Alibaba Group Holding Limited

Good day, ladies and gentlemen. Thank you for standing by. Welcome to Alibaba Group's March quarter and full fiscal year 2026 results conference call. At this time, all participants are in 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. Please go ahead.

Good day, everyone. Thank you for joining Alibaba Group's March quarter and full fiscal year 2026 earnings call. On the call with me are Zhou Cai, Chairman, Eddie Wu, Chief Executive Officer, Toby Xu, Chief Financial Officer, Jiang Fan, Chief Executive Officer of Alibaba eCommerce Business Group. As a reminder, this call is being webcast live. A replay of the call will be available on our website later today. On this call, we may make forward-looking statements and discuss certain non-GAAP financial measures. The forward-looking statements reflect management's current expectations that are subject to risks and uncertainties. Our GAAP results and reconciliations of GAAP to non-GAAP measures is included in today's earnings press release and investor presentation. Our comments will be on year-over-year comparisons unless we state otherwise. And with that, let me turn the call over to Eddie.

Welcome to Alibaba Group's fiscal year 2026 fourth quarter earnings call. Over the past quarter, Alibaba's high-intensity investment in our two strategic priorities of AI plus cloud and consumption is rapidly translating into tangible business results. with group revenue growing 11% year-over-year. This quarter, cloud intelligence groups' external revenue growth accelerated to 40%, and AI-related product revenue achieved triple-digit growth for the 11th consecutive quarter. China e-commerce CMR grew 8% year-over-year on a like-for-like basis, and the quick commerce market achieved significant unit economics improvement while maintaining market share. We are at a pivotal inflection point in the evolution from conversational chatbots to autonomous AI agents, which is directly driving explosive growth across three core workload categories, training, inference, and agent orchestration. Against this backdrop, Alibaba's AI has moved beyond the initial investment phase and progressed commercialization at scale. Next, let me walk you through four areas in detail, AI commercialization, cloud infrastructure, the AI application ecosystem and our consumption business. First, the AI and cloud commercialization inflection point has arrived. This quarter, Cloud Intelligence Group's annualized AI-related product revenue has surpassed 35.8 billion RMB, continuing to maintain triple-digit growth. AI-related product revenue now accounts for 30% of Cloud Intelligence Group's external revenue. We expect that in about one year, AI-related product revenue will cross the 50% threshold, becoming the primary engine driving the cloud business's revenue growth. As a result, cloud intelligence groups' external revenue growth is expected to continue accelerating beyond its current 40% rate over the coming quarters. Given the certainty of long-term AI demand and our full-stack technology advantages, we expect this trajectory to sustain strong growth over the medium to long term. This reflects AI's role in driving a comprehensive upgrade of Alibaba Cloud's entire business as its growth engine fully pivots from traditional compute and storage to models, AI compute and agent services. We're also seeing exponential growth in AI model and application services revenue. A new revenue engine driven jointly by foundation model services and AI native software. Over the past three months, Token consumption volumes on our model services platform grew substantially quarter over quarter as enterprise customers accelerated their shift from simple tasks to production scale and complex workloads, driving continued growth in demand for model and application services on the Model Studio platform. We expect model and application services annualized recurring revenue, ARR, inclusive of the Model Studio platform to surpass 10 billion RMB in the June quarter and 30 billion RMB by year end. The harm margin profile of this revenue stream is becoming increasingly apparent, making it a source of healthy, high quality growth. Second, our AI infrastructure underpins our full technology stack and constitutes a durable moat. T-Head's proprietary GPU chips have achieved scaled mass production with over 60% of compute capacity already serving external customers across internet, financial services, and autonomous driving verticals. As the only AI cloud provider in China capable of delivering self-developed AI chips at scale, we've secured autonomy over our compute supply chain while providing customers with highly competitive AI inference and training services. In an environment of compute scarcity, this structural advantage is favorable to our revenue growth and gross margin improvement. At the same time, our cloud products are accelerating their AI-oriented upgrade The surge in agent workloads has significantly elevated demand for traditional cloud products built around CPU storage and containers, and we're upgrading these into infrastructure solutions optimized for the agent era. Third, at the application layer, we've built a complete closed loop spanning AI-native software to a full agent ecosystem. Alibaba Token Hub ATH continues to launch new products, connecting consumer and enterprise environments with breakthrough progress in AI native software and coding agents. The Q1 model continues to iterate across reasoning, coding, and agentic capabilities. On the enterprise side, we've launched a range of products spanning intelligent workplace tools, AI coding, and business operations management, helping enterprises unlock greater productivity. On the consumer side, The QNAP fully integrated Taobao and Tmall's commerce service capabilities on May the 7th. With this QNAP is now deeply embedded across the ecosystem, spanning Taobao, Alipay, AMAP and Fliggy, making it China's first all-in-one personal assistant to seamlessly bridge everyday life productivity and learning. Fourth, across our consumption business and at the group level, we're prioritizing long-term value. Beyond AI, our consumption strategy continues to progress steadily with CMR growth rebounding significantly. This quarter, CMR grew 8% year-over-year on a like-for-like basis as we continue to improve user experience and merchant operating efficiency. The quick commerce business achieved significant unit economics improvement while maintaining stable market scale. In summary, the return on our investments in AI plus cloud and consumption are increasingly clear. AI plus cloud revenue growth is accelerating with improving margins. Model and application services, ARR, continues to grow at pace and operating efficiency across our consumption business continues to improve. Facing the historical opportunity that AI represents, Alibaba is at a pivotal juncture where our technology investments are beginning to pay off commercially. We'll maintain our strategic resolve and leverage our full-stack AI capabilities to support long-term growth. That concludes my prepared remarks. Next, I'll hand over to Toby to walk you through our financial results. Thank you. Thank you, Eddie.

Our strategic priorities remain laser-focused on AI plus cloud and consumption businesses. Multiple growth catalysts, including technological advancement and business innovation, are aligning to create strong tailwinds. On AI plus cloud, our full stack of abilities span models, cloud infrastructure, and applications with established leadership in every layer, the strong growth of our AI plus cloud businesses and the clear path to monetization of our mass platform give us confidence to make significant investments to extend our leadership. On consumption, we achieved a strong CMR growth on a like for like basis during the quarter. In our quick commerce business, continue to improve UE and AOV quarter over quarter. Now let's look at the financial results for this quarter. On a consolidated basis, total revenue was RMB 243.4 billion. Excluding revenue from Sunnah and InTime, revenue on like-for-like basis would have grown by 11%. Total adjusted EBITDA decreased 84%. primarily due to our strategic investments in technology businesses, quick commerce, and user experience, partly offset by the improved operating results supported by continued growth in consumer management service in the cloud business and enhanced operating efficiencies across various businesses. Our gap net income was RMB 23.5 billion an increase of 96%, primarily attributable to the year-over-year increase in net gain from mark-to-mark changes of our equity investments and disposal losses of Sundar and Intime in the same quarter last year, partly offset by the decrease in adjusted EBITDA. Operating cash flow was an inflow of RMB 9.4 billion, Free cash flow was an outflow of RMB 17.3 billion. We are reinvesting our operating cash flow to enhance our competitive advantage in AI. As of March 31st, 2026, we held approximately US dollar 38 billion in net cash. Excluding debt with maturities beyond five years, our net cash position stands at approximately US dollar 59 billion. This balance sheet strength gives us confidence to invest for growth. Now let's look at our consumption businesses. Revenue from China e-commerce group was RMB 122 billion, an increase of 6%. Customer management revenue increased by 1%, To help merchants grow their businesses and increase willingness to spend on our platform, we upgraded our business development program for select merchants during the quarter, under which the level of platform subsidies for these merchants is directly tied to their marketing spend on our platform. For accounting purpose, such subsidies previously recorded as sales and marketing expenses are now recorded as a contract revenue item to CMR. Accordingly, CMR grow 1% year over year during the quarter. Excluding the contract revenue impact from the program, on a like for like basis, CMR would have grown 8% year over year. Revenue from our quick commerce business increased 57% to RMB 20 billion. The quick commerce business further improved the UE and increased the AOV quarter-over-quarter, primarily driven by order mix optimization. Alibaba China e-commerce group adjusted IPTA was RMB 24 billion, a decrease of 40%, primarily due to the investment in quick commerce, user experience, and technology, while there's positive contribution from customer management service. Excluding loss from our quick commerce business, our Alibaba China e-commerce group, Ipitar, would have been stable year over year and will fluctuate quarter over quarter due to significant investment in merchant retention and the user experience. Revenue from AIDC grew 6% this quarter, AIDC's adjusted EBITDA loss narrowed significantly year over year, approaching break-even, driven by a combination of logistics optimization and operating efficiency. The unit economics of AliExpress's choice business continue to improve substantially on a sequential basis. Next, let's look at the business updates and results of Cloud Intelligence Group. Our cloud business delivered another quarter of accelerating growth. Revenue from external customers accelerated to grow 40%. AI-related products continue to lead this momentum. We delivered our 11th consecutive quarter of triple-digit growth in AI revenue. Its share of external cloud revenue continued to increase, now account for 30%. This quarter's AI revenue is RMB 9 billion, and the annual revenue run rate is RMB 36 billion, or US dollar 5.3 billion. This is a clear reflection of the scale and acceleration in our AI business. The adjusted EBITDA margin remained relatively stable at 9.1%. All other segment revenue decreased by 21% to RMB $65.5 billion, mainly due to the disposal of sunna and in-time businesses, as well as the decrease in revenue from Chania, partially offset by the increase in revenue from Freshepo and AMAP. All others adjusted EBITDA was a loss of RMB $21.2 billion, primarily due to the increased investment in technology businesses, including foundation models and the consumer-facing Queen APP. As we close this fiscal year, we remain committed to delivering consistent shareholder returns. Our board of directors has approved an annual dividend of US dollar 1.05 per ADS. We will continue to invest decisively in AI in consumption businesses, where we see significant long-term growth potential in our competitive advantages of compounding. We believe these investments to deliver growth and returns over time, ultimately creating greater value for our shareholders. Thank you. We will now open for Q&A.

Hi everyone, you're welcome to ask questions in Chinese or English. A third-party translator will provide consecutive interpretation. In the case of any discrepancy, our management statement in the original language will prevail. 大家好,欢迎提问。 我们有第三方工作人员提供实时中英文交替传译。 如有任何疑义,请以管理层原始语言所做的陈述为准。 Operator, please start Q&A session. Thank you.

Thank you. If you wish to ask a question, please press star 1 on your telephone and wait for your name to be announced. If you wish to cancel your request, please press star 2. If you're on a speakerphone, please pick up the handset to ask your question. To give people the opportunity to ask questions, please keep yourself to no more than one question at a time. Your first question comes from Ronald Kung with Goldman Sachs.

Thank you, Joe, Eddie, Toby, Fan, and Lydia. And thanks for sharing the very sizable AI math and applications ARR scale and the target for the first time. So I just want to ask how much of that ARR is driven by our in-house models like QAN versus third-party models? And given the recent token price hike, What would be the implications to mass and also our cloud margins as a result?

Thank you.

Thank you, Joe, Eddie, Toby, Jiangfan, and Lydia. Thank you for sharing the scale of AI mass and application. I would like to ask you about the growth of ARR. Thank you for your question.

Because this season we just announced a new number, which is our model and application model and application service income. The main business of this income is now the main business composition. In fact, it is divided into two parts, which is our 100 chain mass API service and the subscription value of our original AI software. . . . . . Thank you for that question.

This quarter marks the first time that we announced the latest figure for model and application service revenue. That really comprises mainly two things. On the one hand, it includes revenue from API calls en masse on our Bailian platform, and it also includes revenues from our AI software subscriptions. At present, most of the revenue is coming from the first of those two pieces, but this is an open platform, so we are providing access both to our proprietary models as well as third-party models, including open source models and closed models. But for the time being, most of that revenue is coming from our own proprietary models, including Q1 as well as Tmall as well as our voice and video generating models.

The second question you asked is actually a more critical one. Because recently, in the past few months, there has been a very big change in the entire industry. Because the entire AI is moving from a chatbot in a conversation to an agent. . . . . . . . . And then there are a few more important points. The first point is that the development of the entire technology in Twilio is still ongoing. So, in every quarter, we will see some optimization in Twilio technology and the results it brings. It can produce some continuous improvement effects on the token production of a single server and a single card. At the same time, the ability of the model is continuously being enhanced, and the price of the model, in the next year or two, we see that it will continue to be a process of price improvement. So, from this perspective, I think that in the future, because of the rapid growth of the MaaS business, it will have a very positive impact on our net profit.

Your second question was also a really important one because in the past quarter, over the past few months, we've seen a very large shift in the market where AI is shifting from functioning as a conversational chatbot to providing agentic capabilities. These agents are increasingly capable of solving for very complex problems, meaning that they need to do a lot more inferencing than in the past. And precisely because these agents can help to solve very complex tasks, customers' acceptance for higher prices, and we have increased per token prices, is good, and the demand continues to be high and growing. In fact, our ability to supply this demand is not able to keep up with all the growth in demand, and we actually have a lot of customers still waiting to access the service. Inherently, MAS will have higher gross margin than IAS. That's important to know. And I can also add a few important points on top of that. First is that the development of reasoning or inferencing technology still continues to advance, so every quarter we're seeing new results in terms of optimization in reasoning, in inferencing. with continuous incremental effects in terms of the token capacity of a single server and a single cart. At the same time as the capabilities of models continue to strengthen and price of the models continues to increase in the next year or two, we see that this should be a process of continued price improvement. So I think from this point of view, the rapid growth in this business over the next few quarters will result in a very positive impact on our overall gross profit margin.

Your next question comes from Kenneth Fong with UBS.

Hi, good evening, management. Thanks for taking my questions and congrats on the very strong progress on the AI. I have a question regarding the return on invested capital on the AI investment. So while our AI investment have driven impressive 40% cloud growth, they have also created significant drag on the group free cash flow as well as our EBITDA. So how should investors assess the return on this investment and what's the management framework for balancing the aggressive AI spending versus earning stability? Thank you.

Thank you very much, Mr. Guariceng. I also wish you a very good performance in the field of AI. My question is about the return rate of our capital investment in the field of AI. We see that this kind of investment makes us able to achieve uh uh uh uh uh Okay, thank you for your question.

I think I will answer the first part first, because I think everyone, especially in this period, sees that our free cash flow is a negative number, so everyone may be more concerned about how we are going to manage it. I think first of all, you can see that the most important part of such a free cash flow is our investment in AI in the past year. Because we saw such a historical opportunity, we are very determined to make such an investment in this area. So this is the main cause of the overall free cash flow recovery situation.

Thanks, Kenneth, for that question. This is Toby, and I'm going to start by answering that first question because I think it's important and of interest to everybody. The question is the reason for the negative free cash flow and how we are managing that. So starting there, the answer is that the negative free cash flow is primarily due to the very significant investments we've been making in AI over the past year. And we've been extremely resolute in making those investments precisely because we've seen the historic opportunity of AI.

In the next two years, I think our investment will continue to be very firm. Because such a window period may be a few years for us. So from an investment perspective, we will continue to be very firm. At the same time, from the point of view of our operating cash flow, there is actually no big change. Here I want to talk about two aspects. The first aspect is from the point of view of our consumption business. Taobao Tianmao is one of our most important operating cash flows. The whole operating cash flow is still very stable. And in the next two years, with the overall loss of our retail, the relative loss of large volume of collection, the overall consumption business will, plus we also have an AIDC's overall loss from a loss to profit direction, the overall consumption business in the next two years, the overall cash flow, the cash flow will be a very positive development. So this is the first thing I want to say.

So we've been very resolute in making those investments over the past year, and looking forward to the next two years, we intend to be equally resolute in continuing these investments, again, because we see this as a critical window of opportunity that will be open for that period, for the next couple of years. Additionally, there's really been no big change in the way that we look at cash flow. First of all, the major contributor of operating cash flow for the group is Taobao and Tmall, and that cash flow is very stable. And looking ahead over the next two years, in terms of quick commerce, the losses will narrow very substantially at the same time AIDC will develop from making a loss. to being profitable. So we see these developments over the next two years as being highly positive for our net cash flow.

The second point, another very important point is that our investment in such a basic infrastructure in the cloud, as Eddie just mentioned, will make our entire cloud income, AI cloud income, continue to accelerate, while improving the overall profit margin. All of these will further improve the cash flow in the cloud, which can also support our investment in the cloud infrastructure. The third point, I also want to say that I just mentioned that our entire balance sheet is still very strong. Our current cash flow is almost 3.8 billion US dollars. If we take out the debt that has expired for more than five years, our current cash flow is about 5.9 billion US dollars. So, such a very solid asset balance sheet can also support our investment in such a cloud infrastructure. Finally, I would like to say that we still have a strong financing capacity in the capital market, and we can respond to the strategic development needs through different forms of market financing. So I would like to respond to what you just mentioned about cash flow, including how we can prepare for a more sufficient cash flow. Next, let's see if Eddie has anything to add.

Another important point to be added is that our ongoing investments in cloud infrastructure will increase the revenues that we can achieve from our AI and cloud offerings. At the same time, we will increase gross margins in those very same offerings. So in those ways, we expect that we can achieve higher net cash flow from our cloud and AI business, and that cash flow can in turn be used to support the development of the relevant infrastructure. An additional point is that we have a very strong balance sheet. As of March 31st, 2026, we held approximately 38 billion US dollars in net cash. And if you exclude debt with maturities beyond five years, our net cash position stands at approximately 58 billion US dollars. So that balance sheet strength also gives us confidence to reinvest for growth. And beyond that, I would also add that we have a very strong capacity for pursuing financing in capital markets and we have the capability to raise capital from the markets as we need to support our development so i wanted to open with that in response to your question on cash flows and i'll pause there to see if eddie has anything to add

From the development trend of the entire AI business, I think AI is more like a manufacturing industry. In other words, when we want to get more income, we actually have to build two core factories. The scale of these two core factories will affect how much income we will have in the future. One of these two core factories can be called an AI training factory, and the other is called an AI reasoning factory. . . . . . . . The commercialization of 2B is very clear on this path, whether it is the commercialized service of the cloud, or through our MaaS platform, and through our AI native software to create more model-based revenue. We are almost now in our service area, almost no card is empty. That is, now, I think in the next three to five years, in the case of this demand, we have invested a lot in the construction of the AI data center. This investment return is very certain.

thank you you asked about our investments in AI and the ROI on those investments going forward so on top of what Toby's already said I'd like to add a few notes regarding where we're heading I think the best analogy is manufacturing in other words in order to be able to manufacture more and sell more in the future and achieve more revenue what we're doing today is investing capital to build a to factories if you like the first we can call the ai training factory the second we can call the inferencing factory and both of those factories need to be powered by our ai data centers and that requires the investment of cash flow today however looking to the future the pathway to achieving a solid return on investment in those factories in those areas is very clear on the 2B side by monetizing our 2B offerings, including our cloud-based IaaS, as well as MAS, of course, and our AI-native apps. And I can tell you that today there isn't a single card on our servers that is idle. So we see the ROI on this investment in the next three to five-year period as being extremely clear.

Next question, please.

Your next question comes from Thomas Chong with Jefferies.

Hi, good evening. Thanks, management, for taking my question. My question is on quick commerce. We have talked about the improvement in the prepared remarks. I just want to get some more color about the drivers behind in terms of AOV, subsidies ratio, fulfillment ratio, etc. And on top of that, I remember last time we talked about the outlook for QuickCommerce over the next couple of years. Is there any update or changes in terms of how we think about the landscape or the UE in the next few years? Thank you.

Thank you, Manager. My question is about the time-saving aspect. In the presentation, you have already introduced that UE has been significantly improved. I would like to know the driving factors behind it, including the price of the bill, the ratio of subsidies, and the contribution of contracts. In addition, in the last quarter's press conference, in the next two years. I would like to know, from then to now, what changes do you expect to see in the market? What changes do you expect to see in the market format, including in terms of EUV and subsidies? Let me answer this question.

First of all, after a year of investment, we have seen the rapid development of real estate business. Our market share has undergone fundamental changes. . . . . . . . . . . Thank you. Well, first, as a result of our strong investments in QuickCommerce, we've achieved very rapid growth in QuickCommerce over the past year.

marking a very fundamental shift in our market position. Compared to the same quarter last year, which was, of course, prior to all this large-scale investment, both our order volume and our market share have increased significantly. Overall order volume was 2.7 times that of the same quarter last year, with non-food orders at 3 times. From April onwards, while maintaining order volume, we've continued to drive substantial improvement in UE through enhanced fulfillment, logistics efficiency, as well as order mix optimization. So we are confident that UE will turn positive by the end of fiscal year 2017.

At the same time, we will continue to maintain our long-term competitiveness in the field of real-time sales through innovation, improvement of users, and business experience. So we are confident that in the future, we will achieve the overall profit of real-time sales under the new scale and market share. In this quarter, we also see the promotion of retail shopping for food and e-commerce, especially in the acquisition of new customers, the activity of promotion users, the diversification of user satisfaction, the consumption scene, the promotion of transaction and commercialization, as well as logistics infrastructure and other aspects, and the development of Taotian's overall version. We continue to see the obvious drive of retail shopping related products, especially food, raw materials and other products. We also continue to promote the development of related business such as Hema, Maochao, etc., While optimizing UE, we will continue to innovate to improve the experience for both consumers and merchants, thereby sustaining our long-term competitiveness in quick commerce.

We're confident that our QuickCommerce business will achieve overall profitability in the future at new scale and market share. This quarter, QuickCommerce continued to generate synergies with our conventional e-commerce business as demonstrated in driving customer acquisition, enhancing user engagement, fulfilling diverse consumer demands, increasing transactions, improving monetization, and supporting logistics infrastructure In terms of categories, QuickCommerce continued to drive sales in various categories, especially food and fresh produce and healthcare, and contributed to fresh appos and Tmall supermarkets accelerated growth. So in our conventional e-commerce business, we saw GMV and CMR demonstrate strong growth momentum in the March quarter, and QuickCommerce played a vital role in driving that performance.

Next question, please. Your next question comes from Jia Longshi with Nomura.

晚上好,管理層。 非常感謝接受我的提問。 我想追問一下之前在Opening Remark 管理層說到的MaaS的業務。 我想了解一下管理層怎麼看在MaaS領域, 阿里巴巴和中國其他頭部的AI平台公司 以及AI創業公司的優勢是什麼。 In the US, AI agents, especially AI coding, are already the fastest in the field of AI commercialization. So I would like to ask, in China, when do you think AI coding will see a similar increase? In addition, Chinese companies have not been willing to pay for SaaS products. Do you think this will make the commercialization prospects of Chinese AI coding products as promising as in the US? Thank you.

Good evening, management, for taking my question. I have a follow-up based on your opening remarks concerning mass. I'm wondering, first of all, what are the major advantages that Alibaba has when compared to the other major AI platforms in China, as well as Chinese AI startups? In the United States, we see that AI agents, and especially coding, are the fastest growth track in AI. I'm wondering when you think we'll see that kind of growth in China in terms of AI coding. We also know that Chinese customers are less willing than US customers to pay for SaaS. So do you think that means that the future commercialization of Chinese AI coding products might have less potential Okay.

Thank you for your question. You asked a good question. On the Aliyun blockchain platform, we are actually positioning it as an open AI reasoning platform. On this reasoning platform, the main revenue is generated by our own model. Then I think to compare these to our AI startup companies, it is like our investment and breadth on the model. In fact, we will be far beyond these model startup companies. Of course, these model startup companies are focused on a certain model or a certain field. They also have very strong technology and very fast. very fast business sharpness. So their progress is also very fast. So from this perspective, if we just look at the MaaS field, I think these startup companies are also a part of Alibaba. But for Alibaba, we will emphasize that we need to do more extensive research in various fields of models. That is, we will do We believe that in the future, in many business scenarios, users will need a variety of model capabilities to meet their business needs. So, I think this is something that we are working on. Thank you.

Well, the way we define our mass platform, Bailian Model Studio, is as an open AI inferencing platform. Certainly at present, the majority of Bailian's revenue is driven by our own proprietary models. But in contrast to the AI startups in China, I think that we are investing at a much higher scale and across a much broader range of different model types. In contrast, those startups may tend to focus on a very narrow particular vertical segment and they can move rapidly ahead with that kind of focus. You know, and strictly in terms of our mass business, I think those AI startups really are partners rather than competitors, but at Alibaba, we particularly place emphasis on model capabilities and developing them across all different spaces and all verticals to serve a very broad and diverse set of needs, including our coding model capabilities, including image-based models, so both Wan Xiang and Happy Horse, as well as The question you asked about AI coding is also very good.

You said, when will there be a similar number? In fact, I think our judgment is that in China, there is already a similar number. In other words, from the trend we saw on the chain platform, as well as in other industries, such as these AI startup companies that have a better relationship with us. In fact, from November and December last year until now, AI coding. Due to the improvement of AI model capabilities and the combination of AI coding and the operating environment of the entire agent, that is, the so-called Harness engineering, and the combination of these data fields, we can see that complex task agents driven by AI coding can almost complete tasks in various digitized work tasks. So, whether it is the United States or China, this wave of AI needs is mainly due to the improvement of AI coding capabilities. Because of the improvement of AI coding capabilities, combining computer or digitalized tools and scenarios, theoretically, it can solve almost all the complex tasks of digitalization in the future. So this is a very important growth trend in the next two to three years.

The other part of your question was about when we can see a similar kind of growth in China as is being witnessed in the US around AI coding. And I would say in terms of what we're seeing, based on the trends that we ourselves see on as well as the experience of some of these AI startups in China who work closely with us, I would say China is already there. most of the growth that we're seeing in utilization from say November or December of last year through to May of this year has been driven by capability upgrades in terms of coding. And these models are not just able to replace software engineers, basically they're able to solve a wide array of very complex tasks beyond just coding per se in any kind of digitalized productivity scenario. So, you know, we've seen AI coding capabilities improve significantly in both the US and in China. And these capabilities are capable of supporting much more than just Coding, per se, can address a whole wide range of very complex tasks in the workplace, insofar as those tasks can be digitalized. So looking ahead to the next two to three years, we see this as a very, very important growth driver.

Okay. Actually, we see that the problem of the long-term existence of SaaS recovery hospitals in China is relatively low. I think there is a very big difference in this era of the big model. . . . will pay for this smart ability. This demand is the same in the United States and China, and it will be very strong. In theory, as long as it helps it complete this work task, the value created by this part of the work task in its enterprise is greater than the cost of the token. In a sense, the demand for API tokens will be infinite. So from this perspective, we can see that the growth of the needs of the underlying AI will still be very long-term. From what we can see, we can also share some of the data that we can see. The overall growth that we see on our blockchain platform foreign On your other comment, we have also taken note of the lower willingness in China to pay for SaaS.

However, I think that is poised to change as the models become increasingly powerful and are able to truly solve for very complex tasks, very complex problems as they are providing truly valuable intelligence. I think we can expect to see the same demand for that kind of service in China as in the US. In a certain sense, when the value provided by tokens exceeds the cost of those tokens, the demand for tokens will become infinite in a sense. So we see growth in AI demand as a long-term certainty. And I can also share some numbers with you in terms of the growth that we're seeing on our own Bailian platform from November, December last year through the May of this year. It's higher than that 10 times growth. In terms of our ARR, it's already over $8 billion. And I think this quarter, it's highly certain that we can achieve ARR of over $10 billion.

Next question, please.

Your next question comes from Ellie Zhang with Macquarie.

Good evening, management. Thank you very much for taking my question. I just wanted to stay on the topics of that global comparison. So if you look at globally, the overseas peers seem to have captured the most immediate ROIs in enterprise agentic workflows, whereas for the consumer and the monetization would remain a bit lagged. So going forward, considering that Alibaba is investing in multi-fronts for infrastructure models, cloud, and queue and app, How do we evaluate the strategic priority and resources allocation between 2B and 2C initiatives? If going forward, enterprise side continues to gain more traction, will we consider gradually shift more resources away from QNAP to cloud and mass? Thank you.

Thank you, Manager Ceng, for answering my question. I would like to follow up with the question of the international agreement we just talked about. Because of the global pandemic, it seems that some of our overseas colleagues are better able to grasp the opportunities ahead in terms of the intelligent work flow of these enterprises. But for them, the transformation of the consumer side is still relatively post-pandemic. So in the future, since Alibaba is investing in a variety of Q&A, etc. So what do Alibaba think about the strategic priority of 2C and 2B? And what about the priority of resource allocation? If in the future, the enterprise side develops better, will we transfer more resources from 2C to, for example, mass?

Thank you very much for your question. Your question is actually a good one. But from the principle of AI itself, it is actually more of a computational revolution. In the computational revolution, in the end, we still have to be able to help users to complete tasks or help users to solve problems better. So from this perspective, I think 2B and 2C are essentially the same. But now, we see that no matter whether it is in the world or in China, the most able to accept customer payment wishes is in the 2B field. Because it is easier to calculate with its ROI, which is that the payment wishes of these companies are stronger. So most of our reasoning resources are actually invested in 2B. To be, to see, or to learn, to work, to live. To see the you can do that. Do you think that a couple of the schedule to go for a year and I saw how she are eating the But we believe that 2C's AI assistant will also, with the progress of technology and the acceptance of customers, or after helping it accomplish more tasks, slowly form its business model. We have actually seen this business model overseas, right? Including in China, I think in the next one or two years, we will also see a lot of commercialization in 2C's AI assistant.

Thanks for that question. It's a good question, but I think fundamentally from the perspective of AI development, it's really all about a paradigm shift in computing. And it's about leveraging this new technology to help users, whoever they are, to complete tasks and solve problems. And that applies equally on the 2C side as well as on the 2B side. Now, certainly at present, we see higher willingness to pay on the 2B side because it's easier to show a business case with compelling ROI for a business. And at present, most of our infrastructure resources are therefore channeled to the 2B side But at the end of the day, AI ultimately is an invention that's there to be a helper and assistant to humans to help humans with a whole range of things spanning their own daily life, their studies, and their work. And what AI does really is the same across all of those scenarios. It's about solving problems. And that's true for 2B and for 2C. So, certainly, there's less willingness to pay today for 2C, but we're already seeing a business model where consumers are paying for individual usage in the U.S., and I'm confident that the same will come to be the case in China, especially as the technology improves, as it's better able to help them solve real problems in their daily lives. So we think that ultimately this will be the same business model internationally, and I think we'll probably get there in China in the next, say, one to two years.

Next question, please.

So our next question comes from Joyce Chu with Bank of America.

我们会不会看到和国外类似的margin扩张的这么一个趋势? 谢谢。

Thanks, management. I have a follow-up question also on the future growth of the cloud business. And I'd just like to understand what your view is on EBITDA margins in the cloud business over the next few quarters. Do you think as this business accelerates, we can expect to see similar margins as we see in your international peers?

Thank you very much for your question. . . . . . . . . We hope to exceed the average growth rate of the industry to achieve a faster market share. This is our absolute market leading position. Profit rate is our second goal. But due to the current very clear trend in several industries, One of the characteristics of the industry is that, first of all, we think that in the next three to five years, the needs of the AI industry are still very difficult, because there are a lot of physical bottlenecks. Whether it's the construction cycle of the AI data center, or the production cycle of chips or memory in the industry, the physical expansion, the growth of the entire production capacity, we think it's still very difficult in three to five years. can support the growth of the needs of AI. So from this perspective, in the history of Alibaba, Alibaba has a very strong customer-scale effect and asset, our historical IT CapEx scale effect. In this scale effect, due to the current market supply and demand tension, now, in fact, our new server, a certain number of similar servers, the cost of deploying online this year is more than double the cost of deploying online two years ago, that is, the cost has increased by more than 100%. Such a new server's remodeling cost for our cloud customers, the needs of old customers and the needs of new customers, all have a price tag. . . . . The whole IT asset-related business is relatively a high-performance business. At the same time, as we have just mentioned, due to the optimization of the entire推理 technology, the performance of single-card will continue to improve. So, the situation we are seeing now, if we have the same server, and the revenue and profit level created by our white-chain platform is higher than our traditional cloud computing simple computing service, So, we believe that the increase in revenue of this business will also improve our future profit-making level. Another advantage is our full-time technical advantage. Pinduoguo's AI chips and Pinduoguo's AI chips' future scale and volume will help us to provide a return platform with the best cost-performance ratio in China. We believe that this push platform can also create a better profit margin and have a stronger coordination with our model. Because of these objective factors, we estimate that in the next one to two years, the profit margin of Alibaba will have a significant improvement. We will also see these changes in the last two seasons.

I think when it comes to the deep penetration of AI technology across all different industries, we're still really in the early days of that long process. But our objective is clear. Our objective is to achieve growth, to drive growth, to drive growth in token consumption, and to acquire larger market share. We aim to maintain that is faster than the market average in order to gain larger market share and firmly cement our absolute market leadership position. So those are the primary objectives and margin is still secondary. The other thing to be pointed out is that for the next three or even five years to come, there are physical constraints. on production capacity for chips, for memory, for the physical things that are needed to support all this growth in demand. An advantage that we have at Alibaba Cloud is the scale of our customer base as well as the scale effect from all of the CapEx that we've put in over these years. But in this environment of market scarcity, we're already seeing that the cost for us to deploy one new server this year is double what that same server would have cost a year ago. So the cost inflation has been over 100%. So given that higher replacement cost effect, we have a certain pricing power with respect to new customers and also old customers. So I think in the long term, the asset pricing effect will be positive for our revenues going forward. Secondly, we see very rapid growth in MAS as we reported to you. And inherently, as we said, MAS represents a much higher level of gross margin than IaaS or traditional types of IT operations. So as demand for inference continues to grow exponentially we expect this will be very positive for growth margin and due to the optimization of our reasoning technology the output capacity the productivity of a single cart will continue to to rise an additional factor is As we continue to scale up the deployment of THED, the THED chips represent the highest value for money compute power on the cloud platform, and that also will contribute to a better gross margin. But for several objective reasons that I've outlined, I think overall, in the next two to three years, we can expect to see significantly higher gross margin for Alibaba Cloud, and we can expect to start to see that in the next one to two quarters.

Peter, let's take the last question. Thank you.

Your last question comes from Gary Yu with Morgan Stanley.

Hi. for the opportunity. I have a question regarding CapEx. So what kind of level of CapEx investment is required in order to satisfy the demand from both mass and also the long-term cloud revenue? And also management mentioned about THAD opportunity. What is the current penetration of THAD being deployed on AdiCloud? And is this penetration increased margin uplift we should expect from our in-house chip?

Thank you.

Thank you very much for answering my question. My first question is about our capital spending. In order to achieve our mass and cloud business income goals, what kind of capital spending level do we need to maintain? Another question just mentioned. I would like to know how much the penetration rate has reached in our system and how much the penetration rate has improved with the further penetration. Thank you for your question.

Your first question is also very important. Uh. 2022 and 2023, which is the age when the AI model has not yet exploded, is the external revenue of Alibaba. That revenue target is probably a revenue target of 10 times the growth. The initial calculation can be understood as at least 10 times the data defense assets held by Alibaba and Alibaba at that time, in order to support our long-term business goals. So, in a way, the scale of the data center we are going to build in the future is basically a 10-fold increase compared to the growth in 2022. This includes all the CapEx we have invested in, as well as a lot of these algorithms that we have acquired in the OPEX method. This is our overall goal. Compared to the previous 3.8 billion yuan, our goal for the next five years is to get more than the original 3.8 billion yuan. . . . . . Thanks. So the first question is quite an important one.

Actually, in our prepared remarks delivered at the last quarter's earnings call, we set out a forecast for the coming five years for revenues, and it was a very high target. But essentially, I think if you compare where things were in the year 2022 before this explosive growth in AI models, And what we expect to need in 2033, I think we're talking about 10x increase. So we need 10 times the amount of data center infrastructure compared to what we had in 2022. But there are different ways to get that compute capacity. Some of it can be CAPEX. Part of it can also be OPEX. And we're actually now acquiring quite a bit of computing capacity using The situation is complex today for reasons we've discussed, but I think it's likely, given that kind of investment, that we will overshoot the original capex figure that we had stated of $380 billion. But at the same time, we can acquire some compute through OpEx. And as we have our own proprietary THET chips, we can actually also sell AI servers, leveraging those chips to other computing centers, or we can co-build computing centers with others. So there are different ways that we can get to where we need to get. But the bottom line is that the demand for computing compute infrastructure is going to be 10x of 2022.

This proportion is not in the minority yet. Of course, I would also like to share with you that besides our own GPUs, our CPUs, as well as our stored network chips, are all full-time self-operated. So, in the future, we will have the opportunity to use our full-time, from our GPU and CPU storage to network chips, to carry out full-time self-operation. Now, the proportion is relatively low because of some objective reasons. For example, the amount of semiconductor production in China is relatively small. Of course, in recent years, China's semiconductor production has continued to expand. So we think that with the increase in the penetration rate of the entire set of chips, it will have a very big impact on the increase in our毛利率. China China China China The same chip, whether it's power consumption or efficiency, there will be some differences compared to the more advanced chips abroad. But because we can see that the hourly rate of mainstream AI chips abroad is very high, right? It's basically close to 60% to 80% of the hourly rate. So whether it's the overall rate of domestic chips, um um

Yeah, so in terms of our T-head proprietary chips, they can be deployed across a very large part of our AI infrastructure and not just compute chips, but we have a full stack including But at present, the ratio is still relatively low, and that's because of constraints around production capacity in China, which has been limited. Of course, it's been growing. But as we deploy more and more of our own proprietary THET chips, the new chips will certainly contribute very, very significantly to gross margin expansion. It's true to say that domestically produced semiconductors in China lag behind the leading overseas ones in terms of energy efficiency and production efficiency. However, if you look at globally leading AI chip vendors today, their gross margins are as high as 60% or even 80%. So as we ramp up domestic chip production and the capabilities improve, I think there's a lot of room for our chips to be providing very high value for money as compared to that 60% to 80% gross margin that other vendors are taking.

Thank you. This brings us to the end of today's earnings call. We appreciate your time and participation, and we look forward to speaking with you soon.