Global Investors Remain Exposed to US-China AI Competition

Global investors remain financially exposed to both the United States and China as the two countries compete over artificial intelligence, semiconductors and the infrastructure needed to develop advanced AI systems.

The investment relationship is notable because Washington and Beijing are simultaneously trying to strengthen their own technology ecosystems and reduce strategic dependence on the other side. Recent Reuters reporting found that financial links between the two markets remain substantial despite restrictions on technology transfers and growing geopolitical tensions.

The situation creates a complicated environment for investors. Capital continues to move toward companies and assets benefiting from AI growth, while government policies increasingly determine which technologies can be exported, financed or accessed across borders.

Investors continue to operate across both ecosystems

Reuters reported that US banks facilitated $17.2 billion in Chinese high-tech initial public offerings in 2026, representing nearly 30% of total issuance in that sector.

At the same time, holdings of US semiconductor stocks by investors from mainland China and Hong Kong had exceeded $750 billion, according to the Reuters report.

Those figures illustrate the degree to which financial markets remain interconnected even while governments are pursuing greater technological separation.

Investment exposure does not necessarily mean that individual investors support either country’s technology strategy. It can reflect portfolio diversification, market access, expected returns or the availability of investment vehicles.

AI has become a strategic technology

Artificial intelligence has moved beyond being solely a technology-sector investment theme.

Governments increasingly treat advanced computing, semiconductors, data centres and AI models as strategic assets because they have applications in industry, national security, scientific research and defence.

The US government has explicitly linked semiconductor supply chains to national security and AI development. A January 2026 presidential proclamation said advanced computing chips are important to the country’s AI and technology policies and introduced measures intended to encourage domestic semiconductor capacity.

China, meanwhile, is pursuing greater self-reliance across its AI technology stack, including chips, models and data-centre infrastructure.

China is expanding its domestic AI capabilities

Chinese technology companies are continuing to invest heavily in AI despite restrictions affecting access to some advanced foreign chips.

Alibaba announced in September that it was developing a next-generation AI model with between 5 trillion and 10 trillion parameters and unveiled a new AI chip called the Zhenwu V900.

The company said the chip was expected to enter mass production in early 2027 and that it was targeting more than 20 gigawatts of Alibaba Cloud data-centre capacity by 2032. Alibaba shares rose 5.1% following the announcements, according to Reuters.

The announcements demonstrate the effort by major Chinese technology companies to develop multiple layers of the AI stack rather than relying exclusively on imported technologies.

US investment remains central to the AI market

The United States continues to host many of the world’s largest AI companies, semiconductor firms and data-centre operators.

The scale of American investment has helped make AI infrastructure a major financial market theme, particularly around advanced chips, cloud computing, data centres and electricity supply.

The White House’s 2026 Economic Report of the President said the United States accounted for about 74% of global AI compute capacity in the data it cited for May 2025. The report also noted that US export controls on key AI chips and semiconductor equipment to China had been strengthened in stages beginning in 2022.

The figure concerns compute capacity, rather than overall AI capability, company value or investment returns. Those are separate measures.

China remains connected to US capital markets

Technology restrictions have not eliminated financial links between the two countries.

Reuters reported that US financial institutions continued participating in Chinese technology listings in 2026, while Chinese and Hong Kong investors maintained significant exposure to US semiconductor companies.

This creates a distinction between technology decoupling and financial decoupling.

Governments may restrict particular technologies, investments or transactions without completely separating their capital markets.

For investors, that means geopolitical policy can affect companies even when the investors themselves are not directly involved in technology transfers.

Restrictions create investment risks

The AI competition introduces several types of risk for investors.

Export controls can affect a semiconductor company’s ability to sell products into particular markets.

Investment restrictions can limit access to certain companies or technologies.

Tariffs and trade measures can alter manufacturing costs and supply-chain economics.

Regulatory changes can also affect the valuation of companies whose business models depend heavily on cross-border technology sales.

These risks can arise even when a company’s underlying technology remains commercially competitive.

Semiconductor supply chains are particularly sensitive

Advanced AI systems depend on semiconductor technology, including high-performance computing chips, memory, networking equipment and manufacturing infrastructure.

That makes chip supply chains a central component of the US-China technology relationship.

The United States has introduced measures designed to encourage domestic semiconductor production and reduce reliance on foreign supply chains. The January 2026 semiconductor proclamation explicitly linked domestic capacity to AI infrastructure and national security.

Washington has also taken action involving polysilicon, a material used in both semiconductor and solar supply chains. A separate August 2026 proclamation established measures intended to encourage greater US production of polysilicon and related products.

These policies show that AI competition extends beyond AI-model companies themselves.

China is also building a broader AI supply chain

Chinese technology companies are increasingly pursuing vertically integrated strategies.

Alibaba’s September announcement covered an AI model, an internally developed chip and expansion of cloud infrastructure at the same time.

The approach reflects the importance of controlling multiple parts of the AI production chain.

Models require computing capacity. Computing capacity requires chips and data centres. Data centres require electricity, networking equipment and physical infrastructure.

Restrictions at one point in that chain can therefore influence investment decisions elsewhere.

Investors are balancing opportunity and geopolitical exposure

For investors, the US-China AI competition creates both opportunities and uncertainties.

US companies can benefit from continued investment in AI infrastructure, software and computing.

Chinese companies can benefit from China’s large domestic technology market and government support for greater technological self-sufficiency.

But companies operating across borders can also face restrictions that change the commercial value of those markets.

Reuters described investors as effectively playing both sides of the AI divide, reflecting the continuing financial links despite political tensions.

That does not mean the risks are symmetrical.

The regulatory environment, access to advanced chips, market structure and government policy differ between the two countries.

AI investment is increasingly tied to energy and infrastructure

The financial implications of the AI race extend beyond software and semiconductors.

Large AI models require substantial computing infrastructure, while data centres require electricity, cooling systems, land and network connections.

This has created investment opportunities in power generation, transmission, data-centre construction and related infrastructure.

At the same time, the capital requirements can create financial risks.

The Financial Times reported in September that SB Energy, a SoftBank-backed US data-centre developer, delayed its planned IPO amid investor concerns about the sustainability of the AI infrastructure boom. The company had a targeted valuation of $50 billion and was seeking substantial debt financing for its expansion.

The episode illustrates that strong AI demand does not automatically remove financing or valuation risks.

The US-China AI dialogue is also evolving

Despite competition, Washington and Beijing have maintained channels for discussion.

During the September 2026 Trump-Xi meetings, the two countries agreed to establish an AI dialogue mechanism covering issues associated with the technology’s rapid development.

The White House said the leaders also operationalised the US-China Board of Trade and Board of Investment, while reaching agreement on more favourable tariff treatment for $30 billion of non-sensitive goods in each direction.

These developments show that competition and cooperation can occur simultaneously.

The countries can maintain negotiations over specific areas while continuing to restrict or protect strategic technologies.

AI safety adds another investment variable

The AI competition is also taking place alongside growing debate about the safety and governance of advanced systems.

Reuters reported that Chinese and US policymakers have been discussing AI-related safety issues while disagreeing over how much regulation should apply to development.

For investors, regulatory uncertainty can affect companies in different ways.

Stricter rules may increase compliance costs or slow deployment, while clearer rules could reduce uncertainty for companies and investors.

The effect will depend on the specific regulation, technology and market involved.

Measuring the AI race is complicated

There is no single measure that determines which country has the stronger AI sector.

Compute capacity, semiconductor manufacturing, AI-model performance, research output, private investment, data-centre capacity, electricity availability and commercial adoption measure different aspects of the industry.

Reuters recently highlighted this distinction in its reporting on China’s AI race, noting that conclusions about which country is ahead depend on the metric being used.

This makes broad claims about a definitive winner difficult to substantiate.

It also means investors may evaluate the two ecosystems according to different criteria depending on whether they are investing in chips, cloud services, models, infrastructure or applications.

Global markets remain connected

The continuing financial exposure between US and Chinese investors demonstrates that technological competition has not produced complete economic separation.

US banks remain involved in Chinese technology listings, while Chinese and Hong Kong investors retain exposure to US semiconductor companies.

At the same time, both governments are developing policies designed to increase domestic technological resilience.

That combination creates a market environment in which investors must consider not only company performance but also export controls, investment restrictions, trade policy and geopolitical developments.

What happens next

The direction of the US-China AI relationship will depend on several factors, including access to advanced semiconductors, investment restrictions, AI governance discussions, trade negotiations and the ability of each country to expand domestic computing infrastructure.

The September Trump-Xi meeting produced agreements in some areas while leaving major technology and strategic disagreements unresolved.

For investors, the immediate issue is therefore not simply whether AI investment will continue.

It is also how changes in regulation, supply chains and US-China relations will determine which companies and markets can participate in that growth.

Investors face an increasingly interconnected AI market

As of September 27, 2026, US and Chinese AI ecosystems remain competitors but are still financially interconnected.

Recent investment data reported by Reuters show substantial capital exposure on both sides, even as Washington and Beijing pursue greater technological self-reliance.

The result is an AI investment landscape shaped by both commercial opportunity and geopolitical policy.

For global markets, the central issue is how far technological competition progresses without completely severing the financial and commercial relationships that continue to connect the world’s two largest economies.