Goldman Sachs' Chief China Equity Strategist Kinger Lau and his team recently published a China strategy update, reiterating that AI has already reshaped the landscape of China's stock market.
Since the beginning of 2025, China's AI-related listed companies have created nearly US$5 trillion in market value through share price gains and IPOs. Currently, AI stocks account for 42% of the combined market capitalization of A-shares and Hong Kong stocks, and 57% of total turnover.
The main viewpoints from Goldman Sachs are as follows:
Two Major AI Investment Themes in China
The narrative of a global AI duopoly is increasingly drawing investor attention 鈥?for reasons including geopolitics, geostrategy, national security, and economic growth, two dominant and self-sustaining AI ecosystems are gradually taking shape globally: one led by the United States and its major trading partners, and the other led by China.
Goldman Sachs Research previously introduced a global AI equity investment universe covering more than 6,000 listed companies. Within this investment universe, Goldman Sachs' China macro strategy team estimates that Chinese AI companies, weighted by AI business exposure, represent US$7.6 trillion in market value across domestic and overseas markets, or US$10 trillion on a full market capitalization basis, accounting for roughly 10% of global relevant market value and earnings, 14% of capital expenditure, and 24% of revenue.
Leveraging strong manufacturing capabilities and cost competitiveness, China has long been a key exporter in parts of the global AI supply chain, particularly in rare earth mining and refining, power equipment, PCBs, optical modules, and mature-node semiconductors, holding more than 50% global share in each of these sub-markets.
Meanwhile, as domestic AI technology develops and evolves, China has gradually built a domestically circulated and increasingly self-sufficient AI ecosystem, covering segments of the value chain historically dominated by overseas players 鈥?so-called "chokepoint" areas 鈥?especially advanced semiconductors and memory chips, semiconductor packaging technology, open-weight/open-source large language models, token generation and consumption, and physical AI application scenarios.
China's large language model performance levels are already widely recognized, but China has also made breakthroughs in other foundational technology areas, including advanced semiconductor packaging and computing, bioengineering, and aerospace. Importantly, the technology gap between China and overseas is narrowing. Although based on public information China still has a generational gap in frontier semiconductor technology, in some power, infrastructure, model, and (physical) AI application areas, China may be on par with or even ahead of global competitors.
At the same time, the research team also noted that achieving full self-sufficiency in AI technology remains a long journey for China, for reasons including: (1) significant differences between Chinese and U.S. AI-listed companies in market capitalization, profitability, and product pricing, creating gaps in financing and investment capacity to support future growth; (2) specific bottlenecks in the domestic supply chain that may hinder the expansion of China's ecosystem technology frontier; (3) AI technology inherently has multiplier effects 鈥?multiple components in the supply chain each lagging by one generation could result in total computing output/efficiency lagging by more than one generation.
China's Two Major AI Investment Themes
Within the team's research scope, Chinese AI stocks include more than 1,700 listed companies, of which over 360 companies derive more than 40% of revenue from overseas, typically viewed by investors as representatives of the overseas AI capital expenditure boom. By theme, these companies are mainly concentrated in AI infrastructure and power.
On the other hand, more than 880 companies are primarily focused on the domestic market, with a combined total market capitalization of US$3.2 trillion. In the domestic market, AI capital expenditure by China's leading cloud service providers/CSPs has also increased substantially, AI application demand and scenarios are flourishing, and policy support for advancing AI self-reliance and self-strengthening is also relatively strong.
Goldman Sachs Research's top-down return analysis shows that Chinese AI exporters have higher return beta to overall global AI stock performance compared to their domestic peers, and are more correlated with geopolitics. However, domestic AI companies are more sensitive to China's domestic AI capital expenditure trends and policy momentum, which may offer international investors diversified investment returns.
Regarding specific investment opportunities, the research team stated that although geopolitical and trade policy risks still warrant attention, they remain bullish on China's AI export leaders. As a whole, Chinese AI export companies are expected to further expand global market share through strong cost competitiveness, manufacturing capabilities and efficiency, R&D investment intensity, and global vision and execution capabilities.
In addition, they are bullish on select Chinese domestic AI leaders. As the domestic AI ecosystem continues to develop, these companies possess scarcity value and can provide diversified investment returns.
Meanwhile, in the research report, analysts once again emphasized a diversification strategy, noting that AI is far from a homogeneous investment theme. Beyond distinguishing AI companies by demand and revenue geographic sources, they reiterated several investment approaches centered on AI that span other dimensions of the AI investment landscape, including market-level A-shares vs. Hong Kong stocks, power and nuclear energy supply chains across the five key AI layers, hard tech vs. soft tech in the context of the STAR 50, ChiNext vs. Hang Seng Tech Index, and long-short strategies around AI disruption risks.
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