and integrates AI to optimize cooling efficiency.
Capital intensity also remains a barrier. Constructing an advanced hyperscale center can exceed $10 billion, while cutting-edge chip fabrication plants—such as TSMC’s facility in Arizona—can surpass $20 billion. These are investments that only a handful of corporations or state-backed coalitions can afford. The economic structure of compute production therefore favors concentration. A Brookings Institution report (2025) warns that excessive reliance on a few vendors—particularly in GPU and chip manufacturing—creates systemic risk analogous to oil dependency in the 1970s.
There are also deep security and sovereignty implications. When nations depend on foreign cloud providers for critical workloads, they effectively outsource control over data governance, compliance, and even operational continuity. The “digital sovereignty” movement, emerging across Europe and parts of Asia, reflects anxiety over this dependence. Countries such as India and Brazil have responded by promoting domestic data-hosting requirements and sovereign cloud frameworks to retain economic and security autonomy.
On a broader level, the global compute race mirrors patterns seen in earlier technological revolutions. Economists often liken the current phase to the electrification wave of the early 20th century—an infrastructural transformation that redefined productivity across every sector. In both cases, early adopters captured durable competitive advantage through network effects and capital deepening. The difference today is the speed of compounding. Moore’s Law may be slowing, but the aggregate capital invested in compute is expanding exponentially. The International Monetary Fund’s 2025 World Digital Outlook notes that digital capital now constitutes over 15 percent of total global investment, up from just 6 percent a decade earlier.
The consequences for labor and welfare are also significant. Compute concentration drives regional inequality between high-tech clusters and peripheral regions. However, compute infrastructure also generates positive welfare effects through job creation and service access. In Finland, the repurposing of an old paper mill into a Google data center revitalized a declining industrial town, increasing municipal tax revenue and enabling new training programs for digital skills. Similar cases in Texas, Singapore, and Ireland show that compute ecosystems can serve as catalysts for local reinvention when coupled with policy support and education.
In the policy sphere, macroeconomic planners are beginning to view compute investment as a lever of long-term resilience. The U.S. CHIPS and Science Act exemplifies this approach, channeling $52 billion toward domestic semiconductor production. Combined with tax incentives for data centers and renewable-energy integration, such policies aim to ensure that compute capacity remains both sovereign and sustainable. Economists at the Peterson Institute argue that if such programs sustain even moderate productivity spillovers, they could add 1 percent to U.S. GDP by 2030.
Ultimately, the Fox News assertion that “America cannot afford to fall behind” captures the essence of a global transformation. Compute infrastructure now defines competitive advantage at the intersection of economics, geopolitics, and technological sovereignty. Nations investing strategically in computing capital are effectively shaping their macroeconomic future—determining who controls the pipelines of data, the algorithms of commerce, and the engines of innovation.
The new arms race is not fought with military arsenals but with GPUs, fiber, and power grids. The balance of global economic power may hinge on which nations can transform compute capacity into broad-based productivity rather than narrow advantage. For policymakers, the challenge will be ensuring that this infrastructure arms race produces not just more powerful machines, but a more inclusive and resilient global economy.
Key Takeaways
- Compute capacity now functions as strategic economic capital, influencing GDP, productivity, and national competitiveness.
- Case studies in the U.S., China, and Europe demonstrate divergent strategies for compute investment and sovereignty.
- Academic research shows that compute elasticity contributes up to 1.8 percent to GDP for every 10 percent gain in capacity.
- Energy consumption, capital intensity, and concentration of supply chains pose significant risks.
- Sustainable and sovereign compute strategies will determine which economies thrive in the AI-driven future.
Sources
- Fox News — The New Arms Race Is for Compute — America Can’t Afford to Fall Behind — Link
- OECD — The Compute Economy: Capital Formation in the Digital Era — Link
- MIT Initiative on the Digital Economy — Digital Infrastructure and Productivity Growth — Link
- Brookings Institution — The Economic Multiplier of Cloud Infrastructure Investment — Link
- University of Chicago — Regional Spillovers from Cloud Infrastructure — Link
- International Energy Agency — Data Centers and the Energy Transition — Link
- IMF — World Digital Outlook 2025 — Link
