On February 24, Alibaba Group CEO Wu Yongming announced that more than RMB 380 billion will be invested in building cloud computing and artificial intelligence hardware infrastructure in the next three years. This amount not only exceeds the group's total in this field in the past ten years (about 300 billion yuan), but also set a record for the largest single investment by China's private enterprises in AI and cloud computing infrastructure.

Alibaba Cloud's investment will be divided into three major directions and will burn 380 billion yuan in three years

Judging from financial data, Ali's confidence in this major investment stems from the strong growth of its core business.The financial report for the third quarter of fiscal year 2025 (as of December 2024) showed that Alibaba's revenue reached 280.15 billion yuan, a year-on-year increase of 8%. Among them, cloud business revenue returned to double-digit growth (13%), while AI-related product revenue It maintained a triple-digit year-on-year growth for six consecutive quarters, becoming the core engine driving cloud business growth.

It is particularly noteworthy that capital expenditure surged 80% month-on-month to 31.8 billion yuan this quarter, mainly used for computing power expansion and R & D investment. This signal directly stimulated U.S. stocks to increase by more than 10% before the market, and the single-day turnover of Hong Kong stocks exceeded 41 billion Hong Kong dollars, a record amount.Goldman Sachs, Morgan Stanley and other institutions quickly raised their target prices. The former adjusted the target price of Alibaba U.S. shares from US$117 to US$160, and the latter even gave a valuation of US$300 in an optimistic scenario, implying that Alibaba Cloud will double its revenue in the next three years (reaching 240 billion yuan in fiscal year 2028) and its EBITDA profit margin will increase to 35%.

Ali's strategic layout reflects its deep reconstruction of the technology cycle and business logic.

On the one hand, the group divides its investment into three major directions: first, the hardware construction of AI and cloud computing infrastructure, including data centers, servers and computing networks; second, the AI basic model platform and native application development, with Tongyi Thousand Questions as the core of the model family, through the open source ecosystem (For example, there are more than 90,000 derivative models on Hugging Face) to consolidate technical barriers; the third is the AI-based transformation of existing businesses (such as e-commerce and local life). For example, Taotian Group uses AI-driven "all-site promotion" tools to increase merchant penetration., driving customer management revenue to increase by 9%.This "three-in-one" strategy not only strengthens underlying capabilities, but also opens up a closed loop of commercialization, forming a full chain of coverage from infrastructure to application scenarios.InvalidParameterValue

The market is more concerned about how the huge investment of 380 billion yuan will reshape the industry landscape.

From a supply side perspective, Alibaba Cloud is Asia's largest cloud computing service provider, and this investment will further expand its share in the AI computing power market.CITIC Construction Investment estimates that Alibaba's capital expenditure may reach 120 billion yuan in 2025, of which hardware purchases such as servers, switches, and optical modules will directly benefit domestic supply chain companies, such as Inspur Information and Zhongke Shuguang, and IDC service providers (such as Wanguo Data) may also benefit from the surge in cabinet demand.

The demand side is closely related to the global AI competition: OpenAI's GPT-5, Google Gemini and other models iteratively push up computing power demand, while Ali has surpassed international competitors in multiple benchmark tests through open source models such as Qwen2.5-Max, not only providing its own cloud business with differentiated competitiveness, and may also force the global AI developer ecosystem to tilt towards China.InvalidParameterValue

However, optimism in capital markets still needs to be balanced against long-term risks.Although Alibaba Cloud's revenue growth has rebounded, its EBITA profit margin is still limited by hardware amortization and research and development costs.Wu Yongming said frankly that the next three years will be Ali's "most concentrated period of cloud construction", and capital expenditures will inevitably suppress short-term profits.In addition, the contradiction between supply and demand of domestic computing power has not been completely alleviated, and it is still unknown whether the production capacity and technological maturity of domestic GPUs (such as Huawei Shengteng) can match the pace of investment by giants.At the policy level, the State-owned Assets Supervision and Administration Commission recently deployed the "AI+" action of central enterprises, requiring a solid foundation for computing power and the construction of industry data sets. Although this orientation is beneficial to the industry as a whole, it may also intensify the competition relationship between state-owned capital and private giants.InvalidParameterValue

Across the world, Ali's aggressive investment echoes the strategies of technology giants such as Microsoft and Google.Microsoft's capital expenditure in 2024 will increase by more than 50% year-on-year, mainly for the construction of Azure AI server clusters;Meta plans to deploy 350,000 H100 GPUs during the year.In contrast, although Ali's three-year plan of 380 billion yuan is astonishing, it focuses on the differentiated path of the local market and the open source ecosystem, or provides a sample of the "China Solution" for the global AI competition.If General Artificial Intelligence (AGI)"replaces 50% of human labor" as Wu Yongming said, Ali's infrastructure investment will no longer be limited to commercial returns, but will more likely become a fulcrum for reshaping the global economic structure.InvalidParameterValue

How should ordinary people invest without losing their computing power?

Originally, the emergence of Deepseek caused a hidden worry in the market's demand for computing power.0DeepSeek caused panic because it demonstrated the possibility of training AI models at a fraction of the cost of other models.This could reduce the need for data centers and expensive, advanced chips.But in fact, DeepSeek has pushed the AI industry to develop reasoning models that require greater resource requirements, which means computing infrastructure is still necessary.

Now, Ali's artificial intelligence infrastructure plan has undoubtedly given the market another reassurance.

In the future, according to predictions, although AI's future demand for computing power will be only a small part of the current demand, the increased demand for inference models when answering user questions may make up for this.As companies discover that new AI models are more powerful, they are increasingly calling on these models.This shifts the need for computing power from training models to using models, or "reasoning" in the AI industry.

Venture capitalist Tomasz Tunguz said investors and large technology companies are betting that demand for AI models could increase by a trillion times or more over the next decade due to the rapid spread of inference models and AI.

This shows that the era of large-scale infrastructure for artificial intelligence continues.

However, for investors, the stock prices of companies related to the concept of artificial intelligence are generally higher, such as NVIDIA, Oracle, Google, Microsoft, Meta, etc. The capital cost for ordinary investors to hold multiple stocks is higher.In contrast, artificial intelligence-related ETFs have the advantage of low funding barriers, and generally only costs more than 100 US dollars to purchase one piece (100 copies).

The following are some popular artificial intelligence ETF products on the market, for example only and no recommendations:

ETFs have a rich selection of products, covering upstream and downstream companies in the artificial intelligence industry chain. Investors can achieve risk diversification and share the dividends of industry development without in-depth research on individual stocks.In addition, ETFs have no risk of suspension or delisting, and can trade normally even in a bear market, providing investors with an opportunity to stop losses.Based on its advantages such as low threshold, transparent trading, rich selection, high stability and support for on-site trading, ETFs have become an ideal choice for ordinary investors and novice investors to participate in the artificial intelligence market.