A Futurist’s View: US Likely to Lose in the Battle Over AI, Robotics, & Eventually Quantum Computing

The United States is in a sticky wicket. Unfortunately, the US is rapidly losing its grip as leader on many fronts compared to our peers around the world in technology and infrastructure. I have witnessed it firsthand while traveling in Asia, Europe, and across the Americas. Now the data is starting to bear this out.

Washington, D.C. Recently I attended The Washington Post Live event entitled “The Futurist – America’s Technological Edge” some notable speakers included Representative Brett Guthrie (R-Kentucky), Kent Walker, President, Global Affairs, Google & Alphabet, Aparna Bawa, COO Zoom, and Martin A. Schmidt, President, Rensselaer Polytechnic Institute. These sessions helped me reflect and hone my thoughts for what I have been tracking, writing, and speaking about over the last several years.

Kent Walker, President, Global Affairs, Google & Alphabet, Aparna Bawa, COO Zoom – credit: Joseph Raczynski

No clearer example of the US waning is in the battle for AI advantage. Last year while attending the Ash Carter Exchange at the DC Convention Center, put on by the Special Competitive Studies Project, numerous panelists from inside our government and the private sector declared that we were two years ahead of China on AI. Fast forward eight months and DeepSeek is released. Two years disappeared quickly. American bravado might just be blinding us from realizing what is happening globally. Additionally, too few people have observed first-hand what the pace of change beyond the US borders looks and feels like with the rapid deployment of incredible infrastructure which honestly makes the US look in general disrepair. The battle for AI supremacy represents one of the most consequential technological competitions of our time, with the gap between the US and China essentially disappearing in recent years. While the US currently maintains advantages by certain metrics, China is advancing rapidly with a more efficient approach. One significant example is the battle in the US over copyrighted materials to be used for training models. There are powerful arguments to prohibit the use of this data for learning, but it would be a clear disadvantage for the US to not allow under fair use, given China and other countries have already used these data points to advance their models.

The technological competition between the United States, Asian, and the MENA (Middle East and North Africa), particularly China, has intensified dramatically in recent years. Evidence suggests that while the US maintains advantages in some specific areas, e.g. Quantum Computing, structural factors may be eroding its technological leadership. In my analysis of recent data, China’s unified strategic approach, massive infrastructure investments, and growing success in recapturing foreign-educated talent present significant challenges to continue US dominance in critical technologies like artificial intelligence, robotics and eventually Quantum Computing. The US faces obstacles stemming from competing interests, political polarization, regulatory fragmentation, and aging infrastructure—all potentially hampering innovation while specific competitors rapidly advance their technological capabilities.

Credit: Telecom Review Africa

The Shifting Landscape of AI Innovation

Current State of Competition

The United States maintains leadership in private AI investment, with American companies investing $67.22 billion in 2023 compared to China’s $7.76 billion (1). American firms also produced more notable machine learning models (61 versus China’s 15 in 2023) (1). That said, China had huge sums being spent by their public sector, which has transformed dramatically in the last two years. In addition, China has established dominance in patent generation, granting nearly three times as many AI patents as the United States between 2017 and 2023—over 44,000 compared to the US’s 15,000 (1).

This patent advantage highlights China’s strategic focus on intellectual property protection and commercialization of AI research. As Kai-Fu Lee noted in “AI Superpowers,” this surge began with President Xi Jinping’s reaction to DeepMind’s victory over the world Go champion in 2016, after which he set specific targets for 2020 and 2025 that put China on a path to dominance in AI by 2030 (2). This triggered a national mobilization that produced remarkable results: “Twelve months after Xi’s directive, investments in Chinese AI startups had topped investments in American AI startups. By 2018, China filed 2.5 times more patents in AI technologies than the United States” (2).

China’s Efficiency Advantage

Perhaps most concerning for US technological leadership is China’s growing efficiency advantage in AI development. Chinese companies are achieving comparable results at dramatically lower costs. Hangzhou-based DeepSeek unveiled its V3 large language model, which rivals OpenAI’s GPT-4 and Anthropic’s Claude 3.5 on various benchmarks, at a training cost of just $5.6 million—what AI pioneer Andrej Karpathy called “a joke of a budget” (3). This stands in stark contrast to US firms like OpenAI and Google that spend hundreds of millions on similar developments (3). While some of their modelling costs have been debunked, as it appears DeepSeek spent close to 100 million, it is far less than OpenAI or Anthropic for their initial models, with inferior chips.

This efficiency stems partly from necessity. As DeepSeek CEO Liang Wenfeng acknowledged, restrictions on advanced semiconductor exports pose significant challenges, yet the company has demonstrated remarkable ingenuity under these constraints (3). By developing efficient methodologies to operate within these limitations, Chinese AI companies have created an asymmetric advantage that could prove decisive in the long-term competition. Another advantage is the Open Source movement that China has embraced, which, in general is side-eyed in the US. We will have to watch to see if this evolves soon.

Credit: Bernard Marr

Quantum Computing: A Complex Competitive Landscape

The race for quantum supremacy presents a more nuanced competitive picture, with different countries leading in specific aspects of quantum technologies.

Differentiated Areas of Leadership

The quantum technology landscape reveals varying patterns of dominance. According to comprehensive analyses, “China leads in quantum communication and matches the U.S. in quantum sensing, but lags behind in quantum computing, particularly in hardware and practical systems” (4). This differentiation shows how countries have strategically focused their quantum efforts on different applications.

In quantum communications, China has demonstrated global leadership through projects like the 1,200-mile Beijing-Shanghai quantum key distribution (QKD) network and the groundbreaking Micius satellite, which extends quantum communication over even greater distances (5). These achievements put China at the forefront of secure, long-distance quantum communications technology.

Funding and Approach Differences

The funding models for quantum research differ dramatically between the US and China. While private sector investment in quantum technology in China “pales in comparison to that in the United States” with only $44 million in capital compared to $1.28 billion for US startups (5), China claims over $15 billion in public funding for quantum R&D (4), offsetting the US advantage in private funding.

China’s approach to quantum development is markedly different—more centralized and increasingly under state control. Recent exits of large Chinese tech companies from quantum research signal “a broader push by the state to tighten control over quantum R&D in China. Both Alibaba and Baidu have shut down their quantum research divisions, transferring their assets to state-linked institutions” (5). This consolidation allows China to direct quantum research toward national strategic objectives, potentially accelerating development in targeted areas.

Structural Differences in Innovation Models

The fundamentally different approaches to innovation between the US and China may play a decisive role in determining future technological leadership.

China’s Unified Strategic Approach

China’s technological development is characterized by state-centric coordination. Government funding accounts for approximately 60% of financial inflows into China’s science and technology ecosystem, while in the US, 72% of R&D funding came from the private sector as of 2019 (6). This allows Chinese authorities to direct resources toward strategic priorities.

China’s centralized approach “enables a strategic concentration on crucial industries and technologies, accelerating the development of sectors considered vital for national interests, like AI and sustainable energy” (6). The designation of national champions—Baidu, Alibaba, Tencent, iFlytek, and SenseTime—in AI development exemplifies this approach (2). This coordination creates a unified front for technological advancement aligned with national goals.

US Fragmentation and Competing Interests

In contrast, the United States faces challenges from competing interests and regulatory fragmentation. The American system requires coordination between academic research, government grants, venture capital, and free market competition, but faces obstacles with divergent priorities at federal, state, and local levels (7). This complexity can slow decision-making and reduce coherence in technological strategy.

Political hyperpolarization further complicates US innovation: “The central problem in American society today is hyper-polarization…The more proximate the tech business model is to polarization, the greater the reputational and regulatory risks” (7). This political division directly impacts the tech sector, affecting policy decisions and creating an unstable environment for long-term investments.

The Infrastructure Gap

Perhaps no area demonstrates the stark contrast between the US and its Asian competitors more clearly than infrastructure quality, which directly impacts technological competitiveness.

America’s Crumbling Foundation

American infrastructure has fallen dramatically behind global standards. According to the World Economic Forum, the United States “ranks 18th in railroads, 19th in ports, 20th in roads, 30th in airports, and 33rd in the quality of our electrical system” (8). This deterioration creates significant economic costs—in 2010 alone, “Americans spent a total of 4.8 billion hours stuck in traffic, wasting 1.9 billion gallons of fuel, at a total cost of $101 billion” (8). These number a bit on the older side, and yet, they have not improved over the last decade.

Beyond transportation networks, America’s innovation infrastructure itself is deteriorating. At the National Institute of Standards and Technology (NIST), “more than half of the facilities on [its] two main campuses are in poor to critical condition. Older NIST labs are unable to support controlled environments required for advanced research” (9). Similarly, at NASA, “more than 80% of its infrastructure and facilities are beyond their constructed design life” (9). In the last two months, through the DOGE initiative, more constraints are being placed on these institutions.

Asia’s Infrastructure Advantage

In stark contrast, many Asian nations have built world-class infrastructure systems. In the 2024 infrastructure rankings, Singapore (4th), Hong Kong (9th), Taiwan (10th), South Korea (11th), and China (15th) all score highly (10). China’s high-speed rail network dramatically outpaces the US system in both size and speed—exceeding 24,000 miles compared to America’s 456 miles.

This infrastructure advantage directly enhances technological competitiveness. Digital infrastructure specifically “enhances the capacity for technological innovation, thereby facilitating the growth of new quality productivity” (10). Studies show that digital infrastructure promotes innovation through “fostering technological innovation, improving resource allocation efficiency, and enabling industrial structural upgrading” (10). Countries investing more heavily in infrastructure gain significant advantages in technological development and deployment speed.

The Shifting Talent Landscape

The global flow of scientific and technological talent represents another critical dimension of technological competition.

Changing Patterns of Student Return

While the United States has historically benefited from educating international students who remained after graduation, this pattern is shifting significantly. Although the US initially retains 72-73% of international STEM graduates under the Optional Practical Training program, data suggests that “as many as 70,800 of the 104,000 international STEM graduates from U.S. universities in 2021 will eventually leave the country” (11).

This trend is particularly pronounced for Chinese students. Return rates have increased dramatically from approximately 5% in 1987 to over 80% since 2012 (12). This reversal is driven by “China’s prospering economy, strategic talent policies and the large sum of funding it has poured into scientific research” (12). It is also projected that visas in the US over at least the next several years will become increasingly difficult to obtain and renew.

Family and Cultural Factors

Research consistently shows that personal and cultural factors play a significant role in these return decisions. According to studies of international students, “the factors that led them to return home primarily concerned family and culture” (11). For Chinese students specifically, “the drive to seek better employment conditions and career prospects in Chinese academia is consistently high among early career academics” (12).

The generational dimension is particularly noteworthy: “most belong to China’s one-child generation who shoulder heavier filial responsibilities than those born before the country enforced the one-child policy in the late 1970s” (12). This creates strong incentives for Chinese graduates to return home.

Regulatory Environments and Innovation

The contrasting regulatory approaches between the US and China may have profound implications for their innovation trajectories.

China’s Regulatory System

China employs a “centralized, comprehensive, state-driven approach prioritizing national security and digital sovereignty” (13). This has given China an early-mover advantage in regulating emerging technologies like AI through comprehensive frameworks.

While China’s approval processes are typically “2.5 times longer than in the US” (13), its regulatory approach is “iterative and sectoral, allowing for adjustments with each new step” (13). This creates a more predictable environment for companies, even if individual processes may take longer.

EU AI Act

US Regulatory Fragmentation

The United States adopts a “fragmented, market-driven, self-regulatory framework emphasizing innovation and economic freedom” (13). This has resulted in a patchwork regulatory system where different agencies have overlapping jurisdictions, creating confusion and inconsistency.

As one analysis notes, “the United States Congress has taken a relatively hands-off approach to regulating AI thus far… The country’s regulatory framework is largely based on voluntary guidelines like the NIST AI Risk Management Framework and self-regulation by the industry” (13). While this approach promotes innovation in the short term, it may create longer-term challenges for coherent technological development.

The “AI-tocracy” Model and Technological Development

Recent research has identified a potentially transformative relationship between governance models and AI development that may further accelerate China’s technological advancement.

Mutually Reinforcing Relationship

The concept of “AI-tocracy” describes a potentially mutually reinforcing relationship between autocratic governance and AI innovation. Empirical research from China demonstrates this operates in two directions: “AI innovation entrenches the regime, and the regime’s investment in AI for political control stimulates further frontier innovation” (2). You are seeing this all over the Middle East – Dubai and Abu Dhabi as well as in Saudi.

This creates a sustainable innovation cycle where political applications drive commercial innovation: “local unrest leads to greater government procurement of facial recognition AI, and increased AI procurement suppresses subsequent unrest…the contracted AI firms innovate more both for the government and commercial markets” (14). This cycle helps explain how China has rapidly advanced in fields like facial recognition technology.

Data Advantage and Innovation Spillovers

The “AI-tocracy” advantage is amplified by China’s approach to data collection and sharing. Government data becomes “an input into developing AI prediction algorithms and can be shared across multiple purposes” (14), allowing surveillance technologies to later be repurposed for commercial applications.

As the Belfer Center analysis notes, “Because a primary asset in applying AI is the quantity of quality data, China has emerged as the Saudi Arabia of the twenty-first century’s most valuable commodity” (2). This data advantage, combined with China’s unified approach to technological development, creates powerful synergies that could accelerate future innovation.

DJI Drone

Robotics: Asia’s Strategic Dominance and US Challenges

In robotics, there is no single better example than that of DJI for China’s advantage. A company based in Shenzhen, China, they have products that I have used for the better part of the last 10 years. They have innovated beyond any other global drone technology company, to the extent that their consumer products are being used in some of the biggest conflicts occurring right now for military operations. Robotics exemplifies the structural advantages of Asian technological ecosystems, with China now leading global industrial robot installations (51% of global deployments in 2023) and domestic manufacturers capturing 47% of China’s market—up from 17% in 2015 (15). This contrasts with U.S. struggles to scale robotics innovation due to fragmented R&D, ethical debates, and lagging infrastructure.

China’s Robotics Surge

China’s robotics dominance stems from:

Strategic state coordination: The “Made in China 2025” plan prioritized robotics as a core industry, driving domestic robot density to 470 units per 10,000 workers—surpassing Germany (429) and Japan (419) (15). By 2023, China produced 430,000 industrial robots annually and holds 66% of global robotics patents (15).
Cost and scale advantages: Chinese manufacturers like Siasun and ESTUN offer industrial robots at 30-50% lower prices than Western counterparts, accelerating adoption in SMEs (15).
AI integration: Partnerships like Taiwan’s Spingence and Japan’s Forcesteed Robotics deploy edge AI for real-time robotic decision-making, enabling autonomous navigation in unstructured environments (16).

Case study: The Beijing-Shanghai quantum communication network now integrates AI-driven logistics robots, achieving 99.99% sorting accuracy in warehouses—a capability still experimental in U.S. facilities (16).

U.S. Robotics Challenges

The U.S. faces systemic hurdles:

Fragmented R&D: While Asia invests in centralized robotics clusters (e.g., China’s 8-10 planned industrial zones (17)), U.S. research remains siloed. Google’s abandoned “arm farm” project highlights wasted resources due to lack of hardware standardization (18).
Infrastructure gaps: Only 15% of U.S. warehouses are automated versus 80% in China’s major logistics hubs (19).
Ethical paralysis: Debates over job displacement slow adoption—U.S. cobot installations grew just 12% in 2024 vs. China’s 34% (19). Meanwhile, China’s “Robot+” Action Plan openly replaces 4.5 million manufacturing jobs annually with automation (15).

Talent and Strategic Alliances

Asia leverages returning talent and cross-border partnerships:

80% of Chinese robotics PhDs educated abroad now work domestically, fueling companies like the aforementioned DJI and Ubtech.
Japan-Singapore collaborations combine Japan’s precision hardware (52% of global robot supply (17)) with Singapore’s AI algorithms, creating hyper-flexible manufacturing bots now penetrating European markets (16).

Funding Divergence

China: $15B+ public robotics funding since 2021, targeting 20% annual industry growth (15).
USA: Reliant on private VC ($1.28B in 2023 vs. China’s $44M (15)), creating innovation gaps in capital-intensive areas like humanoid robots.

Conclusion: Future Technological Leadership

The evidence suggests that while the United States currently maintains a minuscule technological lead for the moment, structural factors may erode this slight advantage. China’s unified strategic approach, massive infrastructure investments, and growing success in recapturing foreign-educated talent present significant challenges to continued US dominance in critical technologies.

The US model offers advantages in creativity, entrepreneurship, and market-driven innovation. However, competing interests, political polarization, regulatory fragmentation, and aging infrastructure create obstacles to maintaining technological leadership. As the Stanford Global Vibrancy Tool notes, “The U.S. has the world’s most robust AI ecosystem and outperforms every other country by significant margins” (1), yet this advantage appears to be on the verge of disappearing.

With regard to robotics, the analysis reinforces the original thesis: Asia’s unified strategies and infrastructure investments enable rapid scaling, while U.S. fragmentation and ethical debates slow critical technologies. China’s robotics sector—projected to grow 20% annually through 2025—now directly supports its AI and quantum ambitions through integrated systems like AI-optimized quantum key distribution networks.

The difference in innovation approaches between the US and China will likely lead to varying advantages in different technological domains. China’s unified, state-driven approach may accelerate development in areas requiring large-scale coordination and data sharing, while the US may maintain advantages in domains requiring decentralized creativity and breakthrough innovations, though with AI on the verge of breeding innovation itself this might mute the US traditional advantage. The ultimate outcome of this technological competition remains uncertain, but based on the emerging data and trends, it appears that the US will likely fall short of being the global leader in these core technologies in the years ahead.

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