Alibaba’s latest fundraising announcement has once again put the Chinese technology giant in the spotlight.
On August 23, Alibaba announced a share placement targeting non-U.S. persons outside the United States, raising approximately HK$ 80 billion (US$ 10.2 billion).This marks the company’s first equity fundraising since its Hong Kong listing in 2019. More importantly, all net proceeds will be used to strengthen its full-stack AI capabilities and expand AI infrastructure.
Alibaba is not only willing to spend heavily on artificial intelligence but is also prepared to dilute existing shareholders to fund its ambitions. This sends a clear message: the company no longer sees itself simply as an e-commerce or internet business. It wants to become a major AI player.
But several questions remain. Does Alibaba really need the money? Why has it chosen equity financing over debt? And will its massive AI investments generate sufficient returns, or are shareholders being asked to finance an increasingly expensive gamble?
To understand this decision, it is important to look at the competitive landscape.
On August 20, Alibaba reported its first-quarter results for fiscal year 2027. Operating profit fell 57% year over year to RMB 15.16 billion, while capital expenditure surged 75% to RMB 67.68 billion. The company had previously pledged to invest more than RMB 380 billion in AI infrastructure over three fiscal years, from 2025 to 2027. By the end of June 2026, cumulative investment had already reached RMB 190 billion.
At the same time, annualised revenue from Alibaba’s AI-related products exceeded RMB 49.5 billion. This demonstrates that AI is beginning to generate meaningful commercial revenue. However, the gap between current revenue and infrastructure spending remains substantial. Alibaba is far from alone in facing this challenge. The entire AI industry is moving into a new phase of competition.
Over the past two years, the focus was primarily on developing increasingly powerful large language models. Today, as competition intensifies, the battleground is shifting towards computing power, inference costs, data centres and energy infrastructure.
In 2026, Microsoft, Amazon, Alphabet and Meta collectively guided towards more than US$725 billion in AI-related capital expenditure. Chinese technology companies, including ByteDance and Tencent, are also significantly increasing their investments.
The underlying logic is straightforward: AI development requires more than sophisticated algorithms. It depends on GPUs, servers, storage, networking equipment, data centres and reliable electricity supplies. Companies that secure scarce computing resources early may gain a significant advantage in the next stage of the AI race.
Alibaba’s fundraising is therefore partly an attempt to secure computing capacity before supply constraints ease. CEO Eddie Wu has argued that AI computing power is likely to remain in short supply until at least 2030. He believes current infrastructure investments could generate returns within approximately three years, potentially falling to two years as AI product margins improve.
However, there is a fundamental difference between traditional internet businesses and AI companies. Traditional digital platforms often benefit from relatively asset-light business models. AI, by contrast, is increasingly capital-intensive. The faster AI services grow, the more computing capacity and infrastructure they require.
Alibaba is gradually transforming from a cash-generating internet company into a technology business that requires sustained investment on an industrial scale. This also makes its choice of financing particularly important.
As of June 30, 2026, Alibaba held approximately RMB 474.5 billion in cash and other liquid investments. Given this substantial financial reserve, investors have questioned why the company needs to raise another US$10.2 billion.
Michael Burry, the investor portrayed in The Big Short, publicly criticised the decision. He disclosed that he had exchanged his Alibaba holdings for JD.com shares, expressing concerns that continued AI spending could reduce returns on invested capital if profits fail to grow at a comparable pace. Existing shareholders would then suffer not only from weaker returns but also from further equity dilution.
Alibaba priced its new shares at HK$112.70 each, representing an approximately 8.4% discount to the previous closing price. The newly issued shares account for roughly 3.6% of the enlarged share capital.
Unlike debt financing, equity financing carries no fixed interest payments or repayment deadlines. However, it permanently reduces existing shareholders’ proportionate ownership of future profits and corporate value. Why not simply issue bonds?
One explanation is that the global financing environment for technology companies is becoming more expensive. As major players compete for capital to fund AI infrastructure, credit spreads on technology debt have widened, and new bond issuances increasingly require higher yields to attract investors.
Amazon and Meta have even issued bonds with maturities extending to 40 years, with fixed coupons reaching 6.25% and 6.45%, respectively. Alibaba is therefore not choosing between cheap debt and cheap equity. Both forms of capital have become more expensive. Equity financing allows the company to avoid further increasing leverage and preserve borrowing capacity for future investment.
Nevertheless, a reasonable financing decision does not automatically guarantee a sound investment strategy. The deeper question is whether Alibaba genuinely needs to dilute shareholders to fund its AI ambitions.
E-commerce remains the company’s primary profit and cash flow engine. Its core businesses, including e-commerce, payments and cloud computing, also offer substantial opportunities for AI integration. AI could improve advertising efficiency, reduce operating costs, enhance payment services and create new demand for cloud computing.
If these investments successfully strengthen Alibaba’s existing businesses, the long-term benefits could be considerable.
However, the company must also manage intense competition in areas such as instant retail, where substantial subsidies and promotional spending can put further pressure on cash flow.
For a mature technology company, identifying new growth opportunities is only half the challenge. The other half is knowing where to allocate capital and when to stop investing in businesses that fail to deliver sufficient returns.
This is where a comparison with Tencent becomes relevant. Tencent also has extensive AI application scenarios and is increasing its investment in the sector. Yet its profitability, operating efficiency and cash flow generation remain relatively strong. Alibaba needs to demonstrate that it can balance aggressive AI expansion with disciplined management of its traditional businesses.
Beyond capital, there is another constraint that could ultimately determine the outcome of this competition: energy. As AI data centres expand from tens of thousands of GPUs towards hundreds of thousands and eventually millions, electricity supply, grid connections, energy storage, cooling systems and operating costs are becoming critical competitive factors.
China’s Zhejiang Province, for example, is accelerating the development of intelligent computing infrastructure. Its operational computing capacity has reached 13,000 P, while cities such as Jiaxing and Ningbo are developing high-performance computing clusters.
Alibaba is also exploring partnerships to jointly build computing centres and secure capacity through advance payments and long-term contracts. This reflects a broader transformation in AI financing: technology companies will increasingly rely not only on their own balance sheets but also on infrastructure funds, energy companies, institutional investors and customers.
Ultimately, Alibaba’s HK$80 billion fundraising is both a financial decision and a strategic bet.
If AI demand continues to accelerate, computing resources remain scarce and Alibaba successfully builds competitive full-stack AI capabilities, today’s equity financing could prove to be a forward-looking investment.
But if AI monetisation develops more slowly than expected, infrastructure spending continues to rise and core businesses fail to generate sufficient cash flow, the dilution imposed on existing shareholders could become an expensive price to pay.
Source: cztv, 36kr, sina finance, sohu
