Many are concerned about the potential negative impact on American AI companies if China takes the lead in global AI development, particularly in the transport and industry sectors.
There is a realistic concern that if China takes the lead in global AI development, particularly in areas like transportation and industry, American AI companies could face substantial losses and challenges.
Here's why and what aspects of the US-China AI competition contribute to this potential outcome:
Market Share and Global Adoption: China is actively pursuing the global adoption of its AI models and systems, particularly in developing nations, through initiatives like the Digital Silk Road and its Belt and Road Initiative. If China succeeds in embedding its AI technologies as the standard in these regions, it could mean lost market share and earnings for American firms.
Government Support and Industrial Policy: China's centralized government strategy strongly supports domestic AI development, including subsidies, research funding, and a focus on integrating AI into various sectors like manufacturing, healthcare, and autonomous vehicles. This contrasts with the US's approach, which is more reliant on private sector innovation with less government intervention, according to Forbes. This difference in government support could give Chinese companies a competitive edge in scaling and deployment, particularly in emerging markets.
Talent and Compute Infrastructure: Both the US and China recognize the importance of talent and computing power for AI leadership. China is investing in attracting global talent and building robust computing infrastructure, including its National Integrated Computing Network. While the US currently leads in large-scale AI development and access to cutting-edge computing, China's efforts to close the gap are rapidly expanding.
Alternative AI Strategy and Open-Source Models: China is also exploring alternative AI development strategies, including embracing open-source AI models. While the US has traditionally focused on closed, tightly controlled AI systems, China's open-source approach, combined with the efforts of companies like DeepSeek to create efficient and accessible models, could make Chinese AI solutions more attractive globally, particularly to countries wary of US restrictions or seeking cost-effective alternatives.
Impact on Global Supply Chains: AI can significantly transform global supply chains and trade. If China leads in developing and implementing AI-driven solutions for logistics and manufacturing, its companies could gain an advantage in global trade, potentially impacting American companies involved in these sectors.
Mitigating factors and US strategy
Despite the potential for losses, it's important to consider some mitigating factors and the US's efforts to maintain its lead in AI:
US Lead in Foundational AI Models: The US currently maintains a lead in developing large-scale, cutting-edge AI models, with more notable models than China in 2024.
Focus on Innovation and Research: The US continues to emphasize innovation and research in AI, aiming to maintain its technological edge.
International Cooperation and Standards: The US is seeking to engage with China on AI projects while also working with democratic allies and partners to develop robust AI norms and standards, aiming to shape the future of AI governance and deployment.
Addressing Challenges and Strengthening the Ecosystem: The US government is focused on addressing challenges like talent development, ensuring adequate energy supply for data centers, and fostering university and startup access to high-performance AI compute.
Conclusion
The potential for China's AI leadership in transport and industry to negatively impact American AI companies is a significant concern. China's strategic approach, including government support, focus on practical applications, and global outreach, could pose a serious challenge to US dominance in the AI landscape. However, the US is actively working to maintain its lead through innovation, talent development, and international collaboration.
Ultimately, the future of the global AI landscape will depend on how the US and China navigate this complex and multifaceted competition, balancing innovation, competition, and potential collaboration to shape the future of AI development and its impact on the world.
“In the past two weeks one big tech company after another reported blowout earnings amid a wholesale embrace of artificial intelligence.
Look a little closer, and a more unsettling side to the AI boom emerges. All the spending on chips, data centers and other AI infrastructure is draining American corporations of cash.
This underscores the hidden risks from the AI boom. No one doubts its potential to raise growth and productivity in the long run. But financing that boom is straining the companies and capital markets.
Since the first quarter of 2023, investment in information processing equipment has expanded 23%, after inflation, while total gross domestic product has expanded just 6%. In the first half of the year, information processing investment contributed more than half the sluggish 1.2% overall growth rate. In effect, AI spending propped up the economy while consumer spending stagnated.
Much of that investment consists of the graphics-processing units, memory chips, servers and networking gear to train and run the large language models at the heart of the boom. And all that computing power needs buildings, land and power generation.
This is transforming big tech's business models.
For years, investors loved those companies because they were "asset-light," earning profits on intangible assets such as intellectual property, software and digital platforms with "network effects." Users flocked to Facebook, Google, the iPhone, and Windows because other users did. Adding revenue required little in the way of more buildings and equipment, making them cash-generating machines.
This can be seen in free cash flow, roughly cash flow from operations minus capital expenditures.
This is arguably the purest measure of a business's underlying cash-generating potential. Amazon.com, for example, tells investors: "Our financial focus is on long-term, sustainable growth in free cash flow."
From 2016 through 2023, free cash flow and net earnings of Alphabet, Amazon, Meta Platforms and Microsoft grew roughly in tandem. But since 2023, the two have diverged.
The four companies' combined net income is up 73%, to $91 billion, in the second quarter from two years earlier, while free cash flow is down 30% to $40 billion, according to FactSet data.
For all of AI's obvious economic potential, the financial return remains a question mark. OpenAI and Anthropic, the two leading stand-alone developers of large language models, though growing fast, are losing money.
Much of big tech companies' latest profits reflect their established franchises: ad spending for Meta and Alphabet, the iPhone for Apple. As to when their AI hardware will pay off, they counsel patience.
Meta reported a 36% rise in earnings for the second quarter, but a 22% drop in free cash flow. Amazon in the past year has ramped up investment in Amazon Web Services, which hosts data and runs AI models for outside clients, and free cash flow is down by two-thirds from the previous year.
For now, investors are pricing big tech as if their asset-heavy business will be as profitable as their asset-light models.
A dot-com-style bust looks far-fetched. AI's big spenders are mature and profitable, and the demand for computing power exceeds the supply. But if their revenue and profit assumptions prove too optimistic, their pace of capital spending will be hard to sustain.
After the global financial crisis, big tech was both a beneficiary of low interest rates, and a cause. These companies were generating five to eight times as much cash from operations as they invested, and that spare cash was recycled back into the financial system, Jason Thomas, head of research at Carlyle Group, estimates. It helped hold down long-term interest rates, as did inflation below the Federal Reserve's 2% target and the Fed buying bonds. Low interest rates, in turn, made investors value these companies' future profits even more.
Today, government deficits are larger, inflation is above 2% and the Fed has been shrinking its bondholdings. Meanwhile, corporations face steep investment needs to exploit AI and reshore production to avoid tariffs.
Thomas estimates that since 2020, their cumulative free cash flow has been 78% lower, relative to GDP, than in the equivalent period following 2009.
All this suggests interest rates need to be substantially higher in the years ahead than in the years before the pandemic. That is another risk to the economy and these companies that investors may not fully appreciate.” [1]
1. U.S. News -- Capital Account: Boom in AI Carries Hidden Economic Risk. Ip, Greg. Wall Street Journal, Eastern edition; New York, N.Y.. 05 Aug 2025: A2.
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