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編輯:米奇 來源:財經會議圈蔡崇信 VivaTech 2026 巴黎峰會完整對談實錄(中英對照,官方整合全文)
時間:2026 年 6 月 18 日 巴黎 VivaTech
主論壇形式:圓桌深度訪談(主持人:Publicis 集團 Maurice Lévy)
嘉賓:阿里巴巴集團主席 蔡崇信(Joe Tsai)
主題:AI 全棧戰略、50 萬億 AI 市場、開源、歐洲數據主權、產業落地
蔡崇信在VivaTech歐洲科技峰會上對AI的核心觀點,以及阿里全面投入AI的戰略邏輯,核心內容可總結為6點:
重估AI市場空間:不應以軟件市場或企業IT支出衡量AI價值,AI本質是創造等同人類智能與生產力的價值。全球超100萬億美元GDP中,至少一半來自智力勞動與生產效率,因此AI對應數十萬億美元級的增量生產力市場,這是阿里All in AI的根本原因。
堅定AI全棧布局:AI產業分為能源、芯片/基礎設施、模型、應用四層,阿里覆蓋后三層,擁有從芯片、云計算、Qwen大模型到淘寶、餓了么、高德等全鏈路能力;疊加中國成熟的能源供給體系優勢,場景帶來的反饋數據與落地機會,構成了阿里區別于單一賽道AI公司的核心競爭力。
回應AI基建泡沫質疑:全球頭部云廠商明年資本開支或超1萬億美元,若僅對標企業IT支出確實偏高,但若錨定數十萬億生產力市場,當下的基建投入類似電力普及初期的電網、電站建設,是支撐長期生產力發展的必要基礎。
現金流支撐戰略落地:阿里電商業務每年可產生約250億美元自由現金流,無需過度依賴外部融資,就能持續支撐AI基建、模型訓練、算力擴容的投入。
看好制造業AI落地潛力:未來最具價值的AI數據并非來自互聯網,而是來自產業現場的設計、測試、質控、生產流程等專有數據,這類數據積累數十年、壁壘極高,結合模型可訓練出真正懂行業的AI系統。
明確阿里AI戰略核心:將AI定義為下一代生產力基礎設施,打通云、模型、業務場景與產業客戶的閉環,AI已成為阿里未來最核心的戰略方向,在近幾個季度的財報中也得到了持續體現。
蔡崇信VivaTech現場全文
主持人開場
Maurice Lévy:歡迎來到 VivaTech,今天我們對話阿里巴巴主席蔡崇信。過去 25 年阿里從中國電商起步,如今站在 AI 變革的關鍵節點。全球都在關注兩件事:第一,AI 到底有多大市場空間;第二,阿里巴巴如何構建 AI 長期競爭力,以及中國科技企業能給歐洲帶來什么合作機會。Joe,先請你分享對 AI 市場規模的核心判斷。
蔡崇信完整發言(中文完整版 + 對應英文原文) AI 的 50 萬億美元總潛在市場(核心開篇觀點)
蔡崇信(中文):很多行業分析師習慣用企業 IT 支出、軟件市場規模去測算 AI 空間,這個視角太狹窄了。AI 的本質,是創造一套等同于人類智能、人類生產力的全新價值單元。當前全球 GDP 總量超過 100 萬億美元,其中至少一半,也就是 50 萬億美元,全部來自人類腦力勞動、生產效率創造的價值。這 50 萬億美元,就是 AI 完整的潛在市場(TAM)。這也是阿里巴巴選擇全面 all in 人工智能的根本邏輯。如果只把 AI 理解為聊天機器人、云服務售賣,上千億的投入會顯得成本極高;但如果把 AI 看作電力、鐵路一樣,支撐未來數十年全球經濟的底層基礎設施,今天的大規模投入,就是在搭建全人類下一代生產力底座。
英文原文:Most analysts measure AI market size based on enterprise IT or software revenue, which is far too narrow.AI creates a new unit of value equivalent to human intelligence and human productivity. Global GDP exceeds $100 trillion, and at least half of that — $50 trillion — comes from human cognitive labor and productivity gains. That $50 trillion is AI’s total addressable market.This is why Alibaba is fully committed to AI. If you only see AI as chatbots or cloud subscriptions, multi-billion-dollar investment looks costly. But if you view AI as foundational infrastructure like electricity or railroads that will power the global economy for decades, today’s heavy investment is building the productivity backbone for the next generation.
阿里千億級 AI 投入與現金流支撐
蔡崇信(中文):抓住 50 萬億級機遇,必須持續、不計周期的大額投入。阿里巴巴核心電商業務每年穩定產生約 250 億美元自由現金流,這是我們持續加碼 AI 的堅實資金底盤。早在 2025 年 2 月,集團正式承諾:未來三年,累計投入超 3800 億元人民幣(折合 530 億美元),全部用于 AI 算力、云基礎設施、自研芯片與大模型研發。放到中國產業視角看,當前國內 AI 算力、全產業鏈基礎設施的整體投入依然不足,所有中國科技企業都應當加大長期布局投入。阿里是國內少數具備穩定現金流、能長期扛住重資產投入的企業,我們有責任持續加碼。
英文原文:Capturing this$50 trillion opportunity requires sustained, long-cycle massive investment.Our core e-commerce business generates roughly $25 billion in free cash flow every year, forming a solid financial foundation for continuous AI investment. Back in February 2025, Alibaba committed to investing over RMB 380 billion ($53 billion) across three years, fully dedicated to AI computing power, cloud infrastructure, self-developed chips and foundation models.From China’s industrial perspective, overall investment in AI computing and full industrial chain infrastructure remains insufficient. All Chinese tech companies should ramp up long-term R&D spending. Alibaba is among the few domestic firms with steady cash flow to sustain heavy capital expenditure, and we bear the responsibility to keep investing aggressively.
3四層全棧 AI 戰略(阿里核心差異化優勢)
蔡崇信(中文):我們的核心戰略是全棧一體化布局,沒有人能精準預判未來 AI 價值會沉淀在哪一層,完整掌控產業鏈每一環,才能隨市場變化靈活調整、持續沉淀壁壘。整個 AI 產業鏈分為四層:第一層是能源層:中國擁有高效、低成本的綠色能源供給,這是我們發展算力得天獨厚的基礎優勢,海外多數企業不具備同等條件;第二層是基礎設施層:平頭哥自研 GPU 芯片,累計交付 56 萬片,搭配阿里云全球分布式算力集群,構建底層算力底座;第三層是模型層:通義千問(Qwen)開源大模型,已開放 300 + 系列模型,全球下載量突破 10 億次,是全球最主流的開源模型之一;第四層是應用層:阿里擁有電商、即時零售、本地生活、地圖、文旅等海量真實商業場景,為 AI 提供規模化落地、持續迭代的數據土壤。
全球范圍內,同時完整覆蓋算力、基礎大模型、大規模真實商業場景的科技公司非常稀少。全棧布局最大價值不是 “什么都做”,而是內部協同閉環:業務場景產生真實業務數據,反哺大模型持續優化;云與芯片降低模型訓練、推理成本,反過來讓 AI 應用大規模普及,形成正向循環。
英文原文:Our core strategy is end-to-end full-stack AI. No one can accurately predict which layer will capture most AI value long-term. Controlling every segment of the industrial chain lets us adapt flexibly as markets evolve and build sustainable moats.The full AI stack has four layers:
Energy layer: China provides efficient, low-cost green energy supply, a unique advantage for computing power that most overseas competitors lack.
Infrastructure layer: Our T-Head self-developed GPUs have delivered over 560,000 chips, paired with Alibaba Cloud’s global distributed computing clusters to form the underlying computing foundation.
Model layer: Qwen open-source series includes more than 300 models, with over 1 billion global downloads, ranking among the world’s most popular open foundation models.
Application layer: Alibaba owns massive real-world commercial scenarios — e-commerce, instant retail, local services, maps, travel hospitality — providing abundant real data for large-scale AI deployment and continuous iteration.Very few global tech firms fully cover computing infrastructure, foundation models and large-scale real business scenarios simultaneously. The strength of full-stack layout is not just breadth, but internal synergy: business scenarios generate authentic operational data to refine models; chips and cloud cut training/inference costs, accelerating mass adoption of AI applications, creating a self-reinforcing positive loop.
開源 AI:回應歐洲技術主權、數據隱私訴求
蔡崇信(中文):今天歐洲企業最關心兩個問題:技術自主可控、本地數據隱私安全,開源模型恰好是最優解決方案。企業基于開源模型,完全可以在本地機房獨立部署、自主微調,所有核心業務數據全程留在企業自有防火墻內,不需要把敏感數據上傳至第三方外部平臺,完美契合歐盟 GDPR、歐洲數據主權政策。我常打一個比喻:全球技術格局下,企業不能把所有雞蛋放進同一個技術供應商的籃子。開源生態就是企業的安全備份,擺脫單一廠商鎖定、規避 “殺戮開關” 風險。客觀來講,當前全球 AI 開源浪潮的核心推動力量來自中國企業。過去幾年阿里團隊持續開放前沿模型,未來我們還會持續加碼開源投入,向全球企業開放輕量化、可本地部署的 Qwen 系列模型。
英文原文:European enterprises today focus on two core priorities: technological sovereignty and local data privacy. Open-source models deliver the optimal solution.Companies can fully deploy and fine-tune open models on-premises, keeping all sensitive business data behind their own firewalls, without transferring confidential data to third-party external platforms — fully aligned with GDPR and Europe’s data sovereignty agenda.I often use a simple analogy: in today’s global tech landscape, enterprises should not put all eggs in one vendor’s basket. Open-source ecosystems act as a safety backup, freeing businesses from single-vendor lock-in and eliminating the risk of remote kill switches.Objectively, Chinese enterprises are the primary driving force behind global AI open-source development. Alibaba teams have continuously released cutting-edge open models over the past years, and we will keep investing heavily in open-source, offering lightweight, deployable Qwen variants for enterprises worldwide.
AI 產業落地:制造業是下一個爆發賽道,歐洲深度合作
蔡崇信(中文):大眾目前看到的 AI 應用大多面向 C 端消費者,但真正會拉動萬億級增量的,是工業制造業 AI。阿里巴巴已經和博世等歐洲頭部制造企業落地合作,用 AI 優化產品研發設計、自動化產線測試、全流程質量管控、供應鏈預測。制造業擁有海量設備數據、生產流程數據,是大模型落地價值最高的場景。中歐在 AI 產業上具備極強互補性:歐洲擁有頂尖工業制造、精密工藝、合規治理經驗;中國擁有成熟算力基礎設施、海量市場場景、規模化 AI 落地實踐。雙方完全可以建立產業協同,歐洲企業提供工業 know-how,阿里輸出算力、開源模型、云平臺,共同打造面向全球的工業 AI 解決方案。
英文原文:Most visible AI applications today target consumers, but the trillion-dollar growth engine will come from industrial manufacturing AI.Alibaba has launched partnerships with leading European manufacturers including Bosch, applying AI to product R&D design, automated production testing, full-lifecycle quality control and supply chain forecasting. Manufacturing generates massive equipment and production workflow data, making it the highest-value vertical for foundation model deployment.China and Europe hold highly complementary strengths in AI industry: Europe leads in advanced manufacturing, precision engineering and regulatory governance; China boasts mature computing infrastructure, massive market scenarios and large-scale AI commercialization experience. We can build deep industrial collaboration: European firms contribute industrial domain expertise, while Alibaba provides computing power, open-source models and cloud platforms, co-developing global industrial AI solutions together.
回應 AI 泡沫爭議:短期波動不改變長期價值
蔡崇信(中文):市場頻繁討論 AI 投資泡沫,但泡沫更多是金融層面的短期情緒,而非技術本身的長期價值。類比 2000 年互聯網泡沫:資本市場出現劇烈波動,但互聯網最終重塑了全球商業。AI 同理,短期算力、芯片賽道估值起伏,不會改變 AI 重構生產力的底層邏輯。判斷 AI 技術價值的唯一標準,是能否落地真實產業場景、創造可量化的經營效率提升。阿里所有 AI 投入,全部圍繞真實業務落地,拒絕脫離產業的純概念研發,這也是我們抵御行業周期波動的核心底氣。
英文原文:Many market participants debate an AI investment bubble, yet volatility stems mostly from short-term financial sentiment, not the long-term intrinsic value of the technology.We can draw a parallel to the 2000 internet bubble: capital markets saw extreme swings, but the internet ultimately reshaped global commerce. AI follows the same logic — short-term valuation fluctuations in chips and computing power will not alter AI’s fundamental ability to redefine productivity.The only metric to judge AI’s real value is its ability to deploy in real industrial scenarios and deliver measurable efficiency gains. Every dollar Alibaba invests in AI targets tangible business use cases; we reject pure conceptual R&D disconnected from real industries, which forms our core resilience against industry cycles.
結尾:全球化 AI 合作,拒絕技術割裂
蔡崇信(中文):AI 是屬于全人類的通用技術,技術割裂、技術陣營化只會抬高全球企業創新成本,延緩生產力升級。阿里巴巴堅持全球化開放路線,開源、云、AI 算力服務面向全球所有地區企業,包括歐洲本土中小企業。我們希望搭建中立、開放的技術合作平臺,讓不同國家、不同行業的企業共享 AI 基礎設施紅利,共同挖掘 50 萬億美元的生產力增量市場。
英文原文:AI is a general-purpose technology for all humanity. Fragmented tech blocs only raise global innovation costs and slow productivity progress.Alibaba adheres to a global open strategy: our open-source models, cloud and AI computing services are available to enterprises across all regions, including European small and medium businesses. We aim to build a neutral, open collaboration platform, allowing companies from all countries and industries to share the benefits of AI infrastructure and jointly unlock the $50 trillion productivity market.
主持人追問 & 補充問答精簡實錄
主持人:歐洲企業擔心數據出境,開源模型如何徹底規避風險?蔡崇信:Qwen 全系列支持本地私有化部署,模型權重完全交付企業本地服務器,不需要向阿里傳輸任何原始業務數據;企業自主掌握微調、推理全流程,數據不出本地機房,完全符合歐盟數據合規要求。
主持人:阿里 3800 億 AI 投入,短期會擠壓利潤嗎?蔡崇信:電商穩定現金流可以平滑長期重投入,我們不追求短期利潤最大化,優先完成 AI 基礎設施建設;中長期 AI 會反向賦能電商、制造、本地生活全業務,形成新增長曲線。
主持人:中美 AI 競爭背景下,開源能否保持中立?蔡崇信:開源本身無國界,代碼對全球開發者公開;阿里開源策略純粹面向產業落地,不綁定單一區域政策,歐洲、美國、東南亞企業均可無差別使用、二次開發。
官方原文獲取渠道
阿里巴巴集團英文官網完整實錄(含完整英文逐字稿):https://www.alibabagroup.com/document-2004662016358219776
VivaTech 官方活動回放頁面(視頻 + 文字摘要):https://vivatechnology.com/sessions/session/8d750ae5-8a43-f011-8f7d-6045bdf3af56
中文官方通稿:
阿里研究院、環球網、新浪財經同步發布完整中文轉述稿
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