Goldman Sachs has urged investors to reconsider how they approach artificial intelligence stocks as the technology race increasingly divides into two competing ecosystems centered on the United States and China, challenging the assumption that the global AI boom can be treated as a single investment theme.
The shift has implications for how investors assess semiconductor manufacturers, model developers, infrastructure providers, and AI application companies. While US technology spending continues to shape global demand for computing infrastructure, China is building a parallel ecosystem spanning domestic chips, large language models and commercial applications, creating a different set of investment opportunities and risks.
“The narrative of a global AI duopoly is gaining traction among investors,” strategists led by Kinger Lau wrote in a note published on Sunday.
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The two ecosystems are taking shape around different geopolitical, national security, and economic priorities, according to the bank. The US-led system includes America and its key trading partners, while China is developing domestic capabilities to reduce reliance on foreign technology and support the adoption of AI across its economy.
Goldman pointed to advances by Chinese AI developers DeepSeek and Kimi in large language models, alongside progress in semiconductor packaging, computing, biological engineering and aerospace. These developments suggest that China’s role in AI is expanding beyond supplying components and infrastructure for a technology boom largely driven by American companies.
“Importantly, the technology gaps between China and the West seem to be narrowing,” the strategists wrote.
China remains several generations behind the global leaders in the most advanced semiconductor manufacturing, Goldman acknowledged. However, the bank said the country was “probably on par with, or even leading,” competitors in certain areas of AI power, infrastructure, models and physical AI applications.
Competition in artificial intelligence extends beyond access to the most advanced chips. Computing infrastructure, model efficiency, software development and the integration of AI into physical systems can also determine which companies capture commercial value. China’s progress in these areas could allow its technology companies to compete more effectively even while constraints remain at the leading edge of semiconductor production.
For investors, the emerging picture is more complicated than a straightforward contest between American and Chinese technology stocks. The two ecosystems are exposed to different sources of demand, policy decisions, and geopolitical risks, meaning that companies benefiting from the same broad AI trend may no longer respond to market developments in the same way.
Goldman Splits Chinese AI Stocks Into Two Investment Groups
The changing competitive landscape is prompting Goldman to move away from treating AI as a single, globally integrated investment theme. Instead, the bank divides Chinese AI stocks into two broad categories: exporters whose performance is linked to Western AI spending and domestic companies positioned to benefit from China’s own investment, adoption, and government support.
The distinction separates companies exposed primarily to the international AI spending cycle from those whose growth prospects depend more heavily on the expansion of China’s domestic market.
Chinese AI exporters remain sensitive to global investment trends, particularly spending by Western technology companies on data centers, computing equipment and related infrastructure. Their prospects can also be affected by geopolitical tensions and changes in cross-border technology access. Even when demand for AI infrastructure remains strong, restrictions on trade or shifts in global capital expenditure can complicate their growth outlook.
Domestic-focused AI companies face a different set of drivers. Their performance is more closely tied to Chinese investment in AI, adoption by local businesses and consumers, and government policy support. This gives investors another way to gain exposure to the technology’s development without relying entirely on the spending decisions of US technology companies.
The distinction also helps explain why Chinese AI stocks have responded differently to the recent market correction.
According to Goldman, Chinese AI exporters gained 126% from early 2025 through June 2026 before retreating 23% from their peak during the global AI selloff. The decline illustrates how quickly gains can reverse when valuations become vulnerable to changes in sentiment or concerns about the sustainability of global AI investment.
Domestic-focused AI companies have held up better since the correction, the bank said, suggesting that their performance has been less exposed to the same pressures affecting exporters.
That relative resilience does not necessarily mean domestic AI stocks are insulated from market volatility. Their prospects still depend on the pace of commercial adoption, the returns generated by AI investment and the extent to which policy support translates into sustainable business growth. Nevertheless, the divergence suggests that investors may need to examine where companies generate revenue, who their customers are, and which spending cycles underpin their valuations rather than relying on a broad AI label.
The framework also highlights a potential change in how investors evaluate China’s technology sector. If domestic AI adoption becomes a more important source of growth, Chinese companies could be valued more on their ability to capture local demand rather than solely on their participation in the global technology supply chain.
AI Stocks Take a Larger Share of China’s Equity Market
The growing prominence of AI is already visible in China’s public markets. Goldman estimates that nearly $5 trillion in market value has been created in Chinese AI-related public equities since the “DeepSeek moment” in early 2025, through share-price gains and initial public offerings.
AI-related stocks now account for 42% of the combined market value of Chinese companies listed in mainland China and Hong Kong, up from 24% in 2024. Their share of trading turnover has also increased, rising to 57% from 48%.
These figures demonstrate how rapidly AI has become central to investor positioning in Chinese equities. The sector now represents a much larger portion of the market’s aggregate valuation and trading activity, making developments in AI companies important to the performance of Chinese stocks.
The rise also comes with risks. As more capital flows into AI-related shares, market performance becomes more sensitive to changes in expectations for the technology’s commercial prospects. If earnings growth fails to match investor optimism, heavily weighted AI stocks could exert greater pressure on the wider market. Conversely, continued advances in models, infrastructure and applications could sustain interest in companies able to demonstrate durable revenue growth.
The distinction between market value created through share-price appreciation and that created through new listings has also caught investors’ attention. Goldman’s estimate combines both, meaning the nearly $5 trillion figure should not be interpreted as investment returns alone. It captures the broader expansion of the listed AI equity market as valuations rise and more companies enter public markets.
The increase in AI stocks’ share of trading turnover further suggests that investor attention is concentrating in the sector. While strong turnover can accompany genuine growth opportunities, it can also make markets more sensitive to changes in sentiment, particularly when a relatively narrow group of themes dominates trading.
A More Fragmented AI Market Changes the Investment Equation
Goldman’s analysis points to a global AI industry that may become increasingly divided by geography, policy, and technology supply chains. The US and China are both seeking to develop capabilities across the AI stack, but their companies operate under different regulatory conditions, market structures and geopolitical constraints.
That fragmentation makes it harder for investors to assess AI exposure solely through aggregate spending forecasts. A company supplying equipment to global data-center operators faces different risks from a Chinese developer whose growth depends on domestic adoption and government-backed investment. Likewise, a business with advanced AI models may face a different competitive outlook from a manufacturer constrained by access to leading-edge chips.
The narrowing technology gap identified by Goldman could also alter the balance of opportunities within China. If Chinese companies continue to improve model performance, computing infrastructure and physical AI applications, the country’s domestic market could become a more significant source of growth in its own right. But continued progress in these areas would not eliminate China’s disadvantage in the most advanced semiconductor manufacturing, which Goldman says remains several generations behind the leaders.
Thus, the investment implications are not just that Chinese AI stocks will outperform or that the US will lose its advantage. Rather, the emerging divide requires investors to distinguish between companies whose earnings depend on global AI expenditure and those positioned to benefit from the development of a separate Chinese technology ecosystem.
The scale of the market’s recent expansion makes that reassessment increasingly consequential. With AI-related companies accounting for 42% of the combined market value of mainland-listed and Hong Kong-listed Chinese equities, changes in sentiment towards the sector could have a substantial effect on broader market performance.