Alibaba Group September Quarter 2025 Earnings Call - Accelerated AI+ Cloud Growth and Quick Commerce Investments Drive Strategic Momentum

Conference Operator/Moderator: Good day, ladies and gentlemen. Thank you for standing by. Welcome to Alibaba Group’s September quarter 2025 results conference call. At this time, all participants are on listen-only mode. After management’s prepared remarks, there will be a Q&A session. I would now like to turn the call over to Lydia Liu, Head of Investor Relations of Alibaba Group. Please go ahead.

Lydia Liu, Head of Investor Relations, Alibaba Group: Thank you. Good day, everyone. Welcome to our September quarter 2025 earnings conference call. With me today from Alibaba are: Zhou Cai, Chairman; Eddie Wu, Chief Executive Officer; Toby Xu, Chief Financial Officer; Jiang Fan, Chief Executive Officer of Alibaba E-commerce Business Group. I would like to remind you that this call is also being webcast on our corporate website. A replay of the call will be available on our website later today. Just a few forward-looking statements before we begin today. Today’s discussions may contain forward-looking statements, particularly statements about our business and financial results that are subject to risk and uncertainties, which could cause actual results to differ materially from those contained in the forward-looking statements. Please refer to the safe harbor statements that appear in our press release and investor presentation provided today.

Please note that certain financial measures that we use on this call are expressed on a non-GAAP basis. Our GAAP results and reconciliations of GAAP to non-GAAP measures can be found in our earnings press release. With that, I’m going to turn the call over to Eddie.

Eddie Wu, Chief Executive Officer, Alibaba Group: 各位投资人。

Welcome to Alibaba Group’s quarterly earnings call. Over the past quarter, Alibaba delivered steady and healthy growth. Our total revenue increased 15% year over year, excluding Sun Art and InTime. Our continued investment in core businesses is yielding results, with China e-commerce CMR growing 10% and cloud intelligence revenue rising 34%. Let me walk you through the latest developments across our AI+ cloud and consumption businesses. Sustained strong demand for AI and rising usage of public cloud drove Alibaba Cloud’s 34% revenue growth this quarter, while revenue from external customers accelerated by 29%. AI-related products continued to post triple-digit year-over-year growth for the ninth consecutive quarter. In the cloud computing market, two major trends are becoming increasingly apparent. First, as AI applications scale, more developers and enterprise customers are choosing vendors with full-stack AI technology portfolios.

Second, customers are deepening and broadening their use of AI, which is significantly increasing demand for compute, storage, and other traditional cloud services. Together, these forces are accelerating revenue growth driven by external customer demand. This quarter, we continued to strengthen our full-stack AI capabilities, spanning high-performance AI infrastructure, foundation models, and AI development frameworks. Our flagship model, QN3 Max, ranks among the global leaders in benchmarks for real-world coding tasks, agent tool use capabilities, and other specialized evaluations. Our full-stack AI capabilities are now a defining competitive advantage. Alibaba Cloud is gaining market share across multiple segments. In the hybrid cloud market, Alibaba Cloud has become a key player, growing more than 20% year over year, outpacing the industry and steadily expanding market share. Our financial cloud business is also growing faster than the market, with market share continuing to rise.

In China’s AI cloud market, we’re also the clear leader, with a market share larger than the combined total of the second to fourth largest providers. Recently, businesses such as the NBA, Marriott, China UnionPay, and Bosch have partnered with Alibaba Cloud on AI initiatives. Last week, we officially launched the QN app, which aims to be the most advanced personal AI assistant powered by our latest models. In the first week of its public beta, the QN app has already surpassed 10 million in new downloads. The launch of the QN app marks Alibaba’s commitment to both AI for enterprise and AI for consumer. In enterprise-focused AI, our goal is to build a world-leading full-stack AI provider serving businesses across all industries. For consumers, we aim to build native AI-first applications by leveraging our best-in-class models and Alibaba’s extensive ecosystem.

On the one hand, QN3 Max’s intelligence and world-class tool use capabilities, combined with Alibaba’s rich consumer and lifestyle use cases, contributed to exceptional user retention in the QN app’s beta release. We believe this is the right moment to scale our consumer AI efforts. On the other hand, the synergy between AI and the broader Alibaba ecosystem is a powerful multiplier. Alibaba is the only company in China with both a leading large model and extensive lifestyle and commerce use cases. QN will gradually integrate e-commerce, map navigation, local services, and more, becoming an AI-powered entry point for everyday life. With AI innovation and ecosystem collaboration reinforcing each other, we’re confident in our ability to deliver substantial user value. In consumption, we continue to deepen collaboration across businesses, and the benefits of our large integrated platform are becoming increasingly evident. This quarter, China e-commerce CMR grew 10%.

Our quick commerce business saw significant improvement in unit economics, with greater fulfillment efficiency, stronger user retention, higher average order value, and expanding scale. The growth of quick commerce business contributed to rapid growth in Taobao App’s monthly active consumers and supported CMR expansion. Brands on Tmall are also accelerating their adoption of on-demand retail. As of October 31, approximately 3,500 brands on Tmall have onboarded their offline stores to our quick commerce business. Going forward, we will further enhance synergy between quick commerce and the broader Alibaba ecosystem, continue improving unit economics, and meet consumers’ fast-growing demand for immediate access to diverse products and services. On October 1, AMAP’s daily active users reached a historical high of 360 million. In September, we launched the AMAP Street Stars feature, which has significantly boosted user engagement.

In October, AMAP Street Stars averaged more than 70 million daily active users, with average daily user reviews more than triple the amount of the same period last year, indicating strong future growth potential. AMAP Street Stars has built a trust-based rating system for local offline services using user-consented metrics, such as the user’s credit rating. We believe that enhancing consumer trust is essential to strengthening consumer confidence, enabling merchants to focus on operations while giving consumers greater peace of mind, supporting the healthy and sustainable growth of the local offline services sector. Looking ahead, we’ll continue investing decisively in our two core strategic pillars: AI+ cloud and consumption. We will advance both enterprise and consumer-focused AI, unlock deeper synergies across Alibaba’s businesses, and use these engines to drive Alibaba’s long-term growth and carry the company to the next level. Thank you. I will now hand over to Toby.

Toby Xu, Chief Financial Officer, Alibaba Group: Thank you, Eddie. We are continuing our focus and discipline on AI+ cloud and consumption, and we see strong momentum from these strategies with gains in technology, market share, consumers, and user engagement. Now, let’s look at the financial results. On a consolidated basis, total revenue was RMB 247.8 billion. Excluding revenue from Sun Art and InTime, revenue on a like-for-like basis would have grown by 15% year over year. Total adjusted EBITDA decreased to 78%, primarily due to our strategic investments in quick commerce business to grow its user base and transaction volume, partly offset by double-digit revenue growth in China e-commerce group and cloud intelligence group, and improved operating efficiencies across various businesses, including AIDC and Hujing DME. Our GAAP net income was RMB 20.6 billion, a decrease of 53%, primarily attributable to the decrease in income from operations.

Operating cash flow was RMB 10.1 billion, a decrease of RMB 21.3 billion compared to the same quarter last year. The year-over-year decrease was mainly attributed to our increased strategic investments in quick commerce business. Free cash flow was an outflow of RMB 21.8 billion, which reflected our significant investments in quick commerce business and AI+ cloud infrastructure. We are reinvesting our free cash flow to create a winning quick commerce business and to be a leader in AI. Our strong balance sheet, backed by $41 billion in net cash, gives us confidence for this reinvestment strategy. Revenue from Alibaba China e-commerce group was RMB 132.6 billion, an increase of 16%. Customer management revenue increased by 10%, primarily due to the improvement of take rate, which benefited from the increasing penetration of Chen Zhan Tui and the addition of software service fees.

Revenue from our quick commerce business increased 60%. During the quarter, we executed our plan to grow the scale of our quick commerce business, improve user experience, and narrow UE loss. The adjusted EBITDA from Alibaba China e-commerce group was RMB 10.5 billion. Excluding loss from our quick commerce business, our Alibaba China e-commerce group EBITDA would have grown at mid-single-digit year-over-year for the quarter. Going forward, this adjusted EBITDA may fluctuate quarter over quarter due to intense competition and a significant investment in user experience. Revenue from AIDC grew 10%. AliExpress, in particular, has developed its AliExpress Direct model that leverages local inventories in over 30 countries. AliExpress has also enhanced the range of our product offerings by launching the Brand Plus program, providing go-to-market solutions to Chinese brands going overseas.

A combination of logistics optimization and investment efficiency enhancement resulted in AIDC’s adjusted EBITDA profit of RMB 162 million this quarter. Looking ahead, while we continue to enhance operating efficiency, AIDC adjusted EBITDA may fluctuate quarter over quarter due to tactical investments in select markets. Our cloud business delivered another quarter of accelerated growth, as both growth of cloud segment revenue and revenue from external customers accelerated to 34% and 29%, respectively. This momentum was primarily driven by public cloud revenue growth, including the increasing adoption of AI-related products. AI-related product revenue continued to grow at triple-digit pace. AI-related product revenue this quarter accounted for over 20% of revenue from external customers, with its contribution continuing to increase. We are seeing accelerated adoption of our AI products across a broader range of enterprise customers, with a growing focus on value-added applications, including coding assistants.

The adjusted EBITDA margin remained relatively stable at 9%. We will continue to invest in customer growth and technology innovation to increase adoption of AI infrastructure cloud and strengthen our market leadership. All other segment revenue was a decrease by 25%, mainly due to the disposal of Sun Art and Intime businesses. All others adjusted EBITDA was a loss of RMB 3.4 billion, primarily due to the increased investment in technology businesses, partly offset by the improving operating results of other businesses. Hujing DME has achieved profitability for three consecutive quarters. The all other segment comprises a set of innovative initiatives, including several strategic AI-driven technology infrastructure and businesses, including our foundation model and AI apps. We are excited to continue investing in these initiatives for future growth. Thank you. That’s the end of our prepared remarks. We can open up for Q&A.

Lydia Liu, Head of Investor Relations, Alibaba Group: Thank you, Toby. Hi, everyone. You’re welcome to ask questions in Chinese or English. A third-party translator will provide consecutive interpretation for the Q&A session. The translation is for convenience purposes only. In the case of any discrepancy, our management statement in the original language will prevail. If you are unable to hear the Chinese translation, bilingual transcripts of this call will be available on our website within one week after the end of the meeting. 大家好，今天的电话会欢迎您用中文或英文提问。我们会有三方工作人员提供实时交替传译，翻译目的方便大家理解。如有任何疑义，请以我们管理层原始语言所做的陈述为准。如无法听到中文翻译，本次电话会议的双语记录将在会议结束后一周内在我们的网站上提供。 Operator, please go ahead with Q&A session. Thank you.

Conference Operator/Moderator: Thank you. If you do wish to ask a question, please press star then one on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star two. If you are on a speakerphone, please pick up your handset to ask your question. To give more people the opportunity to ask questions today, please keep yourself to no more than one question at a time. Thank you. Your first question today comes from Gary Yu at Morgan Stanley. Please go ahead.

Hi, thank you for the opportunity and congratulations on a strong set of results. My question is related to cloud business. How should we look at the growth outlook going forward? Should we continue to expect growth to accelerate? On the demand side, given we don’t have a big AI company like in the U.S., how should we look at the key driver driving the external revenue growth going forward? Thank you.

各位听众晚上好，感谢接受我的提问，也祝贺公司和技术取得了扎实的业绩。我的问题是关于云方面，尤其想了解云业务未来的增长前景，是不是还有加速的可能性。另外，从需求上面来说，由于中国这边并没有像美国这样的大型的AI公司，那么我们外部客户收入的主要驱动因素是有哪些？好，非常感谢您的提问。我先回答您的第一个问题。我觉得从我们现在看到客户的需求还是非常旺盛。我们现在阿里云的AI服务器，我们的上架节奏其实还是严重跟不上客户订单的增长速度。我们在在手的积压订单数量还在持续的扩大。所以从现在的数据需求上来说，我们可以看到未来的增长潜力还在持续的加速过程当中。然后在需求侧，其实我们看到在企业的应用方方面面，其实的这些需求都在我们看到的情况还是在非常快速的增长。现在在我们的支持的很多企业当中，无论是在产品研发，包括在产品的制造过程当中，以及在产品上线之后的客户买了他们产品之后的每天的日常使用环节，在整个方方面面的环节，其实AI的需求都在持续的渗透。所以我们看到无论是企业作为模型的训练也好，推理也好，甚至是他们的终端客户在开始使用他们开发的AI产品，这些都会用到云端的算力。所以我们看到客户企业实在的付费的需求，其实还是一个比较大的，我们看到是一个大的潜力在增长的过程当中。所以我们觉得对于AI未来的需求，我们是抱有一个比较大的信心。 Thank you for those questions. Let me start with the first one. Certainly, we see that customer demand for AI is and remains very strong. In fact, we’re not even able to keep pace with the growth in customer demand as in orders in terms of the pace at which we can deploy new servers. We certainly do see that demand for AI is accelerating. In terms of where that demand is coming from, it’s really coming from all aspects of enterprise operations as AI adoption continues to not only accelerate but deepen with applications across product development, throughout manufacturing processes, and also in terms of supporting the enterprises and customers use their products. In all of those places, AI adoption continues to deepen. Of course, all of this activity around model training and inference requires the use of compute as well.

Essentially, we’re talking about huge potential and continually growing demand among real customers engaged in real-world use cases. Therefore, our conviction in future AI demand growth is strong.

Lydia Liu, Head of Investor Relations, Alibaba Group: Next question, please.

Conference Operator/Moderator: Thank you. Your next question comes from Kenneth Fong at UBS. Please go ahead.

Hi, good evening, management, and thanks for taking my questions. Congrats on the strong performance in our quick commerce initiative. Can management share some key progress for quick commerce and synergy to our core e-commerce so far? Given the synergy, what’s the outlook for December quarter CMR and EBITDA for our core e-commerce? Thank you.

各位听众晚上好，感谢接受我的提问。同样也祝贺你们本季度在即时零售这一方面取得了扎实的业绩。那么我想了解一下即时零售这一方面最新的一些重大的进展，以及它所实现的一些协同效应。那么基于这些进展，对于12月份季度的CMR以及就是核心电商EBITDA这一方面有什么样的展望？

Jiang Fan, Chief Executive Officer, Alibaba E-commerce Business Group, Alibaba Group: 那我先回答这个问题。对，首先感谢你的问题。就是说这几个月我们是专注于在保持市场份额的前提下优化我们的优异。那么我们认为在这方面我们还是取得了非常显著的进展。一方面订单结构优化，同时规模效应也带来了物流成本的显著下降。对，10月以来散购的优异，就是每单的亏损已经较七八月份降低一半。在这样的基础上，淘宝散购的订单份额稳定，然后GMV份额稳中有升。对相关实物电商品类也有明显的拉动。我可以展开讲一下。首先订单结构的优化。过去两个月平台的高笔单价订单占比提升。按照最新的数据来看，我们非茶饮的订单已经上涨到75%以上。那么散购最新的笔单价环比8月份也涨了超过两位数。笔单价的提升也带动了淘宝散购整体GMV份额的拉动。其次，随着订单份额的扩大，淘宝散购的物流规模效应正在凸显。体现在我们的配送时效优于去年同期，单均物流成本显著降低。那么我们每单的物流成本已经明显低于淘宝散购大规模投入以前。那么在以上两点共同作用下，我们已经完成短期内每单亏损对比七八月份降低一半的既定目标。同时我们看到优异收敛过程中用户的留存跟频次也是好于预期。

Thank you for your question. Over the past few months, we’ve focused on optimizing our unit economics in quick commerce while maintaining our market share. We believe we’ve made significant progress on this front. The order mix has improved, and the economies of scale from growing order volume have driven clear reductions in logistics costs. Since November, the per order UE loss for quick commerce has been cut by 50% compared to July-August. On this basis, quick commerce has maintained stable order share with GMV share holding steady and trending upward. We’re also seeing meaningful uplift in related physical e-commerce categories. Let me expand a bit further on those points. First, in terms of order mix optimization, over the past two months, the share of higher average order value, higher AOV orders has increased.

According to the latest data, non-beverage orders now account for over 75% of total orders. Most recently, AOV for quick commerce has grown by double digits compared to August, which has contributed to an increase in quick commerce’s overall GMV share. On the second point about logistics, as the order volume scales, quick commerce is realizing very clear economies of scale in fulfillment logistics. Delivery speed is now faster than the same period last year, while average logistics cost per order has declined significantly. In fact, the average cost per order is now lower than it was before we started making large-scale investments in quick commerce. These two factors together have enabled us to achieve our near-term target, namely cutting by half the per order loss versus July-August. Importantly, during this phase of narrowing UE losses, both user retention and purchase frequency have outperformed expectations.

除了餐饮外卖，我们也看到散购在零售品类的快速发展。那么散购已经显著带动相关品类跟业务的拉动，尤其在食品健康超市等实物电商品类上。例如，盒马、猫超散购订单环比8月上涨30%。这几个月我们也在积极推动品牌商家加入淘宝散购。那么后续我们也会加速相关业务品类和散购的协同与整合。综合来看，我们坚定认为散购业态与阿里生态有巨大的协同潜力。那么我们第一阶段已经完成了规模的快速扩张。第二阶段，我们的优异优化符合预期，为外卖业务长期可持续发展奠定了一个基础，也增加了我们在即时零售长期投入的决心。下一阶段我们会持续精耕细作用户体验，聚焦高价值用户的经营，聚焦零售品类发展。散购是淘天平台升级的核心战略之一。我们的目标是三年后为平台带来万亿的成交，继而带动相关品类整体市场份额的上涨。

Beyond food delivery, we’re also seeing rapid growth in retail categories via quick commerce, clearly driving growth across related categories and businesses, especially groceries, healthcare products, and supermarket segments within physical e-commerce. For example, Freshippo and Tmall supermarket quick commerce orders are up 30% from August. Over recent months, we’ve also actively onboarded merchants and brands onto Taobao Instant Commerce, and we will further accelerate integration and synergy between key retail categories and the quick commerce model going forward. In summary, we firmly believe that the quick commerce model holds immense potential for synergy with the broader Alibaba ecosystem. In phase one, we successfully achieved rapid scale expansion. In phase two, UE optimization is progressing in line with our expectations, laying a solid foundation for the long-term sustainability of the quick commerce business and reinforcing our confidence in sustained long-term investment in quick commerce.

In the next phase, we will continue to refine the user experience through operational upgrading with a focus on serving high-value users and a focus on expanding retail categories. Quick commerce is a core strategic pillar in the Taobao Tmall group’s platform upgrade. Our goal is to generate CNY 1 trillion in GMV for the platform within three years, thereby driving market share gains across the related categories.

Conference Operator/Moderator: 那我来回答你的第二个问题是关于整个CMR跟EBITDA的波动的。那么刚才讲完说到了，因为从散购的角度，不管是对用户的活跃度、相关品类的成交的拉动，还是都是有明显的作用。所以对CMR也会有一个正向的影响。那下一步其实我们最主要的工作就是要怎么样更好地进行远近场的协同，把这个进行一个体现出来。那么所以重回来，对于整个的中国电商集团的EBITDA，首先我来讲散购这块。散购EBITDA因为整体的一个投入，那么所以从这个角度来讲，这个季度9月季度会是一个高点。随着整个效率的提升，包括优异的显著改善跟规模的稳定，整个的投入我们预计在下个季度是会显著的收缩的。当然对于这点的话，我们也会根据整个市场的竞争的状态动态调整我们的投入策略。

Thanks. This is Toby. Let me take the second part of your question about CMR and EBITDA. As Jiang Fan just shared with you, quick commerce is having a very significant effect in terms of enhancing user engagement as well as driving transactions in relevant categories. That, of course, has a positive impact on CMR. The main thing that we need to do in this next phase is to better integrate and achieve synergies across conventional e-commerce and quick commerce so as to more fully realize that impact. However, we are in an investment phase right now, so this is relevant to EBITDA. I think likely the September quarter will be the quarter during which the scale of those investments are the highest.

As efficiency improves and UE improves and as the scale of this business stabilizes, we can expect to see, I think, by next quarter, a significant sizing down in the scale of those investments. Of course, having said that, we will dynamically adjust the pace and size of our investments in line with market competition.

电商的CMR最主要受到支付手续费跟全站推技术的影响。因为去年我们是9月开始收的支付手续费，所以在下个季度我们预计增速会放缓。那我们一直也在强调我们的最主要的目标是中长期的市场份额。这个过程中我们会坚定地投资消费者，投资商家增长，也会坚定推动电商平台的业务模式升级。在这个过程中，CMR跟EBITDA会有短期的波动。

When it comes to CMR and the e-commerce business, there will be an impact from the base effect in respect of the payment processing fee as well as the rollout of QZT. We started charging the payment processing fee in September of last year. Starting from next quarter, we could expect to see a slowdown in growth due to that base effect. As we’ve consistently emphasized, our primary and foremost objective is to secure market share for the medium and long term. During this process, we will continue to decisively invest in consumers and in merchants, and we will resolutely move ahead with business model upgrading of our e-commerce platform. During that process, you can therefore expect that there will be short-term fluctuations in CMR and in EBITDA.

Lydia Liu, Head of Investor Relations, Alibaba Group: Peter, let’s take the next question.

Conference Operator/Moderator: Thank you. Your next question comes from Alex Yao at JP Morgan. Please go ahead.

Jiang Fan, Chief Executive Officer, Alibaba E-commerce Business Group, Alibaba Group: 好的，谢谢管理层接受我的问题。那就像刚才蒋凡总聊的，我们第一阶段的投资已经结束，现在进入到第二阶段，就是效率优化的一个阶段。那我想问的问题是，随着我们效率优化，然后取得成本的节省，我们在这个节省上面是怎么思考在价值链上key stakeholder上面的利益分配？就比如说对消费者端的补贴是维持原来的强度，那么就是说财务的改善是相对渐进的，包括跟商户这边的补贴的比例。就是我们的成本节省会在这三个利益相关方上面怎么体现，怎么分配？然后还有一个相关的问题就是，如果假设我们不去减少用消费者补贴的话，还是通过现在的路径，用户的结构优化，订单比例的提升，高价值的比例等等，我们的优异还有多少空间继续提升？

Conference Operator/Moderator: 对，这个问题我回答。

Thank you very much for the opportunity. As Jiang Fan just said, we’ve now completed the first phase of these investments. We’re now in the second phase where we are enhancing efficiency. My question is, as the efficiency is optimized and we obtain cost savings, what are we going to do with those cost savings? How will the benefits of those cost savings be allocated or distributed across the value chain among the different key stakeholders? Assume, for example, that we’re going to continue to maintain the same level of intensity with respect to subsidies to consumers and this ongoing incremental improvement in the financial performance of the business, what will that mean in terms of subsidies for merchants? The cost savings will need to be allocated or distributed somehow across the three key stakeholders: consumer, merchant, and platform.

If we do not decrease those subsidies to consumers and we continue to follow the same path that we are on now and rely on optimization of user mix as well as driving increase in order share and driving higher basket sizes, then what does that mean for UE and how much scope is there going forward for UE growth?

Jiang Fan, Chief Executive Officer, Alibaba E-commerce Business Group, Alibaba Group: 我来回答一下这个问题。就是刚才在我的讲述中已经表达了一部分，那就是我们在这段时间的优异提升，首先一方面是比单价的上涨，那意味着我们每单的收入会涨，因为我们的收入是跟比单价相关的。然后刚才我讲到了我们的物流的效率随着规模提升是有一个显著的优化的。对，然后我觉得未来我们还是有很多的空间。那一方面就是我们的消费者，因为我们在过去的几个月还是以新客、大量新客为主，然后随着我们的消费者的这样的一个转化成这种跟我们平台的这种更高的一个粘性，那我们也会在这过程中去提升比单价，然后去改变我们的补贴的方式。然后同时就是我们在淘宝内的这样的一个过去几个月的这种流量，包括闪购的这样的频道的一个快速上涨，成为一个每天过亿用户访问的这么一个频道。那这里面还有很大的一个商业化的空间，那我觉得这也是一个未来优异改善的机会。对，当然就是说整个这个市场还是一个竞争的市场，我们也会去根据市场的竞争的情况，也去看我们的机会，然后也会去动态调整我们这样的一个策略。

Yes, this is Jiang Fan. Let me take this question, and it’s actually related to, in part, some of the things that I was sharing with you a bit earlier. What we’ve been doing in this period of time is enhancing the user experience and at the same time increasing the average order value. That means that the revenues attributable to each order will increase because our revenues are proportionate to average order value. I also spoke earlier about how we’ve optimized logistics, fulfillment logistics efficiency, and will continue to drive improvement there with scale. I think going forward, there is still considerable scope there on the one hand in respect of consumers because over the past few months, it’s really been primarily new consumers in this business.

What we’re doing is converting those users into users with a higher level of stickiness across the platform as a whole. Through that process, we’ll continue to increase average order size, average order value, and to modify the ways in which we provide subsidies. Also, if you look at traffic on the Taobao app over the past few months, including on the quick commerce channel, which has rapidly increased to the point where it now has over 100 million daily users on the channel, I think it speaks to the fact that there’s considerable potential for monetization, further monetization. I think that that’s an opportunity also to improve UE in the future. Now, having said that, again, the market is a highly competitive market, so we will be looking at those opportunities but adjusting our approach dynamically in line with market dynamics.

Lydia Liu, Head of Investor Relations, Alibaba Group: Thank you. Peter, let’s move on to the next question.

Conference Operator/Moderator: Thank you. Your next question comes from Ronald Keung at Goldman Sachs. Please go ahead.

Analyst, Goldman Sachs: 蒋凡, Toby 和 Lydia。那想问一下，我们对未来三年的这个资本开支，之前说过的 RMB 380 billion 应该怎么去想，尤其这个已经过去四个季度花了 RMB 120 billion 了。那我们怎么想这个 CapEx 带动的这个 incremental cloud revenue，我们说这个 ratio，这个 ratio 应该怎么去想这个 CapEx 对 incremental revenue 的那个 outlook？谢谢。

Thank you. I’d like to ask about CapEx over the next three years, and I’m wondering what your thinking is, as you sit here today, regarding the RMB 380 billion figure that you previously mentioned. In particular, because over the past four quarters, I believe RMB 120 billion has already been spent. How should we be thinking about CapEx going forward and the incremental revenue being driven by that CapEx? How do we evaluate the correlation between CapEx and the expected incremental revenue? Thank you.

Conference Operator/Moderator: low side, based on the customer demand we are seeing now.

Thank you for your question. The RMB 380 billion CapEx figure that we had previously mentioned was a planned figure for a three-year period. Based on what we’re seeing now, and as I just mentioned, the pace at which we can add new servers is insufficient to keep up with the growth in customer orders. Looking at the CapEx situation from where we’re at today, and of course there are also supply chain issues to consider as well, the pace at which we can build out IDCs and launch new servers is also part of that consideration. Essentially we’re working as fast as we can to be able to satisfy all of that customer demand.

In that context, if we’re not able to satisfy all of that customer demand especially well with the current pace of investment, then we wouldn’t rule out further scaling up that CapEx investment. That is somewhat dependent on supply chains and availability. In overall terms, certainly we will be investing in AI infrastructure aggressively in order to meet the demand of customers. In big picture terms, I would say that the RMB 380 billion figure we had mentioned previously might be on the small side, certainly in terms of the customer demand that we’re currently seeing.

关于资本开支怎么带来的增量收入，这个比例怎么估算？那我觉得现在这个情况我们其实不太好估算，因为整体 AI 的行业进展就是还是属于比较早期。那我们看到我们整体的整个 AI 基础设施的在使用方面其实还是有几个不同的领域在变化当中。因为比如说我们有直接租用给客户去做训练的，也有直接租用服务器给客户去做推理的。我们也有做用我们自己使用服务器做百炼的推理。那其实包括也有我们的内部的应用，比如说像高德，包括淘宝，包括千问、夸克这样的应用去做转化成他们的会员服务或者会员产品。所以总体的我们的 AI 基础设施在由于这些使用，由于这些应用方式的不同，所以产生的营收和毛利率水平都会不太一样。我觉得就现在这个比例来说可能并不会太稳定。但是我们更从长期来说，我们其实更关注的是我们的基础设施对应的总体产生 Token 的质量和 Token 的一个性价比。

Okay, thank you. The second part of the question had to do with the incremental revenue being driven by these capital expenditures. If there’s some kind of ratio that we can calculate between X amount of CapEx investment and X amount of incremental revenue, I don’t think it’s really possible to make that kind of estimate, at least for the time being, because overall the AI sector is still in the early phases of its development. If you look at the different ways that our AI infrastructure is currently being used, that’s in flux and spans several different areas. For example, we have servers that are directly rented to customers for training. We have servers that are directly rented to customers for inference.

We’re also, of course, using servers ourselves for Bai Lian for inference, as well as for internal applications within the Alibaba Group, like AMAP, like Taobao, like Qwen and Quirk, and transforming these applications into member services or membership-based products for our users. Overall, our AI product and AI infrastructure are being used in all these different ways, different kinds of applications, resulting in different revenues and different gross margin levels. I think in terms of that kind of ratio you were asking about, whatever it is, it certainly wouldn’t be stable at this point. I think in the long term, though, what we care about more is that our infrastructure is serving high-quality tokens and providing good cost-effectiveness for those tokens.

Lydia Liu, Head of Investor Relations, Alibaba Group: Next question, please.

Conference Operator/Moderator: Thank you. Your next question comes from Elijah McCorry. Please go ahead.

Analyst: 感谢管理层接受我的提问。那个我有一个问题也是一个跟进的问题，就是作为一个我们现在全站的 AI 服务商，很明显目前我们还是处在一个比较重要的投资周期嘛，并且这个投资也看到已经涵盖了整个价值链的不同环节。那考虑到目前供应链上持续的一个波动，咱们是如何考虑我们资源上的一些分配？那这里面尤其是在模型 MAS 层，可能对于这个底层能力方面的一个持续建设，或者说在应用端我们看到包括通义、APP、高德等这些更激进的一个推进迭代。那在目前的一个大环境下，咱们如何评价整个行业围绕训练和推理相关 AI 投资的 ROIC？谢谢。

Yeah, thank you, management, for taking my question. This is more of a follow-up question. The company is a full-stack AI service provider, and obviously it’s currently in an important investment cycle. We can see that the investments you’re making cover a number of different segments in the value chain. Considering the instability in the supply chains that are ongoing at present, I’m wondering how you consider the allocation of our resources. Because you have the model as a service, the MAS layer, we also continue to build out underlying capabilities, fundamental capabilities. On the user-facing side, we have apps, including Qwen and AMAP, products like that, that we’re iterating rapidly and scaling up to users.

I’m just wondering, in the present macro environment, how should we think about, how should we evaluate the return on invested capital ROIC in respect of AI, including both training and inference?

Conference Operator/Moderator: 好，我来回答一下。确实我们作为全站的 AI 服务商，我们现在在这个大的 AI 投资周期当中，我们有我们的产品或者我们的基础设施有可以用在各个不同的方面。我们在优先级上，其实是有几个内部不同的优先级的考量。我可以分享其中一些吧。对，我觉得我们最关键的优先级第一要保障总体我们基座模型的训练的这个优先级。因为总体的 AI，我们的 AI 基础设施要有获得更多的客户，或者说要获得更多的高价值场景，只有我们的模型能力持续的迭代提升，才有机会去解锁或者说获得更多的用户以及去解锁更多的场景。解锁更多的高价值场景之后，其实整个的 Token 的消耗量和 Token 的质量，包括客户愿意为这些 Token 去付费的意愿，其实都会逐渐的增强。所以这个是我们的算是优先级比较高的一个领域。另一个在如何使用推理上面，我们觉得对于百炼上面的推理服务，我们也是优先级比较高的。因为我们自己做的百炼平台其实是服务可以全球客户，对于怎么样让我们的 AI 资源能够 24 小时的高效率的使用去削峰填谷，让整体的一台 AI 服务器能够更好地 24 小时满载地去产生更多的 Token，这个是我们觉得是做大百炼的一个资源池，对我们来说也是一个优先级比较高的领域。另一方面就是我们的无论是我们的内部的各个方面的 AI 化的推理服务，我们也是包括外部客户的这些推理服务需求也是在这个后面。我们在外部客户的选择当中，其实也有一个优先级的衡量。如果说我们这个外部客户对我们的阿里云的服务是全方位的，比如说他又要用存储，他又要用大数据，又要用我们的 CPU 的这些资源，那么可能这些客户的优先级会高一点。如果只是纯粹租用 GPU 去满足他的一个简单的推理服务，那这些客户的需求的优先级相对来说就会低一点。

Thank you. Let me take that question. Indeed, as a full-stack AI service provider, we are currently in a very important investment cycle for AI and investing in our products as well as in our infrastructure. There are several different places where we’re investing, and we do have some internal thinking about how we prioritize them, and I can share, I think, some of those considerations with you. First of all, I would say the most critical of those priorities, the first thing that we need to ensure is that we are able to continually train our own foundation models. Because in the AI space overall, the ability of our AI infrastructure to be able to acquire more customers or to be able to acquire more high-value use cases relies on our ability to continually iterate and upgrade our foundation models.

We need to be doing that in order to be able to unlock new demand and to acquire new customers by unlocking new use cases. After that, after unlocking new higher-value use cases, the next thing is to look at the amount of token consumption as well as the token quality, as well as the willingness of customers to pay for those tokens. That willingness is going to continue to strengthen gradually. I would say that is one of the highest priorities when it comes to allocating those investments. Another priority is around inference, and I’m thinking primarily of inference as a service on Bai Lian. That is also a relatively high-priority area for us because we’ve created the Bai Lian platform in order to be able to serve customers all around the world.

We want to ensure that those AI resources are available 24 hours a day and are being utilized 24/7 with high efficiency. The key there is to ensure that one AI server can run at full capacity 24 hours around the clock and thereby to generate more tokens. Bai Lian is a very critical resource pool for us, and it’s a relatively high priority. Separately, of course, we have internal use cases for AI inferencing. Indeed, we also have external customers who are leveraging our inferencing services to meet their demand. That’s also part of the picture. When it comes to these external customers, we also have some criteria for prioritizing different external customers.

If an external customer is utilizing all of our services across cloud, all of Alibaba Cloud services spanning storage, spanning big data, and all of these other things, then of course that customer would be accorded a higher level of priority. If you have a customer that’s merely renting a GPU to meet some very simple inferencing needs, then the demands of those customers would accordingly be given a slightly lower level of priority.

the new GPUs basically running at full capacity, even the previous generation or GPUs from three or five years ago are also running at full capacity. So, we think that within these three years, the so-called AI bubble probably does not exist.

Moving on to the second question, which I thought was a really good one. I think there are two pieces to this issue. First is the demand side. Second is the supply side. If we look at foundation models, and these could be video generation models, they could be omni modal models going forward, but the capabilities continue to increase and be enhanced. We’re not yet seeing any issues in terms of Scaling Law. Nobody’s hit the wall yet, so to speak, in the industry. We continue to make a lot of progress and make very important breakthroughs in terms of model capabilities. As the models become more powerful, then the AI models will be able to do more things in the real world. They’ll be able to serve a larger variety of different use cases.

That will result in these models serving a lot of tasks. As their capabilities increase, they become stronger. As these tasks become more deeply embedded across all industries, all aspects of business operations. With those two drivers, we see in the next three-year period a highly definitive trend of demand for AI. With all of this rapid growth in demand, we also need to be thinking about the supply side. I’m sure that you as analysts have also been looking at the supply side. Starting from the second half of this year, I think we’ve seen worldwide, if you look at fabs, if you look at DRAM vendors, storage companies, CPU manufacturers, across all of those different links in the value chain that go to making AI servers, there is a situation of undersupply.

Supply is unable to keep up with demand for all of these components globally. I think that you can expect that to continue throughout this scaling up and investment cycle driven by real demand for AI. We know that the supply side is going to be a relatively large bottleneck. I think that it could be at least a period of two or three years for those different suppliers, those different vendors to be able to ramp up their production capacity. In this period of two to three years, we can expect to continue to see a rapid increase in demand and that to be driving the supply side. I think in the next three years to come, AI resources will continue to be undersupplied with demand outstripping supply.

What we can see internally in the industry, and if we look at the hyperscalers in the U.S., all of the latest GPUs are running at full capacity, and not just them, the last generation GPUs, even GPUs from three to five years ago, so several generations back, those GPUs are to this day still running at full capacity. Looking ahead to the next, say, three years, we do not really see much of an issue in terms of a so-called AI bubble.

Let’s take the last question, please, Operator.

Lydia Liu, Head of Investor Relations, Alibaba Group: Thank you. Your last question comes from Xie Long Xi from Nomura.

Conference Operator/Moderator: 谢谢管理层接受我的提问。我想请教一下，就是在最近上一个季度电话会，管理层有提到巴巴目前是要在中国的这个大消费市场获得更大的市场份额。我们也看到巴巴在过去几个月在即时零售这个领域里面加大投资，市场份额也有所上升。我想请问一下管理层，除了即时零售，在大消费这个领域里面还有哪些子行业巴巴会觉得比较有潜力，在未来是有可能会加大投入的？谢谢。

Thank you. In the last earnings call, management shared that Alibaba intends to grow its market share in the consumption market in China. We have seen that over the past few months, your investments in quick commerce have indeed resulted in an increase in market share. I would like to know, apart from quick commerce, apart from instant commerce, what are the other subsectors in the consumption market that you see as good opportunities for investment where you will consider scaling up your investments?

Lydia Liu, Head of Investor Relations, Alibaba Group: 我来顺着回答一下这个问题，就是说因为阿里其实在过去多年的布局里面，我们已经进入了非常多的细分品类。对，除了我们现在，就是今年我们在比如说在这个即时零售投入非常大，那其实我们在这个类似于盒马，包括这种线下商超的那个 O2O 的模式，包括像飞猪，包括像在这个高德本地生活，我们都有这样的一个布局。那我们现在更多的还是要整合好我们现有的这样的一个业务，然后能够打通我们各个业务，然后使得我们在业务之间有更好的协同效应，然后来去实现这样的一个在整个大消费领域的一个未来的市场份额的一个提升。

Thank you. This is Jiang Fan, let me take this question. You know, Alibaba has been investing strategically in the consumption market over many years, and we’ve entered a huge number of different categories and sub-verticals. Apart from quick commerce, which we’ve been investing in heavily, we’ve talked a lot about it, we also, of course, have Freshippo, we have the offline O2O model, as well as Fliggy, as well as AMAP, and of course local services. That is our landscape or matrix of businesses that we’ve been investing in. I think what we need to be doing now really is working to integrate, connect those businesses, and to drive more synergies across those existing businesses. In that way, we can achieve further increase in our market share in that larger consumption market. Thank you.

Conference Operator/Moderator: Thank you. Thank you, everyone, for joining us today. We look forward to speaking with you again on our December quarter earnings call.