Moo Live

was live ·

Alibaba Group Q3 FY2026 earnings conference call

Key Takeaways (AI-Generated)

Financial Performance

- Total revenue was RMB 284.8 billion with 9% like-for-like growth excluding disposed businesses

- Adjusted EBITDA decreased 57% due to strategic AI and quick commerce investments

- GAAP net income fell 66% to RMB 15.6 billion

- Cloud Intelligence Group external revenue accelerated to 35% growth with triple-digit AI product growth

Business Highlights

- Launched Alibaba Token Hub business group integrating AI model and application capabilities

- Qwen consumer app surpassed 300 million monthly active users across platforms

- T-Head shipped 470,000 AI chips with 60% serving external customers

- Quick Commerce business achieved 56% revenue growth to RMB 20.8 billion

Financial Guidance

- Target to surpass $100 billion combined cloud and AI external revenue within five years

- Quick Commerce targeting over 1 trillion RMB GMV by FY2028

- Quick Commerce expected to generate positive cash flow at GMV target achievement

- Quick Commerce business expected profitable in FY2029

Opportunities

- AI agent era creating exponential growth in addressable market from infrastructure to applications

- Full-stack AI capabilities positioning company for comprehensive AI transformation across industries

- Integration of Qwen app with Taobao and ecosystem platforms enhancing user engagement

- T-Head proprietary chips achieving cost reduction and supply chain resilience

Risks

- Intense competition in quick commerce requiring continued significant strategic investments

- Weak macro consumption and consumer sentiment impacting e-commerce growth trends

Full Transcript (AI-Generated)

Operator

Good day, ladies and gentlemen. Thank you for standing by and welcome to Alibaba Group's December 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 and 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

Thank you. Good day, everyone, and welcome to Alibaba Group's December quarter 2025 earnings conference call. Joining us today are Juice High Chairman, Eddie Wu, Chief Executive Officer, Toby Shi, Chief Financial Officer, Jiao 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 company website. A replay of the call will be available on our website later today. Now I will quickly cover the Safe Harbor.

Today's discussions may contain forward-looking statements based on current expectations and assumptions that are subject to risks and uncertainties. Actual results may differ materially. Please refer to the Safe Harbor statements that appear in our press release and investor presentation provided today.

Please note that certain financial measures are expressed on a non GAAP basis. 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 now I will turn the call over to Eddie.

Eddie Wu

Thank you and welcome to this quarter's earnings call. Over the past quarter, we maintained strong investment momentum in our two strategic priorities, AI plus cloud and Consumption Cloud. Intelligence Group revenue growth accelerated to 36%, while our quick commerce business continued to expand in scale with ongoing improvement in unit economics.

With the dawn of the AI agent era, the addressable market for AI infrastructure providers like Alibaba is set to grow exponentially. AI models and their capabilities are rapidly being embedded into mainstream work environments across all industries. With token consumption surging across sectors, cloud and software budgets for enterprise IT services have traditionally represented only around 5% of corporate revenue.

As model driven agents begin to handle mainstream work tasks across industries, our total addressable market will expand by several multiples from AI infrastructure to the application layer. Alibaba has built a complete full stack AI capability set to support the exponential growth in AI demand.

Faced with an industry transformation and strategic opportunity of this magnitude, Alibaba Group is itself entering a new phase of entrepreneurial reinvention and critical investment oriented toward the future. Next, let me share Alibaba's AI strategic road map.

We have complete full stack AI capabilities, chips and cloud computing form the AI infrastructure layer, while the AI application layer is anchored by Alibaba Token Hub and comprises foundation models, mass and both enterprise and consumer applications. Together, these give us end to end coverage across the full stack.

Given the enormous and sustained growth momentum of the AI market combined with Alibaba full stack positioning across the AI value chain, the business goal of Alibaba AI strategy is very clear. Over the next five years, our goal is to surpass 100 billion U.S. dollars in combined cloud and AI external revenue including mass.

Regarding our infrastructure driven by sustained strong AI demand, Cloud Intelligence Groups revenue from external customers accelerated to 35% this quarter with AI related product revenue delivering triple digit year over year growth for the 10th consecutive quarter. Cloud Intelligence Group's market share has grown for three consecutive quarters rising to 36% with our lead continuing to widen.

Alibaba Clouds cumulative external revenue through February for fiscal year 2026 officially surpassed 100 billion RMB. Over the past three months, token consumption on the Model Studio platform has grown by 6 times. We expect mass to become Cloud Intelligence Group's largest revenue product.

T Heads proprietary GPU chips have achieved scaled mass production. As of February 2026, T Head had cumulatively shipped 470,000 AI chips in real world business deployments through Alibaba Cloud. More than 60% of Tea Head chips serve external customers and we've completed scaled adoption for external customer AI workloads.

Tea Head now supports the workloads of over 400 enterprise customers across industries, including Internet, financial services and autonomous driving. We're confident that Tea Heads compute supply capacity will continue to expand, contributing high quality compute to our cloud infrastructure and mass platform strength. The overall competitiveness of our cloud services.

Regarding our application layer centered on the core mission of creating, delivering and applying tokens. We established the new Alibaba token hub business Group Ath. It comprises Tony Laboratory, the Amass business line, the Q and business unit, the Wukong business unit and the AI innovation business unit. It is the organizational foundation for executing Alibaba's AI strategy and the hub for efficient coordination across our AI businesses.

During Chinese New Year, we launched our latest generation large model Q and 3.5 Plus, which delivered outstanding performance across comprehensive benchmarks and reasoning, coding and agenda capabilities. 2 and 3.5 Plus demonstrated significant improvements in inference efficiency through foundational architectural innovation.

Building on Q and 3.5, we will soon release the next generation of models optimized for coding and agentic use cases. On the consumer application side, powered by the strength of our models, Q and consumer facing monthly active users have surpassed 300 million.

During Chinese New Year, we deepened integration across Alibaba ecosystem connecting queue and app with Taobao, Instant Commerce, Alipay, Fliggy, Damai and Amap, giving it unique capabilities relevant to everyday life and becoming Chinas first all in one personal AI assistant for life, work and learning.

We've also recently launched Wukong, our enterprise AI agent platform. Wukong is the world's first AI native enterprise grade agent platform, enabling AI powered upgrades to enterprise workflows while remaining compatible with each organization's data, permissions and management processes.

It serves as the unified interface for Alibaba's AI capabilities in enterprise work environments and the B to B capabilities of businesses across Alibaba's full ecosystem will be progressively integrated to support Wukong and becoming the best AI work assistant.

On Alibaba's other strategic priority, the consumption segment, we continue to advance our strategic initiatives. This quarter, our Quick Commerce business further expanded in scale with continued share growth, high customer retention and sequential improvement in both unit economics and average order value.

At the same time, Quick Commerce and e-commerce demonstrated clear synergies driving Taobao app monthly active consumers to double digit year over year growth. That concludes my remarks. I'll now hand over to Toby to share the financial update.

Toby Shi

Thank you, Eddie. Our strategic plus cloud and consumption businesses, we are seeing great momentum with gains in technology, customer adoption, market share and user engagement. On AI plus cloud, we have the full stack AI capabilities with all three core elements, model, cloud infrastructure and chips and leadership in each. With Queen, Alibaba Cloud and T HAT.

We also operate the most comprehensive consumer ecosystem in China, then can monetize through AI. The launch of Queen app was a major milestone and it can bring our consumer applications together. On consumption, our quick commerce business continued to gain GMB market share in December quarter, while unit economics and AOV also continued to improve.

Now let's look at the financial results. Consolidated basis total revenue was RMB 284.8 billion, excluding revenue from Sunna and in time revenue on a like for like basis would have grown by 9%. Total adjusted EBITAR decreased by 57%, primarily due to our strategic investments in technology related innovation initiatives and consumption front, including quick commerce business, partly offset by the improved operating results in cloud business and enhanced operating efficiencies across various businesses.

Our gap net income was RMB 15.6 billion, a decrease of 66%. Trading cash flow was an inflow of RMB 36 billion. Free cash flow was RMB 11.3 billion, a decrease of RMB 27.7 billion from the same quarter last year. We are reinvesting our cash flow to be a leader in AI and quick commerce.

As of December 31st, 2025, we have the US dollar 42.5 billion in net cash. Excluding that with maturities beyond five years, our net position stands beyond the US dollar 60 billion. This balance sheet strength gives us confidence to reinvest for long term growth.

Now let's look at our consumption businesses. Revenue from China E-commerce Group was RMB 159.3 billion, an increase of 6%. Customer management revenue increased by 1%. The slowdown in revenue growth was primarily due to weaker transaction activities and face down of the impact of software service fee implementation.

The Taobao APP achieved a double digit increase in Mac during the quarter, driven by the growing mindshare and increasing scale of our quick commerce business. Revenue from our Quickcommerce business increased 56% to RMB 20.8 billion during the quarter.

We executed our plan to further grow the scale of our Quickcommerce business, improve user experience, improve UE and increase AOV month over month. During the quarter, Alibaba China ecommerce Group adjusted EBITAN was RMB 34.6 billion. IT decrease of 43% primarily due to the investment in quick commerce, user experiences and technology.

Going forward, this adjusted EBITAR will continue to fluctuate quarter over quarter due to intense competition and significant investment in user experience. Revenue from AIDC grew 4% this quarter. AID CS adjusted EBITAR loss narrowed significantly year over year, driven by a combination of logistic optimization and investment efficiency enhancement. The UE of the Aliexpress's Choice business also improved on 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 grew 35%, up from 29% last quarter. AI related products continue to lead this momentum. We delivered our 10th consecutive quarter of triple digit growth in AI revenue. It's share of external cloud revenue continue to increase. This is a clear reflection of the scale and acceleration in our AI business.

Digestive EBITDA margin remained relatively stable at 9%. We will continue to invest in customer growth and technology innovation to increase adoption of AI, cloud infrastructure and strengthen our market leadership.

All other segment revenue decreased by 25% to RMB 67.3 billion, mainly due to disposal of Sunnah and In Time businesses, as well as the decrease in revenue from China, partly offset by the increase in revenue from Fresh Apple and Alibaba Health or others.

Adjusted EBITAR was a loss of 9.8 billion, primarily due to the increased investment in technology businesses, including Queen models and the consumer facing Queen, partly offset by the improved results of Tiny Hujin, DME and other businesses.

Queen model has become one of the most widely adopted open source model families globally, surpassing 1 billion cumulative downloads on Hugging Face by the end of this January. And the consumer facing Queen has surpassed 300 million Mau cross platforms, which reinforces user engagement in the expense long term monetization potential.

We have been increasing investments on these technology fronts, including the Spring Festival campaign. Building on the strong momentum and results achieved, as Eddie mentioned earlier, we will continue to invest substantially in Queen Models and Queen APP.

Our unallocated adjusted EBITA was a loss of RMB 2.7 billion compared to a loss of RMB 0.2 billion in the same quarter last year, which reflected cost associate with tail and rich retention incentive from the one off replacement awards plan of Ulama. Thank you. And we will now open for Q&A.

Lydia Liu

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. 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.

Operator

Thank you. If you would like to ask a question, you can press * then one on your phone and wait for your name to be announced. If you are on a speakerphone, please pick up your handset to ask you a question. And to give more people the opportunity to ask questions. Please keep yourself to no more than one question at a time. First question today comes from Robin Zhu at Bernstein. Please go ahead.

Robin Zhu

Thank you. Thanks management for taking my question. Could you give us some specific examples of how Token Hub will change how the different cloud and AI businesses work together going forward from an organizational standpoint? And you know, strategically, what changes or goals are you hoping to achieve with this new structure that you know improves on the previous arrangement going forward?

And then you know, if management could share a hierarchy of priorities and cloud and AI, is it market share and revenue growth such as the target you just announced versus having, you know, the best first party model capabilities versus consumer side traction with customers using agentic AI or anything else? Thank you.

Eddie Wu

Great. Thank you very much for your question. I think that the goal and purpose of the establishment of the Ath business group is very much connected to the era that we're now in as of the end of 2025 and going into the first few months of 2026 in terms of the development of AI. You know, we're now in the agent driven era of AI development and this is different from the earlier period of AI development.

In the agentic AI era, we need to achieve a very close integration of model with application. In the earlier AI era, a lot of model training data was static data. But in the agentic era, we need to enhance the integration between models and applications and achieve tight integration. And a lot of the data is now coming from the customer side.

So if you look at the different layers involved in AI deployment from an application model, the AI infrastructure through to chips, I think what's most different and most important about the agentic AI era is the need to achieve this tight integration between application and model. That's the critical priority.

Next, let me address the interconnection and synergies among the different businesses in relation to Ath. If if you look at the the, the trends of where this industry is going and, and we think we see these trends very clearly. The AI agents will be tightly integrated together with the application layer and there will be a multitude of highly diverse applications in the two consumer or 2C space.

We're strongly developing the Q1 app as a personal assistant for individuals and in the 2B space, we're positioning Wukong as a 2B assistant. In the AI application layer, there will be a multitude of different industry and vertically specialized applications to serve different industry use cases.

And all of this needs to be supported by very robust model as a service mass layer. So mass supports of course our own internal applications as well as a multitude of external and industry specific use cases that leverage AI. So in this context, we see massive value that we can provide and a huge total addressable market or or tab.

So going forward, we see the AI application layer as the main channel through which tokens will be distributed. And the stronger the model capabilities that you can offer at the mass layer, the more attractive and compelling all of these different offerings will be to customers. That is the business logic that we have laid out within this new business unit.

So from the perspective of both the model and the application layers, our top priority absolutely is to develop the most intelligent models. And I really need to emphasize that only when you have the most powerful models can you truly drive the deployment of AI applications across all kinds of different industries. Only with the strongest models can you attract applications from across diverse industries to adopt our mass offering.

However, in order to build the most robust models, you need to have very close collaboration with various industries and with our own 22-C and 2B applications to connect with our mass to applications across all kinds of different industries and use cases.

So we need to get more users to leverage and make use of our our models in order to gradually be able to leverage the data flywheel effect. Only in that way can we continuously enhance the capabilities of our models. So that's one of the reasons why we have established the Ath business unit at this time.

So to summarize, I would say our top priority is definitely to enhance model capabilities. However, to enhance model capabilities requires concerted efforts across the entire model pipeline, as well as on the application and infrastructure side, in order to achieve sustained improvements over the long term.

Operator

Thank you. Your next question comes from Joyce Ju at Bank of America. Please go ahead.

Joyce Ju

Good evening, management. Congrats on the solid progress you've made in cloud and AI and thanks for taking my question. My question is we see CMR growth. Notably in the December quarter, given the macro pressures we have seen Chinas online retail sales only up to present your video in the fourth quarter 25 but more recently MPs data point to a re acceleration in January and February. Could you share your latest view on the? Trends heading into the March quarter and whether you have stored that you see? Any improvement in consumer sentiment? Thanks.

Toby Shi

Thank you for your question. Indeed, in the December quarter, weak macro consumption, warm winter, the later timing of the Chinese New Year challenged the growth for the December quarter. And due to the extended promotional season, our investments in consumer benefits increased compared to previous years. So as a result, the CMR and EBITDA trend softened going into the March quarter with the improving consumer sentiment that we've observed and momentum from our quick commerce strategy. Our physical goods GMV and CMR trend have significantly recovered from the December quarter and EBITDA is expected to improve accordingly.

Operator

Thank you. Your next question comes from Gary Yu at Morgan Stanley. Please go ahead.

Gary Yu

Hi, thank you management for the opportunity. My question is related to Quick Commerce. I understand that, you know, in the past couple of months we have achieved certain milestone in terms of TDP market share and also your improvement. How should we look at the priority going forward? Are we aiming for, you know, you know, to share or you know, hoping to take this opportunity to improve unit economics, reduce loss? And how should we look at the synergy between quick commerce and traditional e-commerce? And how should we see these synergy to translate into CMR better growth going forward? Thank you.

Jiao Fan

Certainly well. While growing our market share, we have continued to significantly improve UE driven by improvement in fulfillment logistics efficiency, by improvement in monetization as well as by order mix optimization. Driven by those factors, we expect to further optimize UE in the coming quarters.

In terms of the positive impact that Quick Commerce is bringing to our conventional e-commerce business and to our entire ecosystem, we saw a very significant increase in AA CS on the platform in the past year. Our AAC number increased 150 million in 2025, including 100 million conventional e-commerce physical goods, AA, CS, which is more than the previous three years combined.

Now new consumers RPU and purchase frequency are lower than that of existing users. So we aim to continually increase their RPU and purchase frequency, which will serve as a new growth engine for our platform in the coming years. Quick Commerce is clearly driving sales in various categories such as food and fresh produce and healthcare and is contributing to fresh IPO and Tmall Supermarkets accelerated growth on.

In terms of the outlook, we maintain our target of achieving over 1 trillion RMB in Quick Commerce GMV by FY20 8. We expect to generate positive cash flow when the GMV target is achieved and we expect the Quick Commerce business to be profitable in FY20 9.

E-commerce has become a cornerstone of our e-commerce business, playing a strategically vital role in the AI era by driving customer acquisition, enhancing user engagement, fulfilling diverse consumer demands, increasing transactions and improving monetization and supporting logistics infrastructure. We are committed to investing in quick commerce in the next two years towards achieving the one trillion R MB GMV target as a market leader.

Operator

Thank you. Your next question comes from Alicia Yap at Citigroup. Please go ahead.

Alicia Yap

Hi, good evening, management. Thanks for taking my question. I have a questions regarding your cheap business tea hat Pink Ogre. So that's been reports that Alibaba plans to spin off the tea hat unit as a separate listing. Can management provide any information of this And if so, what is the expected time frame for this to occur? And in the meantime, can you share more operating metrics? So in addition to the 470,000 chips that you mentioned. To external customers, how we reconcile that number, the shipments to the revenue size and also what is the expected growth rate for your chip business in the coming year? And I think you mentioned currently is a 60% of this is from external customer. So maybe can you also share with us, are these chips you know for external customer mainly used for inferencing and then for internal is it used for model training and also inferencing? And then lastly, how do the Pinto girls chips or tea has chips compare to other domestic chips management can share some detail will be great. Thank you.

Eddie Wu

OK. Thank you very much for this question. And I'd like to take the opportunity to expand on this a bit because tea head is a very important component of Alibaba's company wide AI strategy. So in the context of China's domestic AI chip ecosystem, we we firmly believe that Tea Head is ranked in the top tier of the domestic AI chip ecosystem in terms of the technology capabilities and product capabilities.

Our products cover the entire AI workflow from model training and fine tuning through to inference. And our T Head AI chips are already in extensive large scale use via Alibaba Cloud both for training workloads and for Bai lien inferencing use cases.

At the same time, over 60% of T Head chips are being used by external commercial customers across Alibaba Cloud's public and hybrid cloud offerings. The external commercial clients span multiple industries, including Internet finance, autonomous driving and intelligent manufacturing. And these external commercial customers are utilizing Tea Head ships in both their training and inferencing workloads.

Moreover, on the Tea Head software stack, we have excellent compatibility with the Linux ecosystem, so customers can migrate their systems easily without spending a lot of time on the migration.

Another another point I would make is that in my view, T heads significance to Alibaba lies not only in our aspiration to close the gap between domestically produced chips and foreign counterparts. Foreign produced chips in terms of manufacturing processes and overall performance across various dimensions.

But given that our chips still lag behind foreign counterparts in performance in various respects, we aspire to engage in more profound Co design with Alibaba's cloud infrastructure and the Q and model to provide improved cost effectiveness. So this is one key differentiator in how we approach chip design at at Tea Head that sets us apart from other chip companies.

Our our primary goal is to create AI capabilities that offer superior value for money. This will make it a key product for the Bailian platform, allowing us to reduce inference costs going forward.

Beyond generally improving our AI efficiency and reducing costs, there's another factor at play, namely the unique circumstances currently facing the AI industry in China. In that context, one significant benefit for us is the guaranteed supply of AI computing power because I believe that over the next three to five years, global AI computing power will be an extremely short supply, especially in the Chinese market.

As the only cloud computing company in the Chinese market with proprietary chip development capabilities, T Head is of paramount importance. Therefore, to the Alibaba Group, increasing the supply of AI computing power will help our cloud and AI businesses, including our mass business, to achieve stronger growth momentum.

At T Head over the past two years, we've successfully commercialized and launched chips with total volume exceeding 470,000 units with annual revenue reaching the CN¥10 billion level. Look looking ahead to 27 well through through 2026. This year through 27 next year, we expect T Heads production capacity for high quality AI chips to continue to expand.

This will provide robust computing power support for our group's AI business and serve as a a powerful growth driver for our overall AI initiatives. We also believe that future improvements in profitability will be achieved, further enhancing profit levels, which will also be very beneficial.

Overall, T heads value to Alibaba goes beyond cost optimization. It primarily serves to ensure supply chain resilience and in an era of scarce computing power I, I see this as crucial to Alibaba's AI strategy. So it is possible and we don't rule out the idea of T Ed considering an IPO in the future, although we currently do not have any definitive timeline.

Operator

Thank you. The next question comes from Yuan Liao at Citix. Please go ahead.

Yuan Liao

Thank you for taking my question, Management. My question is about the business objectives for your AI strategy that you just mentioned. Revenue for the next 5 years is expected to exceed 100 billion. Could you provide more details on this target? For example, if the next five years is through to 2031, what kind of CAGR would that correspond to in this five year. And could you also break out what will be driving that growth and how we should understand those drivers given this scalable growth in revenue, when can we expect to see sustained improvement in Alibaba clouds margins? Thank you.

Eddie Wu

Thank you for your question. So yes, we certainly believe that within five years revenues from our AI and cloud related business will exceed $100 billion. We think that that is very clear. If you look at the market growth that we're seeing today are the strength of our product portfolio and the road map to get there.

I think that the major driver underlying all this really is continued breakthroughs in the capabilities of large AI models. And we've certainly seen a very clear trend over the past couple of months, the first two months of 2026, whereby large models have now gained the capability to execute complex B to B workflows.

More and more enterprises are deploying agents powered by large models to handle end to end business tasks. And that marks a fundamental transformation in the way that the market looks at IT budgets, IT budgets traditionally allocated to AI and cloud services.

The shift really is that many enterprises now when consuming tokens don't treat token consumption as part of their IT budget any longer. Instead they see tokens as part of their overall operational or R&D costs. Tokens are a key component of their production inputs, not just a part of their IT budget. So this is the most fundamental long term factor that we see driving future AI growth.

I believe that the largest drivers of growth will come from three areas. First is the mass driven business, which really is the core growth engine and the growth of our mass business will be supported by a variety of different use cases including our own applications as well as a diverse array of AI application scenarios from across our our customer base and. Across various different industries, including AI, application, software.

And we believe that the growth driven by mass initiatives will be a key driver of future revenue for both AI and cloud services. But secondly, for AI and cloud computing, there's another very important growth opportunity. Of course, we believe that public mass will be a substantial market in the future, but in a considerable number of larger medium and large sized enterprises there'll also be a demand for enterprise level internal inference and training a new marketplace and that market will continue to exist in the long term.

It's not one that will disappear simply because each enterprise makes decisions based on its own business model and the security requirements of its specific use case or the particularity of an application scenario. So for some application scenarios, enterprises will opt to use public mass API services, while many others will be based on privately deployed solutions within the enterprise. So those kinds of application scenarios represent a a large incremental growth opportunity for Alibaba clouds, AI infrastructure.

3rd, there's another important driver, important opportunity that I think tends to get ignored a lot of the time and I'm talking about CPU centric cloud computing, the traditional cloud computing which still has significant room for expansion in this AI enabled era.

So traditional cloud computing is designed for IT engineers, which in China may number a few million, say perhaps no more than 10 million potentially traditional IT engineers and those have been the traditional cloud computing customers.

However, in the future there could be billions of agents that are created by large AI models and their operating environments. The operating environments of these agents will also require substantial support from traditional CPU centric cloud computing. They need these traditional CPUs as well as databases, storage and large amounts of memory to support their long term problem solving and sustained operations.

So the challenge lies in transforming the traditional cloud computing market, shifting from a cloud platform designed for human users, those IT engineers, to one that's optimized for agent based invocation. So I believe there's tremendous room for growth there. So a key challenge for us this year is transforming traditional cloud computing into a platform that is better suited for agentic use, and that's a key focus of Alibaba Cloud's upgrade.

As the revenue from this business continues to grow, our AI business will undergo transformation, transformation and upgrading, shifting from selling resources to selling intelligence, selling intelligent capabilities. And I think that represents a massive upgrade to the business model.

At the same time, by integrating our proprietary T head chips, we are achieving and will achieve cost reduction and efficiency gains. We believe that as our AI and cloud business continues to grow in revenue scale cloud profitability should become increasingly visible and we see it is on a steady path of improvement.

However, the the process of continued improvement is not a linear one. It's it's possible that there could be a scale effect breakthrough, the achievement of an economy of scale or the scaling up of our T head ships and there could be a massive leap forward. But I think that's, you know, a function of the product as a whole and those kinds of economies of scale, but it will not unfold in a linear fashion.

So you asked about the, the kegger, the compound annual growth rate from 2026 through to 2031. You know, I think you can plug that into your calculator and figure out what it would be assuming it were to be linear. But I, I don't think that it will be linear. Our R&D investment and growth in the market will not be linear. And some of the investments we're making today may, may not yield significant growth until one or or even 2 years from now.

However, regarding that overall five year goal, we are highly confident in our ability to achieve it.

Operator

Thank you. The last question comes from Alex Yao at JP Morgan. Please go ahead.

Alex Yao

Thank you. I'd like to shift the topic a little bit and ask a question about e-commerce. You'd previously said that we were in a three-year investment cycle for e-commerce. I'm wondering if that is now being adjusted or being driven by the new opportunities that have arisen in instant commerce and in agentic commerce or if we're still thinking of it in terms of the original three-year plan which would put us now in the middle really of that three-year. Where I guess we would start to be reaping the the returns on a stable basis from those investments. So if you could speak to us about the overall direction of e-commerce in the context of that three-year investment cycle that you'd told us before and also share with us how you're thinking about being positioned and your strategies on this e-commerce track. Thank you.

Jiao Fan

Thank you. So as I just mentioned, we are making a very significant investment in the instant retail business this year, the quick commerce business this year. And at this point in time, we're seeing a highly definitive opportunity in this space. So again, as I just mentioned, we will continue to invest heavily over the next two years in order to achieve our goal of surpassing 1 trillion RMB in quick commerce sales. We also believe that in two years time, our investments in quick commerce will generate positive economic returns for our e-commerce business as a whole.

But I'd like to add to that by bringing in the, the dimension of AI, because Eddie's talked a lot about AI. I believe that AI will also have a very, very significant impact on e-commerce. However, three years is too long a time to talk about when it comes to AI because AI today is evolving at a pace that's measured in weeks or, or in months. But but that's precisely why we're making significant investments on the AIAI front and we are leveraging AI to roll out new experiences for consumers and for merchants as well as upgrading merchants business models with AI.

We believe that AI will allow us to make huge upgrades in e-commerce across different parts of the e-commerce business. It's beneficial for our B to B business where we're seeing tremendous opportunities for its deployment and we will actively seize on all of these new opportunities.

Lydia Liu

OK. That wrap up the Q&A session of today's earnings call. Thank you very much for joining us today and we look forward to speaking with you soon. Thank you.

Operator

That concludes the call for today. Thank you for participating. You may now disconnect your alliance.

Details at Alibaba IR

Tips: This summary was generated by an AI language model based on publicly available information, including auto-generated subtitles and publicly released audio from third-party sources. While efforts have been made to ensure accuracy, AI-generated content may contain errors or omissions. Please refer to the official materials released by the respective listed companies for the most accurate and up-to-date information. This content is for informational purposes only and does not constitute investment advice or a recommendation to buy or sell any investment products. The views and summaries presented do not reflect the official position of moomoo. Moomoo makes no warranties, express or implied, regarding the accuracy, timeliness, or completeness of this content and shall not be held liable for any losses arising from its use. The copyright of any original conference call content remains with the respective listed companies.

179K Views