Goldman Sachs Pushes Back on China AI Bubble Fears, Flags Three Investment Themes

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Goldman Sachs' Chief China Equity Strategist, Kinger Lau, has argued that the overall Chinese artificial intelligence sector does not exhibit a bubble, stating that recent market corrections have brought valuations back to healthy levels. He identified three specific sub-sectors with strong investment potential.

Lau noted that the current total market capitalization of China's AI-related stocks does not yet fully reflect the technology's future economic benefits for the broader economy. While he acknowledged a period of localized overheating in June, when valuations for some AI hardware companies on the STAR and ChiNext boards hit five-year highs, a subsequent month-long market pullback has restored a "reasonable and healthy" balance between stock prices and future earnings growth expectations.

Currently, Chinese AI companies represent approximately 11% of the global AI-related stock market capitalization, yet overseas funds allocate only about 1% of their AI investment portfolios to China. Lau highlighted three sub-sectors within China's AI landscape as offering the most promising investment prospects: the power supply chain, hardware infrastructure, and embodied AI.

The power sector presents a long-term structural opportunity, driven by Chinese equipment manufacturers expanding their global market share and the country's large-scale, ongoing computing infrastructure buildout. Hardware infrastructure, including printed circuit boards (PCBs), optical modules, and data centers, offers high earnings certainty over the next two to three years. Embodied AI, which encompasses industrial intelligence and humanoid robots, benefits from China's robust manufacturing ecosystem and strong global competitiveness.

Beyond physical infrastructure, Lau also sees significant growth potential in Chinese AI software applications. AI tokens, a digital metering unit for AI computing services, could become a new engine for Chinese export growth. He pointed out that the cost per AI token for Chinese large language models is significantly lower than that of international competitors, accelerating the commercialization of AI agents and industry-specific cloud solutions in China. This structural cost advantage, he added, could soon reshape China's trade landscape.

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