On August 20, Alibaba Group released its first-quarter earnings report for fiscal year 2027. This is no routine quarterly scorecard. If the market was previously debating whether AI investment could generate real returns, Alibaba has now answered definitively with the data. Cloud computing serves as the most striking highlight of this earnings report. Alibaba Cloud's external commercial revenue accelerated 45% year-over-year, marking the fastest growth in 22 quarters, while the quality of revenue expansion is also improving. AI cloud and computing services delivered adjusted EBITA of 5.628 billion yuan, surging 133% year-over-year, with profit margins climbing to 12%. Among this, AI-related product revenue reached 12.376 billion yuan for the quarter, maintaining triple-digit year-over-year growth for the twelfth consecutive quarter.
"AI has become the core engine accelerating Alibaba Cloud's growth," said CEO Eddie Wu during the earnings call. He revealed that Alibaba's AI-related product annualized recurring revenue (ARR) surpassed 49.5 billion yuan ($7.3 billion) this quarter, accounting for 35% of Alibaba Cloud's external commercial revenue. Additionally, AI-related product gross margins are significantly higher than the average for cloud products. Last quarter, Alibaba's management declared the AI inflection point had arrived; this quarter, the 45% revenue growth, 49.5 billion yuan ARR, 12% profit margin, and 35% revenue share form a complete chain of evidence validating that claim. In the second half of the AI race, Alibaba, with its full-stack capabilities from chips to applications and demonstrable hard profits, is widening the gap with its competitors. As the AI revenue mix gradually rises, the valuation logic for this tech giant may be standing on the eve of a profound repricing.
Where the growth momentum originates
Three months ago, Wu Yongming made a clear assessment of Alibaba's AI stage: full-stack AI investment has "crossed the early incubation phase and entered a positive cycle of scaled commercial returns." Joe Tsai, in his shareholder letter, explicitly noted that a large number of intelligent agents will consume tokens generated by models in the future, and Alibaba is entering a "new phase of entrepreneurial innovation and critical investment." This quarter, Alibaba's strategic AI investments continued to translate into leading full-stack AI capabilities, delivering tangible business growth across computing power, chips, models, and AI applications, with AI+cloud growth accelerating across the board.
The earnings report shows Alibaba Cloud's external commercial revenue grew strongly by 45%. While revenue growth accelerated, EBITA profit for the AI cloud and computing segment also jumped 133% year-over-year, with adjusted EBITA margin rising to 12%, achieving simultaneous improvement in both growth and profitability. Notably, looking back at 2019-2020, Alibaba Cloud experienced a high-growth cycle driven by the internet industry boom. Nearly six years later, with 45% growth, Alibaba Cloud has once again outpaced Microsoft Azure (+43%) and Amazon Web Services (+37%), reclaiming a top-three position among global cloud computing giants for growth, ranking second globally and the only Chinese enterprise on the list, just one step behind Google Cloud.
In fact, whether specific AI revenue figures are disclosed is the dividing line between an "AI story" and an "AI business." This quarter, Alibaba stands firmly on the "delivery side" of that line. Among global tech giants, Amazon is the only one that regularly discloses AI annualized recurring revenue, with its AWS-related AI revenue exceeding $25 billion and maintaining triple-digit growth. Until this quarter, Alibaba broke that pattern with data: AI-related product revenue reached 12.376 billion yuan, achieving triple-digit year-over-year growth for twelve straight quarters. With this, Alibaba has not only become the only Chinese company but also the second global tech firm capable of providing comparable, highly transparent AI revenue metrics, proving its full-stack AI commercial credibility under real-world scrutiny. Morgan Stanley believes Alibaba possesses large-scale AI infrastructure, high-quality cloud services, and validated Qwen model capabilities, a combination that can support pricing premiums. Therefore, Morgan Stanley argues that Alibaba's previously deployed large-scale capital expenditures are likely to generate relatively attractive ROIC and profit margins.
Profit realization from integrated hardware and software
The other logic behind AI commercialization "delivery" lies in profit recovery. This quarter, Alibaba Cloud's adjusted EBITA grew 133% year-over-year, with margins rising to 12%. This change directly addresses the market's earlier concern: will massive AI capital expenditure erode profits? The answer lies in Alibaba's "integrated hardware and software" strategy. During the quarter, T-Head Semiconductor completed a full-stack self-developed system covering GPUs, CPUs, and network chips, including the latest-generation AI processor Zhenwu M890. Through Alibaba Cloud, these Zhenwu chips have achieved broad commercial application across more than 650 external customers in over 20 industries, including autonomous driving, internet, and finance.
Additionally, Alibaba Cloud has compressed the delivery cycle for large-scale AI data centers to 100 days, and this year, self-developed modular data center production capacity efficiency will more than double to meet stronger AI computing demand. On the model front, Alibaba has accelerated release cadence significantly, with major version updates across large language models, image models, speech models, video models, and music models, all performing at the international first tier. At the same time, Alibaba continues open-sourcing its models, most recently releasing the Qwen3.8-Max and Qwen3.8-27B models with parameter sizes of 2.4 trillion and 27 billion respectively. To date, the Qwen series has surpassed 3 billion cumulative downloads globally, with over 300,000 derivative models, fostering a thriving open-source ecosystem.
AI commercialization ultimately lands in application scenarios. On the enterprise side, Alibaba launched its flagship unified AI-native productivity agent, Qianwen Office, deeply integrated with DingTalk, directly reaching Alibaba's vast enterprise user base and mature workflows, while expanding coverage through integration with third-party business processes and productivity platforms. On the consumer side, the flagship C-end AI application, Qianwen App, is adding diversified value-added services and rolling out paid subscriptions for productivity and professional features. Deeply integrated with core ecosystem businesses like Taobao and Tmall and Taobao Flash Purchase, the Qianwen App has enabled 250 million users to experience AI-driven shopping for the first time through its agent functionality since launch.
Meanwhile, Alibaba is exporting this full-stack AI capability overseas. This quarter, Alibaba's global cloud and AI infrastructure deployment accelerated further, with continued expansion of cloud infrastructure networks in markets including South Korea, France, Japan, Malaysia, and Mexico. Following this round of deployment, Alibaba Cloud's global infrastructure now spans 30 regions and 104 availability zones, covering major markets in Europe, East Asia, Southeast Asia, and Latin America, with new regions planned for Brazil and the Netherlands. In parallel, Alibaba's AI products are expanding globally. Alibaba Cloud is rolling out international versions of Bailian, Qianwen, and Wanxiang models overseas, along with agentic AI products such as AgentRun, STAROps, and ACS Agent Sandbox. Additionally, Alibaba's partnership with SAP is extending from China to Southeast Asia, the Middle East, and Africa. From the chip computing foundation, to the Tongyi Qianwen large models, to applications like Qianwen Office, Alibaba has built a complete AI commercialization loop. While most tech companies remain in the "burning cash to tell stories" phase, Alibaba has demonstrated a clear path to investment returns through its full-stack AI commercialization capabilities.
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