Cuộc họp công bố kết quả kinh doanh Q1 năm tài chính 2027 của Alibaba (BABA): Doanh thu mảng đám mây tăng 45%

Thông tin cốt lõi

• Doanh thu của Tập đoàn Alibaba tăng 9% so với cùng kỳ năm trước lên 269,0 tỷ RMB trong quý 1 năm tài chính 2027, nhờ sự tăng trưởng của mảng điện toán đám mây và thương mại nhanh.
• Doanh thu từ khách hàng bên ngoài của Alibaba Cloud tăng 45%, mức tăng trưởng nhanh nhất trong 22 quý. Doanh thu từ các sản phẩm liên quan đến AI đạt 12,4 tỷ RMB, chiếm 35% doanh thu đám mây từ khách hàng bên ngoài và đạt tốc độ quy năm là 49,5 tỷ RMB.
• EBITDA điều chỉnh giảm 30% xuống 27,3 tỷ RMB, trong khi lợi nhuận thuần GAAP giảm 75% xuống 10,4 tỷ RMB, chủ yếu do đầu tư vào công nghệ, thu nhập hoạt động thấp hơn và lợi nhuận liên quan đến đầu tư giảm.
• Chi phí vốn đạt 67,7 tỷ RMB và dòng tiền tự do ghi nhận mức dòng tiền ra 44,7 tỷ RMB, phản ánh việc tiếp tục đầu tư vào hạ tầng AI và công suất tính toán.
• Doanh thu mảng thương mại nhanh tại Trung Quốc tăng 45% lên 53,3 tỷ RMB. Ban quản lý cho biết Taobao Instant Commerce đã cải thiện hiệu quả kinh tế trên mỗi đơn vị và thu hẹp đáng kể khoản lỗ trong khi vẫn duy trì thị phần.
• Ban quản lý kỳ vọng tăng trưởng doanh thu mảng đám mây sẽ tiếp tục tăng tốc và biên EBITDA sẽ cải thiện so với quý trước. Công ty cũng duy trì mục tiêu đạt ARR của MaaS hơn 30 tỷ RMB vào cuối năm.

Dữ liệu tài chính quan trọng

Kết quả Kinh doanh và Hoạt động

AI và điện toán đám mây

AI tiếp tục là động lực tăng trưởng chính của Alibaba. Các sản phẩm liên quan đến AI chiếm 35% doanh thu từ khách hàng bên ngoài của Alibaba Cloud, với doanh thu định kỳ trải dài trên các mảng tính toán AI, MaaS và các ứng dụng AI. Ban quản lý cho biết nhu cầu diễn ra trên diện rộng ở các mảng tính toán, lưu trữ, dịch vụ mô hình và ứng dụng.

ARR của các dịch vụ mô hình và ứng dụng, bao gồm MaaS, đã vượt quá 16 tỷ RMB tính đến tháng 8. Ban quản lý cho biết nhu cầu tính toán tiếp tục vượt nguồn cung và kỳ vọng công suất bổ sung sẽ hỗ trợ tăng trưởng doanh thu nhanh hơn.

Alibaba đang đầu tư vào các mảng chip, hạ tầng đám mây, mô hình và ứng dụng. Chip Zhenwu độc quyền của công ty đã phục vụ hơn 650 khách hàng của Alibaba Cloud tính đến đầu tháng 8. Ban quản lý cũng cho biết công ty đã rút ngắn thời gian bàn giao trung tâm dữ liệu AI quy mô siêu lớn xuống còn 100 ngày.

Mảng Phòng thí nghiệm và Ứng dụng AI ghi nhận mức lỗ EBITDA điều chỉnh là 13,9 tỷ RMB, phản ánh khoản đầu tư lớn hơn vào năng lực AI và chi phí suy luận cho ứng dụng Qwen. Mức lỗ đã thu hẹp so với quý trước do chi phí tiếp thị giảm.

Thương mại điện tử và thương mại nhanh

Doanh thu Tập đoàn Thương mại điện tử Alibaba tăng 4% lên 205,9 tỷ RMB. Doanh thu từ dịch vụ quản lý khách hàng giảm 7%, nhưng ban quản lý cho biết con số này sẽ tăng 1% nếu không tính đến tác động giảm trừ doanh thu của một chương trình phát triển kinh doanh mới.

Doanh thu mảng thương mại nhanh tại Trung Quốc tăng 45% lên 53,3 tỷ RMB, nhờ sự thúc đẩy từ Freshippo và Taobao Instant Commerce. Giá trị đơn hàng trung bình cao hơn cùng hiệu quả xử lý đơn hàng và logistics được cải thiện đã hỗ trợ hiệu quả kinh tế trên mỗi đơn vị tốt hơn.

Alibaba có kế hoạch đẩy mạnh tích hợp Freshippo và Tmall Supermarket, mở rộng các kho tiền đồn và tăng cường bao phủ các ngành hàng phi thực phẩm. Ban quản lý kỳ vọng khối lượng giao dịch thương mại nhanh phi thực phẩm sẽ vượt khối lượng giao dịch thực phẩm trong năm tài chính tiếp theo.

Thương mại điện tử quốc tế đối mặt với áp lực từ chính sách thuế quan và các điều kiện địa chính trị. Tuy nhiên, ban quản lý cho biết mảng kinh doanh xuyên biên giới đã cải thiện khả năng sinh lời trong khi vẫn duy trì đà tăng trưởng khối lượng giao dịch. Các nền tảng địa phương tại Thổ Nhĩ Kỳ và Trung Đông tiếp tục tăng trưởng, trong khi hiệu quả hoạt động được cải thiện ở Đông Nam Á.

Dự báo của Ban quản lý

• Ban quản lý kỳ vọng tăng trưởng doanh thu của Alibaba Cloud sẽ tiếp tục tăng tốc trong các quý tới khi nguồn cung tính toán được mở rộng.
• Biên EBITDA của mảng đám mây dự kiến sẽ cải thiện so với quý trước nhờ hiệu suất sử dụng cao hơn, tối ưu hóa danh mục sản phẩm và các trường hợp sử dụng mới.
• Ban quản lý dự báo tốc độ doanh thu quy năm đối với các sản phẩm liên quan đến AI có thể tiến gần mức 10 tỷ USD trong quý tới.
• Alibaba duy trì mục tiêu đạt ARR của MaaS vượt 30 tỷ RMB vào cuối năm.
• Ban quản lý vẫn tự tin sẽ đạt 100 tỷ RMB doanh thu đám mây từ khách hàng bên ngoài vào năm 2030 và nhìn thấy lộ trình hướng tới biên lợi nhuận gộp 20%.
• Mức lỗ của mảng Phòng thí nghiệm và Ứng dụng AI dự kiến sẽ thu hẹp trong các quý tới khi hiệu quả huấn luyện mô hình và tiếp thị ứng dụng Qwen được cải thiện.
• Ban quản lý kỳ vọng mảng thương mại nhanh sẽ đạt lợi nhuận tổng thể vào năm tài chính 2029. Về dài hạn, ban quản lý tin rằng thương mại nhanh có thể đóng góp 30% tổng giá trị giao dịch (GMV) của nền tảng.

Rủi ro và Các điểm cần theo dõi

• Việc đầu tư mạnh vào hạ tầng AI đã dẫn đến mức dòng tiền ra của dòng tiền tự do là 44,7 tỷ RMB trong quý.
• Alibaba đã chi 190 tỷ RMB trong kế hoạch đầu tư vốn 3 năm trị giá 380 tỷ RMB tính đến cuối quý kết thúc vào tháng 6. Ban quản lý cảnh báo rằng chi phí vốn hàng quý có thể biến động theo chu kỳ bàn giao và mua sắm phần cứng.
• Nhu cầu tính toán hiện đang vượt quá nguồn cung, có khả năng hạn chế việc chuyển đổi doanh thu trong ngắn hạn mặc dù nhu cầu của khách hàng rất lớn.
• Giá các linh kiện bán dẫn gia tăng, gây thêm áp lực lên chi phí hạ tầng.
• Doanh thu từ dịch vụ quản lý khách hàng giảm, trong khi thương mại điện tử trong nước tiếp tục đối mặt với những thách thức vĩ mô ngắn hạn.
• Các chính sách thuế quan và điều kiện địa chính trị đang tạo áp lực lên đà tăng trưởng thương mại điện tử quốc tế.
• Mảng Phòng thí nghiệm và Ứng dụng AI vẫn đang thua lỗ do tiếp tục đầu tư và chi phí suy luận.

Những điểm nổi bật trong phần Hỏi & Đáp với Chuyên gia Phân tích

Hiệu quả hoàn vốn đầu tư AI: Ban quản lý cho biết thiết bị liên quan đến AI thường đạt điểm hòa vốn trong vòng 3 năm và có thể rút ngắn xuống 2,5 năm hoặc ít hơn khi biên lợi nhuận gộp cải thiện và các chip độc quyền thay thế các linh kiện mua ngoài. Ban quản lý cũng nhấn mạnh rằng con số chi phí vốn hàng quý 67,7 tỷ RMB không nên quy thành con số cả năm vì thời điểm mua sắm không đồng đều.

Động lực tăng trưởng mảng đám mây: Alibaba xác định nhu cầu suy luận, nguồn cung tính toán bị hạn chế, các dịch vụ MaaS có biên lợi nhuận cao hơn, chip độc quyền và năng lực đám mây toàn diện (full-stack) là những động lực tăng trưởng chính. Ban quản lý mô tả tính toán AI trên đám mây là hạ tầng hỗ trợ việc huấn luyện, suy luận, agent, lưu trữ, cơ sở dữ liệu và mạng.

Hiệu quả kinh tế của MaaS: Alibaba cho biết các mô hình độc quyền tạo ra phần lớn doanh thu MaaS, mặc dù các mô hình của bên thứ ba cũng đóng góp đáng kể. Ban quản lý chỉ ra rằng biên lợi nhuận gộp nhìn chung là tương đương giữa các mô hình độc quyền và bên thứ ba được lưu trữ trên nền tảng Bailian.

Chiến lược thương mại nhanh: Ban quản lý có kế hoạch mở rộng các ngành hàng phi thực phẩm, tăng cường năng lực kho tiền đồn và tích hợp chặt chẽ hơn giữa Freshippo và Tmall Supermarket. Công ty xem thương mại nhanh là đường cong tăng trưởng thứ hai tiềm năng cho thương mại điện tử.

Khả năng kiếm tiền từ AI toàn diện: Ban quản lý kỳ vọng giá trị trong ngắn hạn vẫn sẽ tập trung vào chip và hạ tầng đám mây AI do nguồn cung bị hạn chế. Về dài hạn, ban quản lý tin rằng việc thương mại hóa có thể dịch chuyển sang các sản phẩm và kết quả AI thay vì chủ yếu phụ thuộc vào việc truy cập mô hình dựa trên API.

Toàn văn Biên bản Cuộc họp Báo cáo Kết quả Kinh doanh

Toàn văn cuộc gọi công bố kết quả kinh doanh

Phần trình bày của ban lãnh đạo

Operator

Good day, ladies and gentlemen. Thank you for standing by. Welcome to Alibaba Group's June Quarter 2026 Results Conference Call. [Operator Instructions].

I would now like to turn the call over to Lydia Lu, Head of Investor Relations of Alibaba Group. Please go ahead.

Lydia Lu

Thank you. Good day, everyone, and welcome to Alibaba Group's June Quarter 2026 Earnings Conference Call. Joining the call today are Joe Tsai, Chairman; Eddie Wu, Chief Executive Officer; Toby Xu, Chief Financial Officer; Jiang Fan, Chief Executive Officer of Alibaba E-commerce Business Group.

Before we get started, I would like to remind you that today's discussion may contain forward-looking statements based on management's current expectations that are subject to risks and uncertainties. We also make reference to non-GAAP financial measures. Reconciliations between GAAP and non-GAAP measures are included in today's earnings press release and investor presentation. Our comments will be on year-over-year comparisons unless we state otherwise. A replay of the call will be available on our website later today.

With that, I would like to turn the call over to Eddie.

Yongming Wu

Good evening, good morning, and welcome to Alibaba Group's Earnings Call for the First Quarter of Fiscal Year 2027. Over the past quarter, Alibaba's strategic AI investments have translated into robust results with a total group revenue growing 9% year-over-year. AI commercialization has also accelerated across the board. Alibaba Cloud's external revenue grew 45% and EBITDA increased 133% year-over-year, continuing to deliver on our commitment to accelerate growth. Revenue from AR rated products has maintained a triple-digit growth for the 12th consecutive quarter with annual revenue run rate surpassing RMB 49.5 billion around USD 7.3 billion. It is the core engine of Alibaba's Cloud's growth acceleration.

I'll now walk you through 4 key areas: AI and cloud commercialization, full-stack AI capabilities, AI application ecosystem and consumption business. First, AI and cloud commercialization accelerated across the board and is expected to sustain high growth going forward. This quarter, Alibaba Cloud's external revenue growth accelerated to 45%, a 22 quarter high, while adjusted EBITDA margin reached 11.6%. Notably, this 45% growth was broad-based driven by compute storage model as a service, mass and AI applications. We proactively scaled back low-margin business continuing to improve the quality of our growth. This quarter, annual revenue run rate from AI-related products exceeded RMB 49.5 billion and its share of Alibaba Cloud's external revenue rose to 35%.

AI-related products generate significantly higher gross margins than the average cloud portfolio. Our recurring AI-related product revenue spans multiple layers, AI compute mass and AI applications. This multilayered mix of AI revenue sources and monetization models means growing customer demand at any layer converts directly into commercial opportunity for us. This structural advantage will underpin sustained rapid growth in recurring AI-related product revenue going forward. Surge in AI agents directly drives demand for tokens and GPU compute while also significantly boosting demand for our traditional cloud products across CPU compute, storage, databases and networking.

Alibaba Cloud is undergoing a comprehensive upgrade to an Agentic Cloud. Based on the latest data, the ARR of our model and application services, including mass, has surpassed RMB 16 billion. Based on current market feedback and our contract pipelines, compute demand will continue to outstrip supply. As we continue to ramp up our supply, our AI and cloud revenue growth will accelerate further in the coming quarters. alongside continued improvement in profitability. Second, our full stock AI capabilities continue to strengthen, marked by the scaled commercialization of proprietary chips, faster model iteration and a driving open source ecosystem.

This quarter, deepening synergy between proprietary T-Head chips and proprietary foundation models further improved our AI commercialization efficiency. T-Head has established a full stock proprietary silicon portfolio, spanning GPU, CPU and networking chips. As of early August, the Zhenwu chips have served more than 650 customers on Alibaba Cloud. The super node instance powered by T-Head's next-generation Zhenwu M890 AI processor recently launched on Alibaba Cloud at commercial scale. We expect supply to continue ramping up in the second half of the year to meet strong customer demand.

Alibaba Cloud's Zhenwu M890 super node can efficiently run inference workloads for foundation models with more than 2 trillion parameters, both KBK3 and Q1 3.8 MAX are already using it to provide mass services to external customers. At the data center layer, Alibaba Cloud has cut the delivery time for hyperscale AI data centers to 100 days, a world-leading pace that will significantly speed up our global compute infrastructure build-out. At the model here, our model release cadence has intensified over the past months with major iterations across our large language, image, audio, video and music models, all ranking among the world's top tier.

Last week, we opened the modeled weights of Q1 3.8 MAX with 2.4 trillion parameters and the Q13.827B model series. To date, the Q1 model series has been downloaded more than 3 billion times globally with more than 300,000 derivative models built on it. We believe a thriving open source model ecosystem drives greater demand for our cloud computing services creating a virtuous cycle.

Third, our AI native applications span both enterprise and consumer use cases driving rapid growth in token consumption. On the enterprise side, we launched Q1 work, a new AI productivity product built for enterprise workforce scenarios, delivering agent capabilities at scale. We expect productivity agents to become another engine of ARR growth. On the consumer side, the Q1 app continued to steadily grow its user base and is expanding the range of its value-added offerings.

Through close coordination between Alibaba Token Hub and Alibaba Cloud, we're running a highly efficient commercial flywheel across compute models, tokens applications and monetization Fourth, our e-commerce businesses remained solid this quarter. In quick commerce, we continued to narrow losses substantially while growing business scale by 45% with unit economics improving quarter-over-quarter. Having crossed the AI commercialization inflection point this quarter, we're now seeing growth accelerate and margins expand this quarter. Our AI businesses own capacity to self-fund and sustain itself is strengthening giving us greater confidence to keep investing. Looking ahead, AI has become Alibaba's most certain growth engine, we will stay strategically disciplined and drive long-term growth through our full stack AI capabilities.

I'll now hand over to Toby to walk you through our financial results. Thank you.

Toby Xu

Thank you, Eddie. Our strategic priorities in AI plus cloud and consumption businesses backed by disciplined investments delivered strong results this quarter. Cloud segment revenue growth further accelerated to 45% with its EBITDA margin sequentially rising to 12%. AI-related product revenue continued to drive this momentum marking the 12th consecutive quarter of triple-digit growth and accounting for 35% of external cloud revenue. The strong performance demonstrates growing customer adoption of our full stack AI capabilities, spanning AI agents, models, cloud infrastructure and preparatory chips as well as our enhanced scale efficiencies and the robust pricing power in a supply-constrained market.

On consumption, Taobao instant commerce continued to improve its unit economics while maintaining market share. Overall e-commerce EBITDA remained relatively stable year-over-year. To realize synergies across our commerce platforms and strengthen our full stack AI capabilities, we have implemented strategic realignment of certain businesses in our financial reporting. Starting from this quarter, our segment reporting will present the following: first, Alibaba e-commerce group; second, AI cloud and computer services; third, AI labs and applications; and number four, all others.

Now let's look at the financial results for this quarter. Total revenue increased 9% year-over-year to RMB 269 billion, driven by the strong momentum in cloud business and quick commerce. Total adjusted EBITDA decreased 30% to RMB 27.3 billion, primarily attributable to the investment in technology, partly offset by the improved operating results in our cloud business as well as enhanced operating efficiencies across various businesses. Our GAAP net income was RMB 10.4 billion, a decrease of 75%, primarily due to the decrease in income from operations and decreasing net gains from disposal of investments and mark-to-market changes of our equity investments.

Operating cash flow this quarter increased by 11% to RMB 22.9 billion compared to RMB 20.7 billion in the same quarter last year. Free cash flow was an outflow of RMB 44.7 billion compared to an outflow of RMB 18.8 billion in the same quarter last year. The decrease was mainly attributed to the investment in cloud infrastructure. CapEx was RMB 67.7 billion this quarter. reflecting our continued investments in AI infrastructure to meet strong and growing customer demand. The significant year-over-year increase is due to several reasons, including fluctuations in procurement cycles, increasing in CPU compute capacity driven by anticipated growing customer adoption of AI agents and higher pricing of a broad range of chip components.

As of June 30, 2026, we held approximately USD 30.7 billion in net cash excluding debt with maturities beyond 5 years, our net cash position stands at approximately RMB 46.5 billion. This balance sheet strength gives us confidence to invest for robust growth. Our AIs cloud investment has a clear path to attractive ROIC, our service equipment with chips typically reach breakeven within 3 years. With a 5-year useful life, we expect them to get positive free cash flow, at least in the 2 years following breakeven. For the quarter ended June 30, 2026, we repurchased a series of an aggregate consideration of USD 162 billion. We remain committed to maximizing long-term shareholder returns through disciplined capital allocation across investments for AI plus cloud business growth, share buybacks and dividends. We will adjust our priorities as market conditions and the strategic needs evolve.

Now let's first look at our e-commerce businesses. The new Alibaba e-commerce group reflects our strategic focus on unlocking significant synergies across our domestic and cross-border e-commerce businesses. Starting from this quarter, we will present Alibaba e-commerce Group's revenue as the following: first, China e-commerce. Second, China quick comments third, international e-commerce and fourth global wholesale. Revenue for Alibaba e-commerce group was RMB 205.9 billion, an increase of 4%. Customer management revenue decreased by 7%. Excluding the contra revenue impact from the new business development program, customer management revenue would have grown by 1% year-over-year.

Revenue from China quick commerce business was RMB 53.3 billion, an increase of 45%, driven by Freshippo and Taobao instant commerce. Alibaba e-commerce Group's adjusted EBITDA remained relatively stable year-over-year at RMB 39.7 billion, underscoring our cost discipline against the backdrop of increased investments in user experiences and technology. Taobao instant commerce continued to improve its uneconomic quarter-over-quarter while maintaining market share. driven by higher average order value and enhanced fulfillment logistics efficiency. In addition, Ad Express achieved our pre-profit this quarter. We aim to maintain steady profit in our conventional e-commerce business of continuing to drive profitability improvement in our quick commerce business.

Now let's review the business updates and results of Ali Cloud -- AI Cloud and compute services, which comprises the Cloud Intelligence Group and T-Head. The year-over-year growth of total revenue and revenue from external customers both accelerated to 45%. Revenue from Alibaba Cloud also accelerated growing 45% year-over-year. We are confident the growth rate will further accelerate in the coming quarters. This quarter's AI-related product revenue was RMB 12.4 billion, implying an annual revenue run rate of RMB 49.5 billion. It delivered a 12th consecutive quarter of triple-digit growth and accounted for 35% of external cloud revenue. The adjusted EBITDA margin expanded to 12%, driven by improved economies of scale and a stronger pricing power of AI-related products amid tight market supply.

We expect EBITDA margin to further expand steadily in the coming quarters by improving resource utilization, optimizing model portfolio and innovating new scenarios we are accelerating the growth of AI plus cloud business and driving greater benefits of scale. AI Lab applications comprises AI model labs Qwen Consumer Business Group and Qwen work. Its adjusted EBITDA was a loss of RMB 13.9 billion, primarily due to our increased investment in AI capabilities and higher influence costs related to Qwen APP. The loss significantly narrowed quarter-over-quarter due to the reduction in marketing expenses for Qwen ABB. We expect the segment loss to narrow over the coming quarters driven by improving efficiency in both model training and marketing spend on Qwen ABB.

We have launched our frontier language coding, video, audio, image and music models or delivering top-tier performance. $250 million have had their first AI-driven shopping experience through Qwen APP's agentic features across an expanding range of e-commerce and other services since the launch of Qwen APP. All other segment revenue remained stable at RMB 28.8 billion. All other adjusted EBITDA was a loss of RMB 3.3 billion primarily due to our increased investment in technology. AI has progressed from incubation to commercialization at scale as we expand our market share, strengthen AI leadership and improving operating efficiency, we are gaining greater strategic and financial flexibility to make disciplined and sustained investments in both full stack AI capabilities and consumption opportunities driving secular growth and greater value for our shareholders. Thank you. That's the end of our prepared remarks. We can open up for Q&A.

Lydia Lu

Thank you, Toby. We will now begin the Q&A session. 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. Operator, please start the Q&A session. Thank you.

Operator

[Operator Instructions] Your first question comes from Alicia Yap with Citigroup.

Phần hỏi đáp

Alicis a Yap

Also congrats on your solid cloud performance. Could management please comment on the reasons and the drivers for the significant increase in the CapEx this quarter? And also, what's the expected CapEx trend for the coming quarters? And are these -- are there any updates to the existing 3-year CapEx budget that you have of this $380 billion that you mentioned before? And also, we would appreciate if management can also provide a breakdown of CapEx allocation across the different services like the training costs and all that? And then also, what is management affected return on the invested capital for these investments?

Unknown Executive

[Foreign Language] [Interpreted] Thank you very much for the question. It's an important question, and I'd like to take the opportunity perhaps to explain generally what our business model is for AI and our expectations around CapEx going forward. So indeed, last February, we announced a 3-year capital investment plan with total investment of RMB 380 billion as of the end of the June quarter this year, we had already spent RMB 190 billion with progress broadly in line with our expectations. While this quarter spending of RMB 67.1 billion is somewhat higher hardware deliveries follow different procurement cycles, there can be fluctuations in the cadence and pace of hardware deliveries.

So it's not evenly distributed across different quarters. So the increase primarily reflects volatility in those equipment delivery schedules. At the same time, we increased procurement of CPUs this quarter as we are witnessing a substantial surge in demand driven by the agent-centric era. Of course, rising prices for semiconductor components have also contributed to this trend. So I don't think we should take the spending for this quarter and multiply it by 4 to come up with an annualized figure for the year or to expect that there'll be a steady linear progression. The build-out has been progressing at a steady pace, but that is the overall situation.

Next, let me expand on our full stock AI business model. This is an asset-heavy business model. If you think about all of the different ways that AI is monetized and can be monetized, be it through software subscriptions, be it through API calls through models as a service through training, inference. In all of these different respects, you need compute centers to run and to monetize. So it's only possible to monetize when you have that compute capacity in place. So what that means is that we need to be investing upfront in order to be able to grow this business model and monetize across all of those different areas. So that's why beginning in 2025. we began a heavy investment cycle in hardware. And this is really a function of that asset-heavy business model, as I explained, in order to be able to capture that future growth. We first need to make these CapEx investments to build out the necessary compute capacity.

Next, let me explain why we see return on invested capital in AI-related as highly certain. There's consensus across the industry that the current shortage in AI compute will not be resolved until at least 2030. So industry-wide then, it makes sense that there should be high certainty in our investments in AI compute. Based on average gross margins today, roughly, we can break even on AI-related CapEx in 3 years. And of course, average gross margin continues to rise, and we expect to be able to shorten that payback period, say, to 2.5 years.

Following that 3-year payback period then these AI assets that we've invested in can achieve very positive and robust cash flow. So to give you some direct examples and A100 purchased in 2020 or A100 purchased in 20 -- sorry, V100 purchased in 2018. Even are still running at full capacity.

Additionally, we have 3 means that we can leverage to further enhance gross margin and return on invested capital. First is we can continue to develop state-of-the-art models and enhanced gross margin on AI products themselves and continue to expand a higher-margin model as a service mass businesses, and we can adopt our product mix across IAS and across software to achieve higher gross margin on the portfolio as a whole. And as a result of improving gross margin, you've already seen an overall increase of 4.4 percentage points in Alibaba Cloud's overall segment profitability, bringing it this quarter to 11.6%. So that represents initial validation of that thesis.

A very important piece of this is our ability to deploy our own proprietary chips. As you know, our own head proprietary chip spend, GPUs, CPUs and networking chips, which are the critical chipsets for AI. And in AI data centers, the most expensive components are, of course, chips and storage. So we have a very significant advantage in being able to deploy our own proprietary chips as we ramp up deployment of our own proprietary chips in our data centers as they account for an increasing proportion of total ships and replace commercially procured chips, we can expect to see substantially higher gross margin as well as profitability.

Third and also very importantly, we have means to monetize and get better efficiency of utilization of our own cash flow. These include, for example, co-building data centers with partners as well as pre charging and receiving prepayments for compute-based services. So these are important ways in which we can further enhance ROIC.

So through these 3 different methods, we can shorten the payback period for AI CapEx, for example, to 2.5 years or even 2 years. And we can apply a simple framework to understand this. at our current level of gross margin for AI products and under the assumption of a 3-year payback period on CapEx. Theoretically, keeping our growth rate below 33% would already enable positive cash flow. However, that is not our strategic choice at this time. given that AI remains in a very early stage, we're committed to aggressively investing in CapEx and proactively scaling up to drive our rapid business expansion. As our product gross margin improves and our proprietary chip substitution rate increases, our payback period will shorten to 2.5 years or even less. And so under those circumstances, while pursuing growth of over 40%, we'll also be able to maintain positive cash flow. So that is our long-term strategic direction.

Operator

Your next question comes from Charlene Liu with HBSC (sic) [ HSBC ].

Charlene Liu

I come from HSBC. First, when we get an update on the latest developments in quick comers and under the reclassification of multiple business lines, which are regrouped under the Alibaba e-commerce group. Can you talk about the future strategic focuses of these lines of businesses. Let me quickly translate the question myself. [Foreign Language]

Unknown Executive

Okay. Thank you very much for the question as well as for the translation. In the new fiscal year, indeed, we've realigned our e-commerce business segments. And moving forward, we'll be updating progress on 4 core areas: China e-commerce, quick commerce international e-commerce and global B2B global wholesale. Let me then briefly share the strategic priorities and key considerations for each of these 4 segments in the period ahead. So starting with China e-commerce.

While the domestic e-commerce landscape faces short-term macroeconomic challenges, our long-term strategy centers on strengthening core supply capabilities and at the same time, we aim to leverage AI to enhance the overall shopping experience and improve operational efficiency across the board. So first, regarding supply, since last year, Taobao and Tmall have focused on supporting original merchants, including branded sellers, while simultaneously unlocking the potential of high-quality white label suppliers from key industrial clusters.

Unknown Executive

[Foreign Language] [Interpreted] We will continue to strengthen our partnerships with leading brand merchants, helping them achieve stable and sustainable business growth Tmall remains the most critical operational hub for both major brands and many original merchants. At the same time, we are diving deeper into industrial clusters to source high-quality products directly from their origins. We are supporting more manufacturing factories and operating directly on our platform and leveraging our platform AI capabilities to enable white-label merchants to adopt a simpler and more efficient managed operation model. And the share of transactions being generated through that industrial cluster managed model continues to rise steadily.

In the past quarter, during the recent 618 shopping festival despite certain macroeconomic challenges, the outcomes were aligned with our expectations and notably, core merchants achieved solid growth.

At the same time, we see significant opportunities for AI across both the supply and demand sides of e-commerce. On the consumer side, we will continue to launch new experiences and scenarios powered by AI, such as multimodal search and virtual try-ons, our goal is twofold: first, to use AI technology to enhance the experience and efficiency of existing shopping scenarios, and we've already observed that AI has driven significant efficiency gains in our product recommendations and secondly, to drive new kinds of AI-driven interaction. On the merchant side, we observed that merchants are already widely adopting AI in their operations we're exploring ways to leverage AI across various operational links to boost merchant capabilities, particularly in data analytics, advertising and marketing and customer service where merchants can derive clear benefits. And going forward, we'll also collaborate with Qwen Office to launch AI agents that are specifically tailored for e-commerce scenarios.

Next, on quick commerce. After more than a year of investment and development, Taobao Instant Commerce has undergone substantial changes in scale and in market share with significant improvements across user mind share, supply diversity, logistics experience and order volume. Last quarter, while maintaining growth in both users and orders unit economics, UE substantially improved and losses significantly reduced. On that basis, we will accelerate the integration of businesses such as Freshippo and Tmall supermarket to develop the nonfood categories growth within the Quick Commerce business, and we'll place a particular focus on expanding our front warehouses. Over the past year, Freshippo has accelerated the development of front warehouses leading to a year-over-year increase in GMV.

Meanwhile, Quick Commerce will continue to expand its category coverage and innovate in key areas to enhance the consumer experience. We expect the transaction volume of quick commerce for nonfood categories to surpass that of food categories within the next fiscal year, driving growth in many different physical goods categories across the overall e-commerce business. The Quick commerce business is expected to achieve overall profitability in FY '29. In the long term, we believe it has the potential to contribute 30% of the platform's total GMV, becoming the second growth curve for our e-commerce business.

Third is international e-commerce. In the short term, our international e-commerce business has indeed been affected by tariff policies and the geopolitical environment pressuring growth. That said, despite the complex market environment, our cross-border business has delivered significant improvement in profitability while maintaining growth in transaction volume. In terms of both transaction scale and profitability, we believe the cross-border business holds long-term growth potential. In addition, our local e-commerce platforms in international markets such as Turkey and the Middle East are growing rapidly and operating efficiency in markets such as Southeast Asia continues to improve.

Our B2B businesses, including the 1688 and alibaba.com platforms have grown consistently over the past 2 decades and we see that AI technology will bring profound changes to our B2B platforms and may even fundamentally reshape existing business models. In particular, the genetic model will play an increasingly important role in B2B transactions. We've launched Accio Work, which is an AI agent for cross-border merchants and it had already attracted over 50,000 paying merchants shortly after its launch. AI is comprehensively transforming the way that B2B merchants do business especially cross-border merchants. We believe that building on our 2 years of know-how in the 2 decades of know-how in this field, we have the opportunity to create entirely new business models and commercial opportunities in B2B and in cross-border trade in the AI era.

Overall, over the past few years, we have completed a new strategic positioning for our e-commerce businesses across several key areas. And going forward, we aim to continue leveraging our strengths from supply chain synergies to AI technology to unlock greater growth potential for the e-commerce segment in the AI era, while building a more diversified revenue and profit structure to drive steadier development of the overall segment.

Operator

Your next question comes from Yang Bai with CICC.

Unknown Analyst

My question is about the cloud and AI business. We've seen that Alibaba Cloud's revenue growth has been accelerating quarter-by-quarter reaching 45% this quarter. We know the company has previously set a long-term goal of exceeding USD 100 billion in external cloud revenue over the next 5 years. And you've also now indicated that growth will remain on an accelerated trajectory in the quarters ahead. So I'd like to ask 2 questions. First, looking ahead to the coming quarters, what do you anticipate being the pace of growth in the cloud business. what are the core drivers underpinning the continued acceleration of cloud computing growth?

And then secondly, as you mentioned, the industry is now in a phase of relatively tight capacity in terms of supply of compute. And you just mentioned that, that supply demand dynamic may shift around 2030. So I'd like to ask from an even longer-term perspective, what are the fundamental growth drivers for the cloud business? And do they differ from those in the short term?

Unknown Executive

[Foreign Language] [Interpreted] Thank you for the question. And I think I can expand on this in 3 different areas. I can start by looking at our current business and the relevant data. Secondly, I can discuss the drivers for growth. And then thirdly, I can share with you our long-term perspective. based on that analysis. So let me begin with the first part, covering our current business and the key metrics. So as you've seen, external revenue for the AI and Cloud segment has been accelerating now for 9 consecutive quarters. And in this last quarter, growth has already accelerated to 5%. We're seeing very strong customer demand and our offerings boast a distinct competitive advantage compared to those of other cloud providers.

As a result, we expect revenue growth to continue accelerating over the coming quarters. We've observed that AI-related products generated RMB 12.4 billion in revenue this quarter. And so if we convert that into an annualized U.S. dollar figure, that works out to USD 7.3 billion in annual revenue. Looking ahead to the next quarter, our own forecast is that, that same annualized revenue for AI quarters next quarter will approach USD 10 billion. So our growth rate remains exceptionally strong. At the same time, we also expect our EBITDA margin to improve quarter by quarter sequentially over the next few quarters.

Additionally, something very important in respect to the cloud business is growth in demand for mass we've seen very significant growth in demand for mass this quarter, coupled with ongoing improvement in inference efficiencies. So the ARR of our mass business has now surpassed RMB 16 billion. And actually, let me clarify. That's the latest data as of August. It's already surpassed RMB 16 billion.

Next, let me expand on the growth drivers within our business model. So it's important to understand that Alibaba's investment model for AI is fundamentally different from that pure-play AI companies. We are pursuing an intensive strategy across the full stock including chips, including cloud infrastructure and including models. And we maintain a leading position in the industry across all 3 of those most critical domains. Moreover, we believe that the development of AI and technology across the industry is still in its early stages. Looking forward, different stages of technological development. The core commercial value within the AI industry may shift across different layers, including chips, cloud computing models and applications.

Our full stack investments ensure that we can deliver optimal service capabilities and the best value for money positioning us favorably in the industry going forward and ensuring that within each stage of technological development, it's possible for us to maintain competitiveness and sustained growth momentum.

Next, let me look ahead to what we think is going to be the most important growth driver over the next 1 to 2 years in the short term. So we've seen exponential demand for commercial insurance services as of the end of 2025. This exponential growth in demand for inference has marked a fundamental shift in the model whereby compute has now become the core asset driving AI revenue. And today, all AI-related revenue models are centered on AI compute. And at the same time, there's a consensus across the industry, as I mentioned, that compute will remain in a shortage of supply for some time to come.

At the same time, the higher gross margins of mass inference services have also made a major difference if compute was once a cost center, traditionally, compute has now been transformed into a core productive asset whose value generation is positively correlated with revenue. So high-priced computing power remains in short supply across the industry precisely at a time where you have widespread adoption of GPUs across diverse use cases. So pricing models are tending to converge on the most high margin, the most margin generative monetization approaches. So this is driving the pricing models for nearly all GPU-related products.

Moreover, Alibaba, both comprehensive multimodal model capabilities. Our models are state-of-the-art level within the industry, giving us a distinct advantage in realizing the value of that compute power and providing a robust anchor for our pricing strategy when it comes time to price for new customers or to sign -- resign contracts with existing customers as they renew, we can adopt more healthy pricing models. And so we expect to see this as a very positive short-term driver for improving margin in the coming year plus.

Next, let me talk about the scale effect and networking effects, which are very important long-term growth drivers in AI cloud. For the past couple of years, a lot of people have asked what is the super app for AI. And the answer to that is that the real super application is compute, cloud-based AI compute because all of these different workloads need to run on a full stack of AI cloud compute, including training, inferencing AI software and agents requiring GPUs, CPUs, storage, databases, virtualization as well as harness tools among others. So AI cloud is like a super city in which workload is the residents and continually iterating full stock AI cloud services or the urban infrastructure, which in turn attracts more new residents and enhances the stickiness of the existing residents. So this is where you see an extremely powerful network effect and scale effect.

Given that we operate the largest number of data centers across any Asian cloud provider, we benefit from the strongest economies of scale. At the same time, the large-scale deployment of our proprietary T-Head AI chips allows us to avoid the high price premiums associated with procuring expensive commercial GPUs and thus avoiding erosion of our gross margins. And with our state-of-the-art performance in our proprietary models, we possess strong pricing power for our compute resources. So looking ahead from the perspective of industry. Development trends and our own product strength, the long-term revenue growth trend and margin expansion trend are exceptionally strong. And as a result, we're highly confident in our ability to achieve our goal of RMB 100 billion in external cloud revenue by 2030. And we have good visibility into achieving gross margin of 20%.

Operator

Your next question comes from Yuan Liao with CITICS.

Yuan Liao

[Foreign Language] [Interpreted] Congratulations on the strong quarterly results and especially the progress made in the AI sector. I have a follow-up question on the mass business. As Eddie mentioned earlier, ARR as of August has exceeded RMB 16 billion in last quarter. I believe you stated that the target for year-end is to surpass RMB 30 billion in mass ARR. So I'm wondering, given the progress to date, do you anticipate making any adjustments to that year-end goal? And then additionally, within the MaaS business, what are the respective shares of our own proprietary models versus third-party models. And as model-related competition intensifies and more open source models emerge how all these factors possibly affect gross margin and profitability in the MaaS business.

Unknown Executive

[Foreign Language] [Interpreted] Thank you for the question. Yes, indeed, growth in Bailian's MaaS business is very rapid. And in -- as of August, we reached RMB 16 billion or surpassed RMB 16 billion in ARR. So given the current growth momentum as well as the pipeline of new models slated for launch, we remain confident that we will achieve our year-end target of RMB 30 billion ARR by the end of the year.

So on our MaaS platform, our own proprietary model still account for the majority of the revenue. But having said that, revenue from third-party models is also not small. And having said that, perhaps let me talk a little bit about how we see different model capabilities. A lot of customers tend to need to use or want to use multiple different models in their own AI applications because those different models they can draw and have different characteristics or different capabilities. So having more open source models on platforms like ours like Bailian to provide inferencing is a good thing for us and for Bailian. When it comes to gross margin, the level of gross margin that we can achieve on a platform like Bailian from hosting our own proprietary models versus third-party models is actually very similar. It's highly comparable. We're really developing those proprietary models on the one hand in order to keep creating higher levels of model intelligence and also as part of our ultimate drive to achieve AI.

But simply from the perspective of the mouse business, the level of gross margin from those 2 kinds of models is actually very comparable. But overall, having a prosperous and flourishing open ecosystem with many of these open source models on it is highly favorable for a cloud provider like Alibaba Cloud.

Operator

Your final question comes from Alex Yao with JPMorgan.

Alex Yao

[Foreign Language] [Interpreted] I'd like to come back to Eddie's earlier remarks, he spoke at length about how Alibaba is developing a full stock AI ecosystem. My question really is in which layer of that full SAC ecosystem, do you think value will accrete and monetization will be concentrated. We saw just after it has been released for 3 months that you open sourced the weight of your flagship model, Q1 3.8 MAX. At the same time, your proprietary chips are also proving successful, now serving over 600 external customers. I'm wondering if this means that the future value will accrete mainly in the compute layer or perhaps in the orchestration layer and not necessarily in the model layer or do you think that the value will accrete to different layers in different stages of development of the industry.

And in the long term, if you think that value and monetization will largely be concentrated in the hardware and compute layers then how should we think about competition going forward, given that it will be a government-led process for allocating a lot of that hardware and compute capacity.

Unknown Executive

[Foreign Language] [Interpreted] Thanks. That's a very professional question, and really it's a matter of long-term judgment. So I think it's inherently associated with a high level of uncertainty. But what I can say is that we are investing in the full stack. And what that means is that whichever layer represents the greatest value and no matter how that may shift across layers in different periods of time. All of those layers are part of our ecosystem. I guess I can share with you my own short-term view namely in the short-term perspective, I think that most of the value will be in chips and in AI cloud infrastructure.

It's a pattern that we can see not just in China but globally across a lot of different companies when a technology is in its early stages and especially when there's a shortage of supply. Lots of the value tends to be concentrated in the infrastructure and in the core hardware. In this case, chips and storage. So in Alibaba's case, we've integrated our compute power, our cloud infrastructure and our AI inference into one core business segment.

Let me turn next to where the ultimate commercial value will be realized from these models. It's a question around which there's a lot of debate within the industry and indeed, there are different views even inside our own company. So here, I'm just sharing my own personal opinion, but in my personal view, I think that the current monetization model for large language models through APIs is just a short-term approach, a short-term transitional approach and is certainly not the ultimate business model.

Our company has invested a tremendous amount of compute across our entire platform, but the objective is not simply to be able to generate that kind of short-term API revenue. I think when we get to the stage where we've accomplished AEI or we're close to achieving AGI at that point, the ultimate business model will be delivering actual products, delivering actual results that clients are looking for. It will be conducting the actual R&D that delivers products and that delivers operations. So the reason that all these different AI model companies are investing so heavily and engaging in an arms race today is not simply to be able to compete to provide that API-based service. It's because they have to eyes on that ultimate end game where I think that the monetization level will be significantly higher, be much higher than what you see today selling the service through API calls.

In terms of hardware, I'd like to add a few thoughts regarding our head proprietary chips. I know it's a topic about which we haven't communicated a lot with investors in the past, but the last generation of T-Head chips, we've already manufactured over 500,000 of them and shipped. And then the latest generation in August has already been deployed on AI Alibaba's AI cloud as super nodes. And I think we're one of the only companies that's able to deploy such proprietary chips, domestic chips at scale. .

One thing that's really unique about our tea head chips, domestically manufactured chips, is that they are designed with GPU architecture as their core technical foundation, and they can very well support both training and inference workloads. So there are now already several hundreds of companies that are leveraging these chips via Alibaba Cloud for both inference as well as for model training and these span companies across embodied AI, autonomous driving as well as large model. companies. So in terms of our generation 2 of chips, we are going to start developing them in the second half of this year. And we expect them to boost exceptionally high compute power as well as extremely robust interconnection bandwidth, making them fully capable of serving as a direct replacement for existing chips.

So I think we're in a really, really unique position in the chip sector, especially when it comes to large scale model training. So I don't think that there's any government-led compute supply allocation scheme that could produce chips with such truly strong competitiveness. So I think that the T-Head's future is highly certain as a very key and core component of Alibaba Cloud, and we remain highly confident in our core competitive strength in this area. I've interacted with a lot of different engineers across China. And I can tell you that these chips have a very broad audience with engineers across a wide range of different engineering domains.

So to sum up, I think that our tea head ships are definitely the best among domestic Chinese ships for supporting both training and inference across a wide range of different industries. So we really are #1 in the industry. And then I think in terms of future production capacity and deployment, we can confidently claim to be at least 1 of the top 2. But in terms of our ability to actually reach customers with AI chips, Alibaba Cloud is the largest player by market share in China's cloud and AI market. So I think we have a very strong edge when it comes to channel distribution. So from this perspective, I am highly confident in the long-term commercial value of T-Head chips.

Lydia Lu

Thank you very much. We appreciate your support, and we look forward to updating you on our progress next quarter. Thank you.

Operator

Thank you. That does conclude our conference for today. Thank you for participating. You may now disconnect.