阿里巴巴 (BABA) 2026 Q3 法說會逐字稿

Good day, ladies and gentlemen. Thank you for standing by, and welcome to Alibaba Group's December quarter 2025 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.

女士們、先生們，大家好。感謝您的耐心等待，歡迎參加阿里巴巴集團2025年第四季業績電話會議。（操作員指示）現在我將把電話交給阿里巴巴集團投資者關係負責人呂麗雅女士。請繼續。

Thank you. Good day, everyone, and welcome to Alibaba Group's December quarter 2025 earnings conference call. Joining us 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. I would like to remind you that this call is also being webcast on our corporate website. A replay of the call will be available on our website later today.

謝謝。大家好，歡迎參加阿里巴巴集團2025年第四季財報電話會議。今天與我們一同出席的有阿里巴巴集團董事長蔡崇信、執行長吳宇森、財務長徐東輝以及阿里巴巴電子商務集團執行長蔣帆。我想提醒各位，本次電話會議也會在我們公司網站上進行網路直播。本次電話會議的錄音回放將於今日稍後在我們的網站上提供。

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.

現在我將快速介紹安全港條款。今天的討論可能包含基於當前預期和假設的前瞻性陳述，這些陳述存在風險和不確定性。實際結果可能與實際情況有重大差異。請參閱我們今天發布的新聞稿和投資者簡報中的「安全港聲明」。

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 our year-over-year comparisons unless we state otherwise.

請注意，某些財務指標是按非公認會計準則 (non-GAAP) 編製的。我們的 GAAP 結果以及 GAAP 與非 GAAP 指標的調整表已包含在今天的獲利新聞稿和投資者簡報中。除非另有說明，否則我們的評論將基於同比數據。

And now I will turn the call over to Eddie.

現在我將把電話交給艾迪。

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 + 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 economics. With the dawn of the AI agent era, the addressable market for AI infrastructure providers like Alibaba is set to grow exponentially.

謝謝，歡迎參加本季財報電話會議。過去一個季度，我們在人工智慧+雲端運算和消費這兩大戰略重點領域保持了強勁的投資動能。雲端智慧集團的營收成長加速至 36%，而我們的快速商務業務規模隨著經濟效益的持續改善而不斷擴大。隨著人工智慧代理時代的到來，阿里巴巴等人工智慧基礎設施供應商的潛在市場必將呈指數級增長。

AI models and our 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.

人工智慧模型和我們的能力正在迅速融入各行各業的主流工作環境中，代幣消費在各個領域都爆炸性成長。企業 IT 服務的雲端和軟體預算歷來只佔企業收入的 5% 左右。隨著模型驅動型智能體開始處理各行各業的主流工作任務，我們的潛在市場規模將擴大數倍。

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.

從人工智慧基礎設施到應用層，阿里巴巴建構了一套完整的全端人工智慧能力體系，以支援人工智慧需求的指數級成長。面對如此巨大的產業變革和策略機遇，阿里巴巴集團本身也正進入一個面向未來的創業重塑和關鍵投資的新階段。

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 in both enterprise and consumer applications. Together, these give us end-to-end coverage across the full stack from AI infrastructure to applications.

接下來，我將分享阿里巴巴的人工智慧策略路線圖。我們擁有完整的全端人工智慧能力，晶片和雲端運算構成了人工智慧基礎設施層，而人工智慧應用層則以阿里巴巴代幣中心為核心，包含基礎模型，涵蓋企業和消費者應用的各個面向。這些加起來，就為我們提供了從人工智慧基礎設施到應用程式的全端到端覆蓋。

Given the enormous and sustained growth momentum of the AI market, combined with Alibaba's full stack positioning across the AI value chain, the business goal of Alibaba's AI strategy is very clear. Over the next five years, our goal is to surpass USD100 billion in combined cloud and AI external revenue, including mass.

鑑於人工智慧市場巨大的持續成長勢頭，加上阿里巴巴在人工智慧價值鏈上的全端定位，阿里巴巴人工智慧策略的商業目標非常明確。未來五年，我們的目標是雲端和人工智慧外部收入（包括大眾市場）總計超過 1,000 億美元。

Regarding our infrastructure, driven by sustained strong AI demand, Cloud Intelligence Group's revenue from external customers accelerated to 35% this quarter with AI-related product revenue delivering triple-digit year-over-year growth for the tenth consecutive quarter.

就我們的基礎設施而言，在持續強勁的 AI 需求推動下，雲端智慧集團來自外部客戶的營收本季加速成長至 35%，AI 相關產品收入連續第十個季度實現三位數同比增長。

Cloud Intelligence Group's market share has grown for three consecutive quarters, rising to 36% with our lead continuing to widen. Alibaba Cloud's cumulative external revenue through February for fiscal year 2026 officially surpassed RMB100 billion. 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.

雲端智慧集團的市佔率已連續三個季度成長，達到 36%，我們的領先優勢仍在擴大。截至2026財年2月，阿里雲累計外部收入正式突破1,000億元。過去三個月，模型工作室平台上的代幣消耗量增加了 6 倍。我們預計大規模數據將成為雲端智慧集團最大的收入來源。

T-Head's 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 the T-Head ships serve external customers, and we've completed scaled adoption for external customer AI workloads.

T-Head 的自主研發 GPU 晶片已實現規模化量產。截至 2026 年 2 月，T-Head 累計出貨了 47 萬枚 AI 晶片。在透過阿里雲進行的實際業務部署中，超過 60% 的 T-Head 船服務於外部客戶，我們已經完成了外部客戶 AI 工作負載的規模化採用。

T-Head now supports the AI workloads of over 400 enterprise customers across industries, including Internet financial services and autonomous driving. We're confident that T-Head's compute supply capacity will continue to expand, contributing high-quality compute to our cloud infrastructure and mass platform, strengthening the overall competitiveness of our cloud services.

T-Head 目前為 400 多家企業客戶提供 AI 工作負載支持，這些客戶遍布各個行業，包括網路金融服務和自動駕駛。我們相信，T-Head 的運算能力將繼續擴大，為我們的雲端基礎設施和大眾平台提供高品質的運算能力，從而增強我們雲端服務的整體競爭力。

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 Tongyi Laboratory, the mass business line, the QN 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.

針對我們的應用層，以創建、交付和應用代幣為核心使命，我們成立了新的阿里巴巴代幣中心業務集團（ATH）。它由同益實驗室、大眾業務線、QN業務單位、悟空業務單位和AI創新業務單位組成。它是阿里巴巴執行人工智慧策略的組織基礎，也是我們人工智慧業務高效協調的中心。

During Chinese New Year, we launched our latest generation large model, Qwen3.5-Plus, which delivered outstanding performance across comprehensive benchmarks in reasoning, coding, and agentic capabilities. Qwen3.5-Plus demonstrated significant improvement in inference efficiency through foundational architectural innovation. Building on Qwen3.5, we will soon release the next generation of models optimized for coding and agentic use cases.

春節期間，我們推出了最新一代大型模型 Qwen3.5-Plus，該模型在推理、編碼和智能體能力的綜合基準測試中表現出色。Qwen3.5-Plus 透過基礎架構創新，在推理效率方面實現了顯著提升。在 Qwen3.5 的基礎上，我們將很快發布針對編碼和代理用例最佳化的下一代模型。

On the consumer application side, powered by the strength of our models, Qwen's consumer-facing monthly active users have surpassed 300 million. During Chinese New Year, we deepened integration across Alibaba's ecosystem connecting Qwen app with Taobao Instant Commerce, Alipay, Fliggy, and Amap giving it unique capabilities relevant to the everyday life and becoming China's first all-in-one personal AI system for life work and learning.

在消費者應用方面，憑藉我們強大的模型，Qwen面向消費者的月活躍用戶已超過3億。春節期間，我們深化了阿里巴巴生態系統的整合，將Qwen app與淘寶即時商城、支付寶、飛豬和地圖連接起來，賦予其與日常生活相關的獨特功能，使其成為中國首個集生活、工作和學習於一體的個人AI系統。

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 B2B capabilities of businesses across Alibaba's full ecosystem will be progressively integrated to sort Wukong becoming the best AI work system.

我們最近也推出了企業級人工智慧代理平台 Wukong。Wukong 是全球首個原生 AI 企業級代理平台，可在保持與各組織資料權限和管理流程相容的同時，實現企業工作流程的 AI 驅動升級。它為阿里巴巴在企業工作環境中的人工智慧功能提供了統一的介面。阿里巴巴整個生態系中各企業的B2B能力將逐步整合，以使悟空成為最佳人工智慧工作系統。

On Alibaba's other strategic priority, the Consumption segment, we continue to advance our strategic initiatives. This quarter, our Quick Commerce bills 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.

在阿里巴巴的另一個策略重點——消費領域，我們將繼續推動我們的策略舉措。本季度，隨著市場佔有率的持續成長、客戶留存率的提高以及單位經濟效益和平均訂單價值的逐週改善，我們的快速商務帳單規模進一步擴大。同時，快商和電子商務展現出明顯的協同效應，推動淘寶應用程式的每月活躍用戶實現了兩位數的同比增長。

That concludes my remarks. I'll now hand over to Toby to share the financial update.

我的發言到此結束。現在我將把發言權交給托比，讓他來報告最新的財務狀況。

Thank you, Eddie. Our strategic priorities are clear: we remain focused on AI + Cloud and consumption businesses. We are seeing great momentum with gains in technology, customer adoption, market share, and user engagement. On AI + Cloud, we have the full stack AI capabilities with all three core elements: model, cloud infrastructure, and chips. And leadership in each with Qwen, Alibaba Cloud, and T-Head.

謝謝你，艾迪。我們的策略重點很明確：我們將繼續專注於人工智慧+雲端運算和消費業務。我們在技術、客戶採納率、市場份額和用戶參與度方面都取得了巨大進步，發展勢頭強勁。在 AI + 雲端方面，我們擁有全端 AI 能力，涵蓋所有三個核心要素：模型、雲端基礎設施和晶片。並在 Qwen、阿里雲和 T-Head 等公司中擔任領導角色。

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

我們也在中國經營最全面的消費者生態系統，可以透過人工智慧來獲利。Qwen App 的推出是一個重要的里程碑，它可以將我們的消費者應用程式整合在一起。在消費方面，快速商務業務在 12 月季度繼續獲得 GMV 市場份額，同時單位經濟效益和 AOV 也繼續改善。

Now let's look at the financial results. On a consolidated basis, total revenue was RMB284.8 billion. Excluding revenue from Sun Art and Intime, revenue on a like-for-like basis have grown by 9%. Total adjusted EBITDA decreased by 57% primarily due to our strategic investments in technology-related innovation initiatives and the consumption front, including quick commerce business, partly offset by the improved operating results in cloud business and enhanced operating efficiencies across various businesses.

現在我們來看看財務業績。合併後的總收入為人民幣2848億元。剔除大潤發和銀泰的收入，以可比口徑計算，收入增加了 9%。經調整的 EBITDA 總額下降了 57%，主要原因是我們在技術相關創新計畫和消費領域（包括快速商務業務）的策略性投資，部分被雲端業務經營績效的改善和各項業務營運效率的提高所抵銷。

Our GAAP net income was RMB15.6 billion, a decrease of 66%. Operating cash flow was an inflow of RMB36 billion. Free cash flow was RMB11.3 billion, a decrease of RMB27.7 billion from the same quarter last year. We are reinvesting our cash flow to be a leader in AI and quick commerce.

我們的GAAP淨利為人民幣156億元，下降了66%。經營活動現金流為人民幣360億元流入。自由現金流為人民幣113億元，較去年同期減少人民幣277億元。我們將現金流再投資於人工智慧和快速商務領域，力求成為該領域的領導者。

As of December 31, 2025, we held USD42.5 billion in net cash. Excluding that with maturities beyond five years, our net position stands beyond the USD60 billion. This balance sheet strength gives us confidence to reinvest for long-term growth.

截至 2025 年 12 月 31 日，我們持有 425 億美元的淨現金。除去期限超過五年的到期債務，我們的淨部位超過 600 億美元。穩健的資產負債表使我們有信心進行再投資，以實現長期成長。

Now let's look at our consumption businesses. Revenue from China e-commerce group was RMB159.3 billion, an increase of 6%. Customer management revenue increased by 1%. The slowdown in revenue growth was primarily due to weaker transaction activities and phase out of the impact of software service fee implementation.

現在我們來看看我們的消費業務。中國電子商務集團營收為人民幣1,593億元，成長6%。客戶管理收入成長了1%。營收成長放緩主要是因為交易活動疲軟以及軟體服務費實施的影響逐漸消失。

The Taobao App achieved a double-digit increase in MAC during the quarter, driven by the growing mind share and increasing scale of our quick commerce business. Revenue from our quick commerce business increased 56% to RMB20.8 billion. During the quarter, we executed our plan to further grow the scale of our Quick Commerce business. improved user experience, improved UE, and increased AOV month-over-month during the quarter.

受快速商務業務市場份額不斷擴大和規模不斷增長的推動，淘寶App在本季度實現了兩位數的MAC成長。我們的快速商務業務收入成長了56%，達到人民幣208億元。本季度，我們執行了進一步擴大快速商務業務規模的計劃，提高了用戶體驗，提升了用戶體驗效率，並實現了季度環比平均訂單價值的增長。

Alibaba China E-commerce Group adjusted EBITDA was RMB34.6 billion, a decrease of 43%, primarily due to the investment in quick commerce, user experiences, and technology. Going forward, this adjusted EBITDA will continue to fluctuate quarter-over-quarter due to intense competition and significant investment in user experience.

阿里巴巴中國電子商務集團調整後 EBITDA 為人民幣 346 億元，下降 43%，主要原因是投資快速商務、使用者體驗和技術。展望未來，由於激烈的競爭和對用戶體驗的大量投資，調整後的 EBITDA 將繼續出現季度環比波動。

Revenue from AIDC grew 4% this quarter. AIDC's adjusted EBITDA loss narrowed significantly year-over-year, driven by a combination of logistics optimization and investment efficiency enhancement. The UE of the Aliexpress Choice business also improved on a sequential basis.

本季AIDC營收成長4%。受物流優化和投資效率提升的雙重推動，AIDC調整後的EBITDA虧損年減。Aliexpress Choice 業務的使用者體驗也較上季有所改善。

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.

接下來，我們來看看雲端智慧集團的業務更新和業績。我們的雲端業務連續第二個季度實現了加速成長。來自外部客戶的收入成長了 35%，高於上一季的 29%。人工智慧相關產品持續引領這一發展勢頭。我們在人工智慧收入方面連續第十個季度實現了三位數成長。

Its sheer of external cloud revenue continue to increase. This is a clear reflection of the scale and acceleration in our AI business. The adjusted EBITA 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.

其外部雲端收入持續成長。這清晰地反映了我們人工智慧業務的規模和發展速度。調整後的 EBITA 利潤率保持相對穩定，為 9%。我們將繼續投資於客戶成長和技術創新，以提高人工智慧雲端基礎設施的普及率，並鞏固我們的市場領導地位。

All Others segment revenue decreased by 25% to RMB67.3 billion, mainly due to the disposal of Sun Art and Intime businesses as well as a decrease in revenue from China, partly offset by the increase in revenue from Freshippo and Alibaba Health. All Others adjusted EBITA was a loss of RMB9.8 billion, primarily due to the increased investment in technology businesses, including Qwen models and consumer-facing Qwen, partly offset by the improved results of (inaudible) DME and other businesses.

其他業務板塊收入下降 25% 至 673 億元人民幣，主要原因是出售了高鑫零售和銀泰銀行的業務，以及來自中國的收入減少，部分被盒馬鮮生和阿里巴巴健康的收入增長所抵消。其他業務調整後息稅前利潤虧損人民幣98億元，主要原因是加大了對科技業務的投資，包括Qwen模型和麵向消費者的Qwen，部分被（聽不清楚）DME和其他業務的業績改善所抵消。

Qwen model has become one of the most widely adopted open-source model families globally, surpassing 1 billion cumulative downloads on hacking phase by the end of this January, and the consumer-facing Qwen has surpassed 300 million MAU across platforms, which reinforces user engagement and expands long-term monetization potential. We have been increasing investments on these technology fronts, including the Spring Festival campaign.

Qwen 模型已成為全球最廣泛採用的開源模型系列之一，截至今年 1 月底，其黑客階段的累計下載量已超過 10 億次，面向消費者的 Qwen 在各平台上的月活躍用戶已超過 3 億，這增強了用戶參與度並擴大了長期盈利潛力。我們一直在增加對這些科技領域的投資，包括春節促銷活動。

Building on the strong momentum and results achieved, as Eddie mentioned earlier, we will continue to invest substantially in Qwen models and Qwen App. Our unallocated adjusted EBITDA was a loss of RMB2.7 billion compared to a loss of RMB0.2 billion in the same quarter last year, which reflected costs associated with talent retention incentive from the one-off replacement awards plan of Ele.me.

正如 Eddie 之前提到的，我們將基於強勁的發展勢頭和取得的成果，繼續對 Qwen 模式和 Qwen App 進行大量投資。我們未分配的調整後 EBITDA 虧損 27 億元人民幣，而去年同期虧損 2 億元人民幣，這反映了餓了麼一次性替換獎勵計劃中與人才保留激勵相關的成本。

Thank you, and we will now open for Q&A.

謝謝，現在開始問答。

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's statement in the original language will prevail.

大家好。歡迎您用中文或英文提問。將由第三方翻譯人員提供交替傳譯服務。如有任何出入，以我方管理階層原文聲明為準。

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.

如果您無法收聽中文翻譯，本次通話的雙語文字稿將在會議結束後一週內發佈在我們的網站上。

(spoken in foreign language)

（用外語說）

Operator, please go ahead with the first question. Thank you.

操作員，請先回答第一個問題。謝謝。

(Operator Instructions) Robin Zhu, Bernstein.

（操作說明）Robin Zhu，Bernstein。

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 strategically, what changes or goals are you hoping to achieve with this new structure that improves on the previous arrangement going forward?

能否從組織角度舉例說明 Token Hub 將如何改變未來不同雲端與人工智慧企業之間的合作方式？從策略角度來看，您希望透過這種新的架構實現哪些改變或目標，以改善先前的安排？

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

如果管理層能夠分享雲端和人工智慧領域的優先事項層級，那麼是市場份額和收入成長（例如您剛剛宣布的目標），還是擁有最佳的第一方模型能力，還是透過代理人工智慧吸引消費者，或其他任何方面？

(interpreted) 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.

（翻譯）太好了。非常感謝您的提問。我認為，ATH 商業集團的成立目標和目的與我們現在所處的時代（截至 2025 年底和 2026 年前幾個月）密切相關。

In terms of the development of AI, 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.

就人工智慧的發展而言，我們現在正處於人工智慧發展的智慧體驅動時代。這與人工智慧發展的早期階段有所不同。在智能體人工智慧時代，我們需要實現模型與應用的緊密整合。在早期人工智慧時代，許多模型訓練數據都是靜態數據，但在智能體時代，我們需要加強模型與應用程式之間的集成，實現緊密整合，而且現在很多數據都來自客戶方。

So if you look at the different layers involved in AI deployment from application model, the AI infrastructure, through 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.

因此，如果你從應用模型、人工智慧基礎設施到晶片等不同層面來審視人工智慧部署，我認為智能體人工智慧時代最不同、最重要的特點是需要實現應用和模型之間的緊密整合。這是當務之急。

Next, let me address the interconnection and synergies among the different businesses in relation to ATH. If you look at the trends of where this industry is going, 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.

接下來，我想談談ATH旗下不同業務之間的相互連結與綜效。如果你觀察這個產業的發展趨勢，我們認為我們已經非常清楚地看到了這些趨勢。人工智慧代理將與應用層緊密整合。而且將會有大量用途各異的應用。

In the two consumer or 2C space, we're strongly developing the Qwen 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 a very robust model as a service, mass layer.

在 2C 消費者領域，我們正在大力開發 Qwen 應用，將其打造為個人助理。在 2B 領域，我們將悟空定位為 2B 助手。在人工智慧應用層，將有許多不同行業和垂直領域的專業應用，以服務不同的行業用例。而這一切都需要非常強大的服務型大眾層模型的支援。

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 TAP.

因此，大眾支援當然包括我們自己的內部應用程序，以及利用人工智慧的眾多外部和行業特定用例。因此，在這種背景下，我們看到了我們可以提供的巨大價值和巨大的潛在市場（TAP）。

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.

因此，展望未來，我們認為 AI 應用層將成為代幣分發的主要管道。您在大眾層面提供的模型功能越強大，所有這些不同的產品對客戶就越有吸引力和說服力。這就是我們在這個新業務部門中所製定的業務邏輯。

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.

因此，無論從模型層或應用層來看，我們的首要任務絕對是開發最聰明的模型。我真的需要強調，只有擁有最強大的模型，才能真正推動人工智慧應用在各個不同行業的部署。只有擁有最強大的模型，才能吸引來自不同行業的用戶採用我們的大規模產品。

However, in order to build the most robust models, you need to have very close collaboration with various industries and with our own 2C and 2B applications to connect with our mass two applications across all kinds of different industries and use cases. So we need to get more users to leverage and make use of 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.

然而，為了建立最強大的模型，您需要與各個行業以及我們自己的 2C 和 2B 應用程式進行非常密切的合作，以便與我們跨越各種不同行業和用例的大規模 2C 應用程式連接起來。因此，我們需要讓更多使用者利用我們的模型，以便逐步發揮資料飛輪效應。只有這樣，我們才能不斷提升模型的效能。所以，這也是我們此時成立 ATH 業務部門的原因之一。

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 on the application and infrastructure side in order to achieve sustained improvements over the long term.

總而言之，我認為我們最重要的任務絕對是提升模型效能。然而，要增強模型能力，需要在整個模型流程以及應用程式和基礎設施方面做出共同努力，才能在長期內實現持續改進。

Joyce Ju, Bank of America.

Joyce Ju，美國銀行。

Congrats on the solid progress you've made in cloud and AI. My question is we see CMR growth slowing notably in the December quarter, given the macro pressures. We have seen China's online retail sales only up 2% year-over-year in the fourth quarter '25.

恭喜你在雲端運算和人工智慧領域的顯著進展。我的問題是，鑑於宏觀經濟壓力，我們看到 CMR 的成長在 12 月季度明顯放緩。我們看到，2025年第四季中國線上零售額年增僅2%。

But more recently, MBS data point to a reacceleration in January and February. Could you share your latest view on the CMR trends heading into the March quarter? And whether you have started to see any improvement in element?

但最近的 MBS 數據顯示，1 月和 2 月出現了重新加速成長的跡象。您能否分享一下您對3月季度CMR趨勢的最新看法？您是否已經開始看到這方面有任何改善？

(interpreted) Thank you for your question. Indeed, in the December quarter, weak macro consumption, a 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 benefit increased compared to previous years. So as a result, the CMR and EBITDA trend softened.

（翻譯）謝謝你的提問。事實上，在 12 月季度，宏觀消費疲軟、冬季氣溫偏暖、春節時間較晚等因素都對 12 月季度的經濟成長構成了挑戰。由於促銷季延長，我們對消費者福利的投入比往年增加。因此，CMR 和 EBITDA 的趨勢有所放緩。

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.

進入三月季度，隨著我們觀察到的消費者信心改善以及快速商務策略的推進，我們的實體商品GMV和CMR趨勢已從去年12月季度顯著恢復，預計EBITDA也將相應改善。

All right. Let's move on to the next question.

好的。我們來看下一個問題。

Gary Yu, Morgan Stanley.

Gary Yu，摩根士丹利。

My question is related to Quick Commerce. I understand that in the past couple of months, we have achieved certain milestones in terms of GDV market share and also GDV improvement. How should we look at the priority going forward? Are we aiming for market share or hoping to take this opportunity to improve unit economics, reduce loss?

我的問題與快速商務有關。我了解到，在過去的幾個月裡，我們在 GDV 市場佔有率和 GDV 改進方面都取得了一些里程碑式的成就。我們接下來該如何看待優先事項？我們的目標是爭取市場份額，還是希望藉此機會改善單位經濟效益、減少損失？

And how should we look at the synergy between Quick Commerce and traditional e-commerce? And how should we see these synergies to translate into CMR better growth going forward?

我們該如何看待快速商務與傳統電子商務之間的綜效？我們應該如何看待這些協同效應，才能將其轉化為 CMR 未來更好的成長？

(interpreted) Certainly, 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 in the coming quarters.

（解釋）當然，在擴大市場份額的同時，我們透過提高物流效率、提高盈利能力以及優化訂單組合，持續顯著改善用戶體驗。受上述因素驅動，我們預計在接下來的幾季中將進一步優化。

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 AACs on the platform in the past year. Our AAC number increased [150 million] in 2025, including [100 million] conventional e-commerce physical goods AACs, which is more than the previous three years combined.

就 Quick Commerce 對我們傳統電子商務業務和整個生態系統的正面影響而言，在過去一年裡，我們看到該平台上的 AAC 數量顯著增加。到 2025 年，我們的 AAC 數量增加了 1.5 億，其中包括 1 億傳統電子商務實體商品 AAC，超過了前三年的總和。

Now new consumers ARPU and purchase frequency are lower than that of existing users. So we aim to continually increase their ARPU 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 Freshippo and Tmall supermarkets accelerated growth.

現在新用戶的平均每用戶收入和購買頻率都低於現有用戶。因此，我們的目標是不斷提高他們的 ARPU 和購買頻率，這將成為我們平台未來幾年新的成長引擎。速購顯然正在推動食品、生鮮產品和保健品等各個類別的銷售，並為盒馬鮮生和天貓超市的加速成長做出了貢獻。

In terms of the outlook, we maintain our target of achieving over RMB1 trillion in Quick Commerce GMV by FY28. We expect to generate positive cash flow when the GMV target is achieved, and we expect the Quick Commerce business to be profitable in FY29.

展望未來，我們維持原定目標，即在 2028 財政年度實現快速商務 GMV 超過 1 兆元。我們預計在實現 GMV 目標後將產生正現金流，並預計快速商務業務將在 2029 財年實現盈利。

Quick 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 demand, 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 RMB1 trillion GMV target as a market leader.

Quick Commerce 已成為我們電子商務業務的基石，在人工智慧時代發揮著至關重要的戰略作用，它推動客戶獲取、增強用戶參與度、滿足多樣化的消費者需求、增加交易量、提高盈利能力並支持物流基礎設施。我們致力於在未來兩年內加大對快商的投入，力求成為市場領導者，實現1兆元的GMV目標。

Operator, let's move on to the next question.

操作員，我們進入下一個問題。

Alicia Yap, Citigroup.

Alicia Yap，花旗集團。

I have some questions regarding your chip business (spoken in foreign language). So there have been reports that Alibaba plans to spin off the T-Head unit as a separate listing. Can management provide any information of this? And if so, what is the expected timeframe for this to occur? And in the meantime, can you share more operating metrics?

我有一些關於貴公司晶片業務的問題。（用外語說）有報導稱，阿里巴巴計劃將 T-Head 業務分拆上市。管理階層能否提供相關資訊？如果屬實，預計需要多長時間才能實現？同時，您能否分享更多營運指標？

So in addition to the 470,000 chips that you mentioned you shipped to external customers, how we reconcile that number, the shipments to the revenue side? And also what is the expected growth rate for your chip business in the coming year?

那麼，除了您提到的 47 萬枚向外部客戶發貨的晶片之外，我們如何將這個數字，也就是發貨量，與收入對接呢？另外，您預計未來一年晶片業務的成長率是多少？

And I think you mentioned, currently, it's 60% of these from external customers. So maybe can you also share with us, are these chips for external customer mainly used for inferencing? And then for internal, is it used for model training and also infere ring? And then lastly, how do the (inaudible) chips or TS chips are compared to other domestic chips? If management can share some detail would be great.

我想你也提到過，目前有 60% 來自外部客戶。那麼，您能否也向我們分享一下，這些面向外部客戶的晶片主要用於推理嗎？那麼，對於內部使用，它是用於模型訓練還是也用於推理環？最後，（聽不清楚的）晶片或TS晶片與其他國產晶片相比如何？如果管理階層能分享一些細節就太好了。

(interpreted) Okay. Thank you very much for this question. And I'd like to take the opportunity to expand on this a bit because T-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 firmly believe that T-Head is ranked in the top tier of the domestic AI chip ecosystem in terms of the technology capabilities and product capabilities.

（翻譯）好的。非常感謝您的提問。我想藉此機會再詳細闡述一下，因為 T-Head 是阿里巴巴公司整體人工智慧策略中非常重要的組成部分。因此，在中國國內人工智慧晶片生態系統的背景下，我們堅信，就技術能力和產品能力而言，T-Head 在國內人工智慧晶片生態系統中名列前茅。

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 Bailian inferencing use cases.

我們的產品涵蓋了從模型訓練和微調到推理的整個人工智慧工作流程。我們的 T-Head AI 晶片已經透過阿里雲進行了廣泛的大規模應用，既用於訓練工作負載，也用於百利推理用例。

At the same time, over 60% of T-Head ships 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.

同時，超過 60% 的 T-Head 船舶正在被阿里雲的公有雲和混合雲產品中的外部商業客戶使用。外部商業客戶涵蓋多個行業，包括網路金融、自動駕駛和智慧製造。

And these external commercial customers are utilizing T-Head chips in both their training and inferencing workloads. Moreover, on the T-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.

這些外部商業客戶正在他們的訓練和推理工作負載中使用 T-Head 晶片。此外，T-Head 軟體堆疊與 Linux 生態系統具有極佳的兼容性。因此，客戶可以輕鬆遷移系統，而無需在遷移上花費大量時間。

Another point I would make is that in my view, T-Head's 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 and performance in various respects, we aspire to engage in more profound co-design with Alibaba's cloud infrastructure and the Qwen model to provide improved cost effectiveness.

我想提出的另一點是，在我看來，T-Head 對阿里巴巴的重要性不僅在於我們渴望縮小國產晶片與國外同類晶片在製造工藝和各個維度的整體性能方面的差距。但鑑於我們的晶片在各方面性能仍落後於國外同類產品，我們渴望與阿里巴巴的雲端基礎設施和Qwen模式進行更深入的協同設計，以提供更高的成本效益。

So this is one key differentiator and how we approach chip design at T-Head that sets us apart from other chip companies. 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.

所以，這是我們 T-Head 與其他晶片公司區分開來的關鍵因素，也是我們進行晶片設計的方式。我們的主要目標是創造性價比更高的AI能力。這將使其成為 Bailian 平台的關鍵產品，使我們能夠降低未來的推理成本。

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.

除了普遍提高人工智慧效率和降低成本之外，還有另一個因素在起作用，那就是中國人工智慧產業目前面臨的獨特情況。在這種情況下，對我們來說一個重要的好處是人工智慧運算能力的供應得到了保障，因為我相信在未來三到五年內，全球人工智慧運算能力將極度短缺，尤其是在中國市場。

As the only cloud compute 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.

作為中國市場上唯一一家擁有自主晶片開發能力的雲端運算公司，T-Head 對阿里巴巴集團而言至關重要。增加人工智慧運算能力的供應將有助於我們的雲端運算和人工智慧業務（包括我們的大眾業務）實現更強勁的成長勢頭。

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 RMB10 billion level. Looking ahead to '27 -- well, through 2026, this year through '27, next year, we expect T-Head's production capacity for high-quality AI chips to continue to expand.

在過去的兩年裡，T-Head 已成功實現晶片的商業化和上市，總銷量超過 47 萬片，年收入達到 100 億元。展望 2027 年——確切地說，到 2026 年，也就是今年到 2027 年，我們預計 T-Head 的高品質 AI 晶片產能將繼續擴大。

This will provide robust computing power support for our group's AI business and serve as 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.

這將為我們集團的人工智慧業務提供強大的運算能力支持，並成為我們整體人工智慧計畫的強勁成長動力。我們也相信，未來獲利能力將會提升，利潤水準將進一步提高，這將非常有利。

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

總的來說，T-Head 對阿里巴巴的價值不僅僅在於成本優化。它的主要作用是確保供應鏈的韌性。在運算能力稀缺的時代，我認為這對阿里巴巴的人工智慧策略至關重要。所以這是有可能的，我們也不排除 T-Head 未來考慮進行 IPO 的可能性，儘管目前我們還沒有任何確切的時間表。

Next question, please.

下一個問題。

Yuan Liao, Citic.

袁廖，中信集團。

(interpreted) My question is about the business objectives for your AI strategy that you just mentioned. Revenue for the next five 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 period?

（譯）我的問題是關於您剛才提到的AI策略的業務目標。預計未來五年收入將超過1000億美元。您能提供更多關於這個目標的資訊嗎？例如，如果接下來的五年到 2031 年，那麼這五年期間的複合年增長率 (CAGR) 會是多少？

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 Cloud's margins?

您能否進一步分析推動這種成長的因素，以及我們應該如何理解這些驅動因素？鑑於阿里雲營收的這種可擴展成長，我們何時才能看到其利潤率的持續改善？

(interpreted) 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, the strength of our product portfolio, and the road map to get there.

（翻譯）謝謝你的提問。所以，是的，我們當然相信，五年內，我們人工智慧和雲端運算相關業務的收入將超過 1,000 億美元。我們認為，如果你看看我們今天看到的市場成長、我們強大的產品組合以及實現目標的路線圖，這一點就非常清楚了。

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 riskier trend over the past couple of months, the first two months of 2026, whereby, large models have now gained the capability to execute complex B2B workflows.

我認為這一切背後的主要驅動力是大型人工智慧模型能力的不斷突破。在過去的幾個月裡，也就是 2026 年的前兩個月，我們確實看到了一個風險更高的趨勢，即大型模型現在已經具備了執行複雜的 B2B 工作流程的能力。

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.

越來越多的企業正在部署由大型模型驅動的代理程式來處理端到端的業務任務。這標誌著市場看待 IT 預算的方式發生了根本性的轉變，IT 預算傳統上分配給了人工智慧和雲端服務。

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.

這種轉變的真正意義在於，現在許多企業在使用代幣時，不再將代幣消耗視為 IT 預算的一部分。相反，他們將代幣視為其整體營運或研發成本的一部分。代幣是他們生產投入的關鍵組成部分，而不僅僅是他們 IT 預算的一部分。所以，這是我們看到的推動未來人工智慧成長的最根本的長期因素。

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 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.

我認為，推動成長的最大動力將來自三個領域。首先是大眾市場，這才是真正的核心成長引擎。我們的大眾業務成長將得到各種不同用例的支持，包括我們自己的應用程序，以及來自我們客戶群和各個不同行業的各種人工智慧應用場景，包括人工智慧應用軟體。我們相信，大規模舉措帶來的成長將成為人工智慧和雲端服務未來收入的關鍵驅動力。

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.

但其次，對於人工智慧和雲端運算而言，還有另一個非常重要的成長機會。當然，我們相信大眾市場在未來將會是個相當大的市場。但對於相當數量的中大型企業而言，也會出現對企業級內部推理和培訓的需求，這將催生一個新的市場。而且，這個市場在長期內仍將持續存在。

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 large incremental growth opportunity for Alibaba Cloud's AI infrastructure.

它不會因為每個企業都根據自身的商業模式、特定用例的安全要求或應用場景的特殊性做出決策而消失。因此，對於某些應用場景，企業會選擇使用公有的大規模 API 服務，而許多其他應用場景則會基於企業內部私人部署的解決方案。因此，這類應用場景為阿里雲端的人工智慧基礎設施帶來了巨大的增量成長機會。

Third, there's another important driver, an 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.

第三，還有另一個重要的驅動因素，一個重要的機遇，我認為它常常被忽略。我指的是以 CPU 為中心的雲端運算，也就是傳統的雲端運算，在這個人工智慧時代，它仍然有很大的發展空間。因此，傳統的雲端運算是為IT工程師設計的，而在中國，傳統的IT工程師可能只有幾百萬，也許不超過一千萬。而這些正是傳統的雲端運算客戶。

However, in the future, there could be billions of agents that are created by large AI models and their operating environment. The operating environment 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.

然而，未來可能會出現數十億個由大型人工智慧模型及其運行環境所創建的智慧體。這些代理程式的運作環境也需要傳統以 CPU 為中心的雲端運算的大力支援。他們需要這些傳統的 CPU 以及資料庫、儲存和大量記憶體來支援其長期問題解決和持續營運。

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 implication. 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.

因此，挑戰在於改變傳統的雲端運算市場，從為人類用戶（即 IT 工程師）設計的雲端平台，轉向為基於代理的推理而優化的雲端平台。所以我認為那裡還有巨大的發展空間。因此，我們今年面臨的一個關鍵挑戰是將傳統的雲端運算轉變為更適合代理商使用的平台。而這正是阿里雲升級的重點。

As the revenue from this business continues to grow, our AI business will undergo 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.

隨著這項業務收入的持續成長，我們的人工智慧業務將進行轉型升級，從銷售資源轉向銷售智能，銷售智能能力。我認為這代表著商業模式的巨大升級。

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.

同時，透過整合我們專有的 T 型晶片，我們正在並將繼續實現成本降低和效率提升。我們相信，隨著我們的人工智慧和雲端業務收入規模的不斷增長，雲端獲利能力應該會越來越明顯，我們看到它正走在穩步改善的道路上。

However, the process of continued improvement is not a linear one. 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 chips. And there could be a massive leap forward, but I think that's a function of the product as well and those kinds of economies of scale. But it will not unfold in a linear fashion.

然而，持續改進的過程並非線性過程。有可能出現規模經濟突破，實現規模經濟或擴大我們的 T 型晶片的生產規模。而且可能會有巨大的飛躍，但我認為這也取決於產品本身以及規模經濟。但這並不會以線性方式展開。

So you asked about the CAGR, the compound annual growth rate from 2026 through to 2031. I think you can plug that into your calculator and figure out what it would be assuming it were to be linear, but 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 not yield significant growth until one or even two years from now. However, regarding that overall five-year goal, we are highly confident in our ability to achieve it.

所以你問的是 CAGR，也就是 2026 年至 2031 年的複合年增長率。我認為你可以把這個值輸入計算器，假設它是線性的，然後算出來，但我認為它不會是線性的。我們在研發方面的投入和市場成長並非線性成長，我們今天進行的一些投資可能要到一兩年後才能產生顯著成長。然而，對於這五年的整體目標，我們非常有信心能夠實現它。

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

謝謝接線員，我們來回答最後一個問題。

Alex Yao, JPMorgan.

Alex Yao，摩根大通。

(interpreted) I'd like to shift the topic a little bit and ask a question about e-commerce. You 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 period where I guess we would start to be reaping the returns on a stable basis from those investments?

（翻譯）我想稍微轉換主題，問一個關於電子商務的問題。你之前說過，我們正處於電子商務的三年投資週期。我想知道，現在是否正在調整或受到即時商務和代理商務領域出現的新機會的驅動，還是我們仍然按照最初的三年計劃來考慮？如果是這樣，那麼我們現在實際上正處於這三年計畫的中期，我想我們應該開始從這些投資中穩定地獲得回報了。

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.

所以，如果您能根據您之前提到的三年投資週期，談談電子商務的整體發展方向，那就太好了。也請和我們分享您是如何考慮在電子商務領域進行定位的，以及您的策略。

(interpreted) 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.

（翻譯）謝謝。正如我剛才提到的，今年我們將對即時零售業務，也就是快速商務業務進行非常大的投資。目前來看，我們看到了這個領域存在著非常明確的機會。

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 RMB1 trillion 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.

所以，正如我剛才提到的，我們將繼續在未來兩年內加大投資，以實現快速商務銷售額突破1兆元人民幣的目標。我們也相信，兩年後，我們對 Quick Commerce 的投資將為我們整個電子商務業務帶來積極的財務回報。

(interpreted) But I'd like to add to that by bringing in the dimension of AI because Eddie has 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 in months.

（翻譯）但我想在此基礎上補充人工智慧的維度，因為艾迪已經談論了很多關於人工智慧的內容。我認為人工智慧也將對電子商務產生非常非常重大的影響。然而，就人工智慧而言，三年太長了，因為如今人工智慧的發展速度是以周或月來衡量的。

But that's precisely why we're making significant investments on the AI 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.

但正因如此，我們才在人工智慧領域進行了大量投資，並利用人工智慧為消費者和商家推出新的體驗，同時利用人工智慧升級商家的商業模式。

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 B2B business where we see tremendous opportunities for its deployment and we will actively seize on all of these new opportunities.

我們相信，人工智慧將使我們能夠在電子商務的各個環節中實現巨大的升級。這對我們的 B2B 業務來說是有益的，我們看到了它巨大的部署機會，我們將積極抓住所有這些新機會。

Okay. That wraps 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.

好的。今天的財報電話會議問答環節到此結束。非常感謝您今天蒞臨，我們期待盡快與您再次交流。

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

謝謝。今天的通話到此結束。感謝您的參與。現在您可以斷開線路了。

Portions of this transcript that are marked (interpreted) were spoken by an interpreter present on the live call. The interpreter was provided by the company sponsoring this event.

本記錄中標有（已翻譯）的部分是由現場通話中的翻譯人員翻譯的。本次活動的翻譯人員由活動贊助公司提供。