Building Digital Empires: Is the US Losing Ground to China in the Data Infrastructure Race?

Article by Mrityunjay Goswami and Sudhanshu Kumar

In July 2025, the Trump Administration introduced two transformational executive orders under the “America’s AI Action Plan” to cement US dominance in artificial intelligence and virtual digital assets. These two key executive orders streamline federal approval for large-scale construction of data centres and advance blockchain technology adoption, signalling a strategic push to adopt digital assets, coupled with an AI race. Experts are viewing it as a point of recalibration where the US now thinks that if they will not accelerate the pace of AI development, China will catch up in no time.

The executive order for Accelerating Federal Permitting of Data Centre Infrastructure under the AI Action Plan aims to strengthen next-generation AI inference or synthetic data generation with digital assets ecosystem, build American AI infrastructure, and lead international AI diplomacy and security. The symbiotic adoption of building AI data centres and strategic reserves for digital assets underscores the United States’ commitment to ‘achieve global dominance in Artificial Intelligence’, establishing itself as the epicentre of “Global Bitcoin Strategic Reserves”, as stated by President Trump. The decreasing dependency of the countries on the dollar and the emerging de-dollarisation narrative due to the tariff wars require a new way to balance out the strategic interests of the US in trade and commerce. Interestingly, this Global Bitcoin Strategy seems to be a plausible strategy from the American establishment to maintain its hegemony in geo-economics.

The strategic interaction of AI data centres with digital asset reserves positions the United States as a frontrunner in global AI dominance, adoption, and regulation of digital assets. By easing regulatory constraints, such as environmental statutes, and federal adoption of digital dollars, this policy enhances the United States’ ability to develop robust digital financial technologies and accelerate the adoption of advanced Artificial Intelligence. The US is running fast to maintain its position in both the fields of AI and Blockchain, as one is essential to its national security and the other is to its economic security. The rise of China in both areas has raised deepening concerns about the future of the US as a global policeman. Whether this will be a helpful strategy in maintaining the long-term strategic interest of the US or not, only time will tell, but the US also doesn’t have any other option than to rely on investing heavily in these technologies. 

Building Large Data Centres and Adoption of Digital Assets

The Biden Administration signed an executive order in January 2025, directing the Department of Defence to identify three federal sites for private-sector-driven AI data centre development. Following Biden’s policy, one of the early decisions by President Trump was an announcement of a $20 billion plan to fund new data centres in states like Texas, Ohio, and Arizona. This policy is in action due to the fact that approximately 75% of global semiconductor manufacturing capacity is concentrated in China and East Asia, with 100% of the world’s most advanced (below 10 nanometers) semiconductor manufacturing capacity located in Taiwan (92%) and South Korea (8%). This creates severe single points of failure vulnerable to natural disasters, infrastructure shutdowns, or international conflicts. The US establishment wants to reduce this critical vulnerability in the AI race at any cost and is looking forward to making the process of chip development and production entirely indigenous and local.

The rising tensions in the South China Sea and the critical conditions associated with the state of Taiwan, in addition to the problems of the TSMC as a single point of failure in the global supply chain of semiconductor chips, have made it imperative for the US to go in this direction only.  Interestingly, due to this, one could see a functional consistency in Biden-Trump policies that reflects the United States’ effort to maintain strategic, economic, and technological dominance over artificial intelligence research. However, building large data centres requires not only logistical strength but also the ability to withstand threats like cyberattacks and data breaches and provide green energy solutions to power such massive data assets. These problems are multidimensional and multifaceted, and there exists no one solution, but to apply everything and see what works and what does not. On top of that, the race to build the AGI and ASI is no less than building nuclear weapons. What nuclear weapons hold for the level of capacity to create devastation in the physical world, the possession of ASI is no less devastating in the realm of cyber.

Strategic Advantages

The integrated approach under the larger AI-Framework reflects serious strategic considerations. The GENIUS Act and STABLE Act, which became law in July 2025, aim to establish a clear regulatory framework for virtual assets, signalling a proactive approach to integrating into an AI-driven digital ecosystem. This strategy highlights the United States’ efforts to reduce dependency on competitors like China, where strict AI oversight, allegations of data theft, and ambiguous regulation on digital assets pose significant challenges. For example, a July 2025 ProPublica investigation revealed that China-based data engineers employed by Microsoft were accused of stealing sensitive information from DOD-controlled cloud systems, risking the United States’ critical security infrastructure.

As the US-China technological gap narrows, the accelerated adoption of digital “strategic assets” and advancement in the AI race remain central to US technoeconomic and security policy, as acknowledged by Trump’s AI and Crypto Czar, David Sacks, in the Paris AI Action Summit. The timeline pressure is acute in the race to AGI, and China’s rapid advancement in both AI capabilities and digital currency infrastructure means that American hesitation or implementation delays could result in permanent strategic disadvantage in these critical technology domains. Though the time for maintaining technological leadership appears to be shrinking rapidly, making resolution of these policy constraints and market limitations an urgent national priority.

Additionally, The Trump Administration’s AI Action Plan addresses critical workforce shortages by establishing a comprehensive national initiative led by the Department of Labor and Commerce to identify and develop training frameworks for “high-priority occupations” essential to AI infrastructure, particularly electricians, advanced HVAC technicians, data center operators, and specialized manufacturing roles that will build and maintain the expanding network of data centers and semiconductor facilities. On reading the policy document it is visible that the plan significantly expands Registered Apprenticeships programs across multiple states, creating industry-driven training partnerships between employers, state governments, and workforce stakeholders to ensure workers can transition into these high-paying technical positions while establishing early career pipelines through career and technical education programs for middle and high school students. However, the initiative faces the fundamental challenge of preparing workers for roles that are still evolving as AI infrastructure develops, requiring the newly established AI Workforce Research Hub under DOL to continuously evaluate labor market impacts through scenario planning and provide “actionable insights” for workforce policy adaptation—essentially training people for jobs that may not fully exist yet while racing against the rapid pace of technological change that could render some skill sets obsolete before training programs are even completed.

Policy Constraints and Market Volatility

The biggest policy concern in this regard is about the “compute access inequality”. It is because the financial market for computing remains immature, requiring companies seeking large-scale computing to sign “long-term contracts with hyperscalers, which is far beyond the budgetary reach of most academics and many startups”. This concentrates AI development capabilities among established hyperscale providers, limiting innovation ecosystem diversity. On top of that, while the plan emphasizes strategic digital asset reserves, practical integration faces significant obstacles. Cryptocurrency mining operations consume substantial energy resources, which is potentially around 63 terawatt-hours annually for Bitcoin alone and that will be competing directly with AI data centres for limited power generation capacity. Furthermore, technical constraints limit the effectiveness of integrated AI-digital asset systems, especially due to the Blockchain scalability issues. It is important to acknowledge that current blockchain networks face fundamental throughput limitations that constrain real-time AI applications. Most blockchain systems cannot handle the high-frequency data processing requirements of advanced AI workloads. Energy consumption from proof-of-work systems compounds power grid constraints already stressed by AI data centres.

However, it is also worth noting that more critically, the integration of Bitcoin strategic reserves into this framework creates a monetary paradox: while proponents argue that a bitcoin-backed dollar could strengthen U.S. financial hegemony by countering Chinese digital currency initiatives and attracting global capital flows, critics warn that legitimizing cryptocurrency as a strategic asset may accelerate de-dollarization trends by providing nations with alternative settlement mechanisms that bypass traditional dollar-centric systems. The economic calculus thus hinges on whether the projected productivity gains from AI infrastructure which is estimated to contribute up to $500 billion annually to economic output can offset the potential destabilization of dollar dominance and the concentration of technological power among a handful of hyperscaler giants, creating a high-stakes gamble where success could cement American technological supremacy while failure might accelerate the very financial and technological displacement the policy seeks to prevent.

Conclusion

Whether this aggressive investment in AI infrastructure and digital assets will successfully maintain America’s long-term strategic interests remains an open question that only time will answer. But as China rapidly advances in both AI capabilities and digital currency infrastructure, American hesitation or implementation delays could result in permanent strategic disadvantage in these critical technology domains. In this high-stakes competition for technological supremacy, the United States has chosen to bet its future on innovation, infrastructure, and the transformative power of American ingenuity. The window for maintaining technological leadership appears to be narrowing rapidly, making the resolution of policy constraints and market limitations not just a priority, but an urgent national imperative.

The race to maintain hegemony through brute-force infrastructure development and speculative digital asset accumulation may ultimately accelerate the very technological and economic decline it seeks to prevent. Whether this strategy represents visionary leadership or dangerous overreach will depend largely on whether American policymakers can recognize and correct these fundamental contradictions before they become irreversible constraints on the nation’s technological future. [End]