In recent months, the rise of artificial intelligence (AI) technologies has ignited a re-evaluation of the value of Chinese assets, particularly within the realm of its stock marketIn a groundbreaking research report, Goldman Sachs analysts, including Kinger Lau, have introduced an innovative AI investment framework specifically tailored for the Chinese marketThis emerging paradigm is largely credited to the advancements made with DeepSeek-R1 and other competitively positioned AI models being developed in China, which have dramatically altered the narrative surrounding the country's technological advancementsInvestors are now rallying around the optimistic prospects for AI growth and its potential economic benefits.

Goldman Sachs estimates that AI's widespread adoption could boost earnings per share (EPS) for Chinese companies by 2.5% annually over the next decadeThis renewed growth outlook, coupled with an increase in investor confidence, could see the fair value of the Chinese stock market rise by an impressive 15% to 20%, enticing a staggering influx of over $200 billion in portfolio investmentsIn light of these findings, Goldman Sachs has raised its price targets for key indices, setting the MSCI China and CSI 300 expected prices at 85 and 4700, respectivelyThis adjustment signals potential upside gains of 16% and 19% within the next year.

However, while these projections highlight AI's vast potential to reshape China's economic trajectory, Goldman Sachs cautions that robust policy measures are essential to address ongoing macroeconomic challengesSuch interventions are vital to fostering sustainable gains in the stock market, ensuring that the optimistic forecasts materialize into tangible outcomes.

To further shape their perspective, Goldman Sachs has developed a structured investment framework comprising six thematic sectors focusing on AI-related equitiesThese include semiconductors, infrastructure, data and cloud computing, software and applications, revenue growth drivers, and productivity enhancers

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Each sector represents a unique facet of the AI ecosystem, allowing investors to navigate the complexities of the market more effectively.

When examining investment opportunities arising from DeepSeek's introduction into the Chinese AI landscape, analysts noted a significant divergence based on market segmentationOffshore equities showcase greater exposure to AI themes compared to A-shares, a trend that aligns with the superior performance of offshore stocks in recent monthsWithin the primary benchmark indices, sectors such as Hang Seng Tech, CSI 1000, ChiNext, and STAR Market have emerged as more technologically and AI-focused investment vehiclesGoldman Sachs currently remains particularly bullish on data and cloud computing, as well as software and applications sectors.

The framework established by Goldman Sachs operates on several foundational principles that elucidate the dynamics of the Chinese stock market's AI ecosystemIt begins by categorizing the expansive $14 trillion capitalized market into two primary classifications: AI technology and non-technology sectors.

Subsequently, within the AI technology sector—which comprises a market worth $6 trillion—further classifications are made based on the supply chain roles of various industries and the nature of their business operationsThis categorization includes semiconductor firms (which encompass software design), infrastructure companies (hardware, data storage, cooling systems), data and cloud providers (such as internet platform companies), and software/application developers (spanning autonomous driving, biotechnology, humanoid robotics, and internet service providers).

In contrast, the non-technology sector, valued at about $7 trillion, is divided into two distinct categoriesThe first consists of revenue enhancers that, due to their relatively high capital expenditures and R&D investments, are expected to drive increased incremental revenueThe second group, identified as productivity enhancers, holds a labor-intensive cost structure, which may bolster operational efficiency and profitability through the integration of advanced technologies.

Moreover, Goldman Sachs also ranks various sub-industries based on their relative price sensitivity to major players in the market, such as NVIDIA and META

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This analytical approach provides critical insights into how industries and AI agents are responding to the overarching trends of capital expenditures and application developmentsBy understanding these dynamics, investors can ensure they maintain a balanced exposure to the evolving ecosystem, which is in continuous flux.

Through this comprehensive evaluation, Goldman Sachs has gleaned several crucial observationsNotably, China’s technology infrastructure and semiconductor sectors have exhibited remarkable performance over the past two years, driven by substantial capital expenditures toward the enhancement and expansion of global computing capabilitiesBoth sectors currently trade above mid-cycle valuations, suggesting that optimism surrounding AI and the theme of China’s technological self-sufficiency have largely been factored into prices.

As capital expenditures on foundational technologies grow at a more moderated pace both in China and the United States, the introduction of DeepSeek is anticipated to expedite the adoption of AI within ChinaThis shift may refocus investor attention from semiconductors and infrastructure towards data and cloud services along with software and application sectors—areas currently trading below mid-range valuations and demonstrating superior profit growth potential.

Conversely, both revenue enhancers and productivity enhancers have lagged behind in the current technology cycles in both countries, which may reflect the uncertainties surrounding the cost-benefit trade-offs of AI advancements alongside socio-economic implications (such as labor reductions and deflationary pressures). As a result, investors are likely to remain vigilant regarding fundamental and policy developments before engaging with these trailing AI beneficiaries, particularly until their advantages can be quantified and demonstrated more effectively.

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