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即时零售与AI 阿里的「割裂叙事」|估值叙事12

主编24小时在线 2026-06-12 10:31
主编24小时在线 2026/06/12 10:31

邦小白快读

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这篇文章核心梳理了当前阿里在AI转型过程中面临的估值矛盾,核心干货如下:

1. 当前市场对阿里估值有两种主流叙事,一种对标谷歌,认为阿里是中国具备全栈AI垂直整合能力的企业,按谷歌PE计算阿里股价有40%-50%上行空间;另一种对标亚马逊,认为阿里本质是电商+云公司,AI只是长期期权,估值抬升空间有限,当前市场更认可谷歌叙事。

2. 阿里为讲好谷歌AI叙事做了大量组织和人事调整,接连将技术派核心吴泽明推上集团合伙委员会,强化AI的顶层战略地位,每次调整都带动股价出现2%-6%不等的上涨。

3. 阿里同时大额投入即时零售补贴,和AI高投入形成矛盾,市场并不认可即时零售是AI试验场的逻辑,目前AI和零售已经走向平行叙事,阿里估值仍存在较大不确定性。

阿里当前的战略调整对品牌商布局阿里渠道、调整经营策略有明确参考价值,核心干货如下:

1. 阿里即时零售战略已经从抢份额转向减亏盈利,明确了2027财年末UE转正、2029财年整体盈利的目标,目前已经开始压缩低转化率、低毛利补贴,大额满减免单活动显著收缩,品牌商需要调整促销参与策略,重新测算投入产出比。

2. 阿里提出未来三年内即时零售有望带来1万亿元新增成交,这类高频、高实时的交易场景会成为阿里AI模型核心训练数据来源和落地场景,未来阿里会推出更多AI赋能的营销运营工具,品牌商可提前对接布局抢占红利。

3. 阿里整体定位为AI科技平台,电商作为基本盘负责提供稳定现金流,渠道整体稳定性有保障,但品牌商需要关注战略倾斜带来的流量分配变化,提前适配新规则。

阿里当前战略调整给卖家带来了明确的机会与风险提示,核心干货如下:

1. 机会层面:阿里明确未来三年即时零售将带来1万亿元新增成交,属于电商赛道明确的增量市场,同时即时零售作为AI核心训练和落地场景,未来会有更多AI工具开放给商家,帮助卖家降低运营成本、提升运营效率,卖家可提前布局抢占增量。

2. 风险层面:阿里已经把即时零售减亏列为核心硬性考核目标,低转化、低毛利的平台补贴活动大幅收缩,过往依赖平台补贴冲销量的模式难以为继,卖家需要尽快调整自身盈利模型,提升自生盈利能力。

3. 当前阿里核心资源持续向AI和云业务倾斜,电商流量分配逻辑大概率会发生变化,同时AI和零售的战略割裂短期无法弥合,卖家需要提前关注规则变化,适配新的运营玩法。

阿里当前的战略调整,给布局阿里渠道的工厂带来了明确的商业机会和转型启示,核心干货如下:

1. 商业机会层面:即时零售是阿里当前电商板块的核心增量赛道,未来三年将带来1万亿元新增成交,工厂可以针对性布局即时零售赛道,依托高频即时消费场景拓展新销路,获取更多稳定订单,扩大生意规模。

2. 生产设计层面:即时零售的消费需求偏向高频、短周期、小批量,和传统电商需求有明显差异,工厂需要调整自身生产计划和产品设计方向,适配即时零售的消费特征,开发更符合即时消费场景的产品。

3. 数字化转型启示:阿里将即时零售作为AI闭环的核心场景,未来会开放更多AI数字化工具给产业链上下游,工厂可以依托阿里的AI能力推进自身数字化改造,提升生产研发效率,更好更快匹配终端消费需求变化。

本文透露出阿里生态的发展趋势和核心痛点,给To B服务商带来了明确的业务方向参考,核心干货如下:

1. 行业发展趋势:阿里已经明确向AI开放科技平台转型,顶层核心权力向技术派倾斜,AI将成为未来阿里生态的核心驱动力量,围绕阿里全栈AI生态的各类技术服务、运营服务需求会持续增长,行业存在大量新业务机会。

2. 客户核心痛点:当前阿里生态的核心矛盾是AI高投入和即时零售大额补贴的冲突,阿里需要电商板块持续提升利润为AI转型输血,电商商家普遍存在降本增效的刚性需求,服务商可以针对性开发相关解决方案切入市场。

3. 新技术合作机会:阿里走全栈自研AI路线,需要大量垂直场景做AI应用落地,即时零售就是核心落地场景,围绕即时零售场景的AI应用开发、运营服务存在大量合作机会,服务商可以提前对接布局,抢占生态红利。

阿里当前的转型路径,给其他平台型企业的战略规划、运营管理带来了很多参考启示,核心干货如下:

1. 组织调整参考:市场对科技平台AI转型过程中,强化技术派顶层话语权的做法认可度很高,阿里两次调整提升技术派地位都带动股价大幅上涨,计划推进AI转型的平台,可以参考这一组织调整路径,通过明确的组织调整向市场传递转型信号,获得市场认可。

2. 战略平衡启示:AI转型需要大量长期资金投入,平台需要平衡长期AI投入和短期商业业务投入的关系,阿里此前同时大比例投入AI研发和即时零售补贴,引发市场担忧,压制了企业估值,平台需要做好资金分配管理,避免出现战略叙事割裂的问题。

3. 业务定位参考:阿里将原有成熟电商业务定位为现金流基本盘,AI业务定位为未来增长引擎,明确不同业务板块的定位、匹配对应考核目标的做法,对多元业务布局的平台有较高参考价值。

本文展现了中国头部科技企业AI转型过程中的新动向和新问题,对互联网产业研究有较高参考价值,核心干货如下:

1. 产业新动向与新商业模式:当前头部电商科技企业纷纷推进AI转型,阿里探索出了全栈自研AI的路线,构建芯片-云-基础模型的全链路自研闭环,同时将原有成熟零售电商业务定位为现金流基本盘,支撑AI转型投入,形成了“零售输血+AI增长”的新型转型商业模式。

2. 转型过程中的新问题:转型过程中出现了AI叙事和零售业务叙事的割裂问题,市场将AI定价为增长期权,将大额补贴的即时零售定价为利润看跌期权,长期AI野心和短期零售亏损的拉扯,成为压制企业估值的核心因素,这是科技转型中出现的新的估值和战略矛盾。

3. 组织层面的新变化:AI转型推动头部企业顶层权力向技术派转移,阿里已经形成AI战略派和零售商业派两个清晰阵营,两者协同暂时终止走向平行叙事,这是产业转型过程中出现的新组织特征,值得深入研究。

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Quick Summary

This article analyzes the key valuation contradiction Alibaba is facing amid its AI transformation, with core takeaways below:

1. The market currently holds two dominant narratives about Alibaba’s valuation. One frames the company as China’s full-stack vertically integrated AI player, comparable to Google; under this narrative, its stock price has 40% to 50% upside when valued using Google’s PE multiple. The other compares Alibaba to Amazon, framing it as fundamentally an e-commerce and cloud company where AI is just a long-term option with limited room for valuation expansion. The Google-aligned narrative is currently the more widely accepted one among investors.

2. Alibaba has made extensive organizational and personnel changes to reinforce its Google-like AI narrative, including promoting core technology leader Wu Zheming to the group’s partnership committee to elevate AI’s status as a top-tier strategy. Every round of adjustments has driven a 2% to 6% rally in the company’s share price.

3. A contradiction exists between Alibaba’s heavy AI investment and its large subsidies for instant retail. The market does not accept the argument that instant retail serves as a viable testing ground for AI, and AI and retail have now become two separate, parallel strategic narratives. This leaves Alibaba’s valuation facing significant uncertainty.

Alibaba’s ongoing strategic adjustments offer clear guidance for brands operating on its platform to adjust their channel layout and operating strategies, with key takeaways as follows:

1. Alibaba’s instant retail strategy has shifted from capturing market share to cutting losses and turning profitable, with clear targets to reach unit economic profitability by the end of fiscal 2027 and overall profitability by fiscal 2029. The company has already started cutting subsidies for low-conversion, low-margin activities, and large order-discounting promotions have been scaled back significantly. Brands need to adjust their promotion participation strategies and recalculate their return on investment.

2. Alibaba projects that instant retail will generate 1 trillion yuan in additional gross merchandise volume (GMV) over the next three years. This high-frequency, high-real-time transaction scenario will become a core source of training data and deployment use case for Alibaba’s AI models, and the company will roll out more AI-powered marketing and operation tools going forward. Brands can get an early start on integration and positioning to capture first-mover advantages.

3. Alibaba has positioned itself overall as an AI technology platform, with e-commerce as its core cash cow providing stable cash flow. This ensures the overall stability of the channel, but brands need to monitor shifts in traffic allocation driven by the company’s new strategic priorities and adapt to new rules early.

Alibaba’s current strategic adjustments bring clear opportunities and risk alerts for sellers on its platform, with core takeaways below:

1. On the opportunity side: Alibaba has confirmed that instant retail will add 1 trillion yuan in new GMV over three years, making it a clear incremental growth market in the e-commerce sector. As a core AI training and deployment scenario, instant retail will see more AI tools opened to sellers to help cut operational costs and boost efficiency. Sellers can expand into this space early to capture incremental growth.

2. On the risk side: Alibaba has made cutting instant retail losses a core hard performance target, and has drastically scaled back subsidies for low-conversion, low-margin activities. The old growth model that relied on platform subsidies to drive sales volume is no longer viable, so sellers need to adjust their profitability models as soon as possible to build independent profitability.

3. Alibaba is continuing to shift core resources to AI and cloud businesses, which will likely change the platform’s e-commerce traffic allocation logic. In addition, the strategic split between AI and retail cannot be resolved in the short term, so sellers need to monitor rule changes early and adapt to new operational practices.

Alibaba’s ongoing strategic adjustments bring clear business opportunities and transformation insights for factories that sell through Alibaba’s channels, with core takeaways as follows:

1. Business opportunities: Instant retail is the core incremental growth track in Alibaba’s current e-commerce division, and will add 1 trillion yuan in new GMV over three years. Factories can tailor their布局 to enter the instant retail track, leverage high-frequency instant consumption scenarios to open new sales channels, secure more stable orders, and scale their business.

2. Production and product design: Consumer demand in instant retail tends to be high-frequency, short-cycle and small-batch, which differs noticeably from demand patterns in traditional e-commerce. Factories need to adjust their production planning and product design directions to match the consumption characteristics of instant retail, and develop products that better fit instant consumption scenarios.

3. Digital transformation insights: Alibaba uses instant retail as the core scenario for its closed-loop AI development, and will open more AI-powered digital tools to upstream and downstream players in the industrial chain. Factories can leverage Alibaba’s AI capabilities to advance their own digital transformation, improve R&D and production efficiency, and respond faster and more accurately to changes in end consumer demand.

This article reveals the development trends and core pain points of the Alibaba ecosystem, and provides clear guidance on business direction for B2B service providers, with core takeaways below:

1. Industry development trends: Alibaba has clearly positioned itself to transform into an open AI technology platform, and has shifted top-level core power to its technology leadership. AI will become the core driving force of the Alibaba ecosystem going forward, and demand for various technology and operation services centered on Alibaba’s full-stack AI ecosystem will continue to grow, creating a large number of new business opportunities in the sector.

2. Core customer pain points: The core contradiction in the current Alibaba ecosystem is the conflict between heavy AI investment and large subsidies for instant retail. Alibaba needs the e-commerce division to continuously increase profits to fund its AI transformation, and e-commerce merchants have a rigid demand for cost reduction and efficiency improvement. Service providers can develop targeted solutions to enter this market.

3. New technology cooperation opportunities: Alibaba is pursuing a full-stack in-house AI development strategy, which requires a large number of vertical scenarios to deploy AI applications, and instant retail is a core use case. There are extensive cooperation opportunities in AI application development and operation services targeting the instant retail scenario, and service providers can start early integration and布局 to capture ecosystem dividends.

Alibaba’s current transformation path offers many reference insights for other platform companies on strategic planning and operational management, with core takeaways below:

1. Organizational adjustment reference: When tech platforms pursue AI transformation, the market responds very positively to strengthening top-level话语权 for technology leaders. Alibaba’s two adjustments to elevate the status of its technology team both drove sharp share price gains. Platforms planning to pursue AI transformation can reference this organizational adjustment approach, using clear restructuring to send a clear transformation signal to the market and win investor acceptance.

2. Strategic balance insights: AI transformation requires large amounts of long-term capital investment, so platforms need to balance long-term AI spending and short-term commercial business investment. Alibaba’s simultaneous heavy spending on AI R&D and instant retail subsidies triggered market concerns and suppressed its valuation. Platforms need to manage capital allocation well to avoid fragmented strategic narratives.

3. Business positioning reference: Alibaba positioned its existing mature e-commerce business as a cash cow base, and its AI business as the future growth engine. This approach of clarifying the positioning of different business segments and matching them with corresponding performance targets is highly valuable for reference for platforms with diversified business layouts.

This article presents new trends and emerging issues in the AI transformation of leading Chinese technology companies, and offers high reference value for internet industry research, with core takeaways below:

1. New industry trends and new business models: Leading e-commerce technology companies are now pushing forward AI transformation in droves. Alibaba has pioneered a full-stack in-house AI development approach, building a full closed-loop in-house chain from chips to cloud to foundation models, while positioning its existing mature retail e-commerce business as a cash cow to fund AI transformation investment. This has formed a new transformation business model of "retail cash cow funding AI growth".

2. New issues in the transformation process: A narrative split between AI and retail business has emerged during the transformation. The market prices AI as a growth option, while prices heavily subsidized instant retail as a put option on profits. The tension between long-term AI ambitions and short-term retail losses has become the core factor suppressing corporate valuation, which represents a new valuation and strategic contradiction in technology transformation.

3. New organizational changes: AI transformation is pushing top-level power in leading companies to shift toward technology leadership. Alibaba has formed two clear camps: the AI strategy faction and the retail business faction. Their collaboration has been suspended, and the two have moved toward separate parallel narratives, which is a new organizational feature emerging during industrial transformation that merits in-depth research.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

作者:苏打

出品:明亮公司

AI基建与即时零售的投入分配,已成为“制衡”阿里估值的关键。

目前,市场对阿里向AI转型的走势大致有两种主流意见。

一种将其对标谷歌。大摩曾在今年3月份一份报告中指出,“阿里巴巴是中国科技巨头中最接近Alphabet(谷歌)垂直整合能力的企业,横跨芯片、云、基础模型三层”。高盛在去年11月份的报告中持相同观点,认为“阿里正在采取类似谷歌的‘全栈式’打法,押注自研芯片、云、基础模型。”

一种对标亚马逊。摩根大通在今年4月份的报告中指出,阿里首先是一家电商+云公司,与亚马逊完全一致;AI是长期期权,非短期驱动,“我们以亚马逊同业倍数为估值锚”。汇丰在3月份的报告中持有类似观点。

若按谷歌25x倍PE计算,阿里股价有40-50%上行空间。亚马逊叙事的想象空间也不差,但其PE已近40倍,且阿里电商的增速更低,很难抬至同等倍数。更重要的是,如果AI被视为“长期期权”,估值会被无限压制。

对比之下,“谷歌叙事”显然对阿里的估值潜力更划算。

为讲好“谷歌故事”,阿里密集动作,包括大力增加Capex,同时以完成“芯片-云-模型”全栈自研闭环为目标,推动“全球只有谷歌与阿里实现全链路自研”共识的形成。这些努力均获得市场热烈欢迎。

不过,“谷歌叙事”水下,电商业务的角色正在变化。

近日,阿里宣布吴泽明新晋为5人合伙委员之一,带动股价大涨。一面是市场认可其AI主导已逐渐成型,一面是AI战略派与零售商业派形成鲜明阵营,从尝试协同逐渐走向平行叙事。

权责暗线

过去一年,千问大模型共有6次大型迭代,其中2026年上半年密集迭代5次,前5个月“每月一更新”,每次迭代均带动股价上涨。粗略统计,港股涨幅2%-4%、美股涨幅1.5%-3.5%。而Agent落地如发布悟空、店小蜜等,对阿里股价涨幅影响较为温和,多在1%-2%之间,显著反应出市场偏好。

但相较于技术突破,组织架构调整与人事变动这条暗线,在“谷歌叙事”中对估值的影响却更为显著。

2026年3月4日,林俊旸宣布离职,阿里港股当日下跌近5.9%,美股下跌5.5%;3.16ATH宣布成立,港股应声上涨7.8%,美股涨7.5%。

其中,“技术派是否能够上位”成为焦点之一。

6月2日,有消息称,阿里巴巴集团CTO吴泽明(范禹)已于5月份正式进入阿里合伙委员会,与马云、蔡崇信、吴泳铭、蒋凡共列该委员会5名成员。同时,盒马CEO严筱磊从向吴泽明汇报改为直接向蒋凡汇报。

AI从“业务线”完全升级为“顶层战略”后,当日,阿里港股收涨6.60%,美股收涨4.32%。

这一走势早在4月份便曾有过实践。彼时,吴泳铭在内部信中称,吴泽明(范禹)专注阿里巴巴集团CTO工作,负责集团业务技术平台以及AI推理平台建设,并作为技术委员会召集人。其淘宝闪购CEO职务由雷雁群接任。

市场将这一调整解读为“技术派收回AI主导权”,当日,阿里港股收涨6.75%。

两次权力提纯,一步步将吴泽明从蒋凡统筹的业务圈剥离出来,正式纳入吴泳铭构建的技术权力核心。反应在估值上,这一人事调整对阿里股价的正面影响,甚至可以比肩ATH事业部成立,并显著高于整合出Token Foundry事业部等架构调整。

这意味着,市场对于阿里内部在顶层提升技术派的主导权抱有极高期待,甚至直接关乎阿里能否继续讲好类似谷歌的AI叙事。

「割裂」叙事

遗憾的是,这一叙事中,电商业务的处境便略显尴尬。

尽管在阿里的表述中,两者是“一个逻辑”——阿里董事长蔡崇信曾在2026年Q3财报中表示,“烧钱做即时零售不是为了短期盈利,而是为了构建AI时代的基础设施,数据、场景、用户心智”;阿里CEO吴泳铭于Q4财报中继续强调,“我们现在是数据-模型-场景-更多数据的闭环,即时零售是这个闭环里不可替代的发动机。”

其中,高价值“数据”的确是目前阿里极为渴求的部分——尽管拥有庞大的业务生态,但在数据维度、数据频次、数据流通性等关键指标上,阿里面对腾讯和字节的数据丰富度,仍有大课要补。这也是千问被推到台前、成为吸纳数据前置容器的主要原因。

但市场似乎并不买单。2025年5月,阿里宣布投入500亿补贴铺开淘宝闪购后,至7月份股价累计下跌23%;7月份再次确认未来12个月投入500亿补贴后,股价创新低;2026年3月份和5月份,管理层相继宣布投入继续即时零售,令股价又两度出现大跌。

“阿里正面临技术理想主义(AI/云)与商业现实(即时零售补贴战)之间的持续张力。这种内部矛盾,即高AI投入与激进零售开支的冲突,定义了股票的风险收益特征,是当前阿里最大的内部矛盾。”富瑞在2026年4月份发布的《Alibaba:MaaS to Drive Next 5 Years》报告中指出。

大摩在今年5月份2026年5月《Best AI Enabler in China》中亦指出,“投资者实质上把AI定价为增长期权、把即时零售定价为利润看跌期权。长期AI野心与短期零售亏损之间的拉扯,仍是压制市场情绪的核心因素。”

“谷歌叙事”与“大幅补贴”的割裂,阿里也曾尝试弥合。

最初是尝试讲通“即时零售对AI有价值、很有价值且将越来越有价值”的逻辑。如阿里电商事业群CEO蒋凡于26Q1财报中所言,“未来三年内,闪购和即时零售有望带来1万亿元新增成交。这些高频、高实时、高场景密度的交易,会成为我们AI模型最重要的训练数据来源和应用场景。”

同时不能放弃主线。2025年云栖大会上,吴泳铭表示,阿里的战略重心是“用户为先、AI驱动”,要“从传统电商平台,转型为服务全社会AI创新的开放科技平台企业”。

如果展开讲讲电商业务的定位呢?吴泳铭在云栖大会中的表述是,阿里未来是双轮驱动,一边是消费平台,负责现金流与基本盘;一边是AI+云科技平台,负责未来增长与价值创造。

翻译一下,“电商负责现金流,AI负责估值与未来增长”。

电商业务「转身」

据阿里5月份公布的2026财年年报,淘天(中国电商)经调整EBITA为1075亿元,同比下降44%;集团自由现金流-466亿元,同比减少约1204.8亿元,降幅约163.1%。

如果叠加年度约1260亿元AI基建投入(对应三年3800亿投入),以及多家券商测算的即时零售亏损约700亿元,整个财年合计约2000亿元战略支出,几乎全部由淘天利润覆盖——期内,阿里云经调整EBITA仅为142.7亿元,AIDC和其他业务均为亏损。

不仅如此,26财年集团研发费用同比增加约16%,亦主要投向AI算力与云基础设施,而电商业务核心客户管理收入(CMR)增速仅为1%。

要走向谷歌,未来阿里还需要继续构建系统级入口、全球化覆盖,甚至在长期做到基础研究全球领先,形成全球科技基础设施以及“信息+商业双生态闭环”。云业务不能担纲,其他业务更不能指望,还得电商继续“输血”。

可以想见电商事业群CEO蒋凡的心情。

大摩还在2025年9月发布《China’s AI Path:Owning the Full AI Stack》中添油加醋:“阿里的云/AI业务是核心估值引擎,而即时零售(QC)短期仍是主要现金消耗器。在大规模AI资本开支与激进的即时零售补贴之间取得平衡,将是对管理层资金分配纪律的关键考验”。

面对即时零售究竟是“AI试验场”还是“商业战场”的抉择,蒋凡2025年3月表示“先拿到足够的市场份额,再谈盈利与价值释放”,11月便称“将UE优化作为即时零售的核心目标”。

今年4月,雷雁群上任后,又发布全员信表示将全面压缩低转化率、低毛利补贴;大额满减/免单显著收缩;年度核心目标为亏损减半(从约700亿降至350亿)。这是阿里首次把即时零售的减亏目标量化到具体金额,标志着其“要利润”从战略目标落地为硬性考核。

5月13日2026财年业绩电话会中,蒋凡首次明确UE转正具体时间,“我们有信心在2027财年末实现UE转正。2029财年实现整体盈利。”

估值方向

伴随吴泽明进入合伙委员会,AI基建与即时零售两个叙事似乎变得更加平行。

先来看一下这位“老技术派”的升迁履历。2022年起,吴泽明便被张勇任命为集团CTO,同时兼本地生活CTO、淘天CTO、饿了么董事长;2024-2025,其兼任淘宝闪购CEO,亲自带队打外卖大战。

彼时,技术与业务在阿里还是紧密结合,此前的外卖大战中,吴泽明也曾负责用技术(AI)驱动业务增长。

而此次调整将其从业务线彻底剥离后,AI战略派与零售商业派的阵型变得更加清晰,一边是吴泳铭、周靖人、吴泽明,一边是蒋凡、雷雁群及老铁军。

既然“即时零售对AI有价值”的逻辑不被认可,电商业务的战略优先级急剧退坡,但构建AI叙事又需要利润支撑,蒋凡与雷雁群便放开了手脚。

6月2日,美团CEO王兴在Q1财报电话会中多次强调,外卖补贴的竞争态势开始趋于理性,6月3日,阿里便间接对外表示,“美团并非不可战胜,外卖大战才刚刚开始”。

从打配合转向要利润变得顺理成章,也等同于宣告电商与AI之间的协同尝试已暂时终止。因此,短期之内市场可能无法看到阿里对AI和商业两个割裂叙事弥合的成果。而这将进一步考验阿里估值的弹性。

那个问题仍有待解答,AI交易繁荣的当下,阿里应按什么方向来估值?

注:文/主编24小时在线,文章来源:明亮公司(公众号ID:suchbright ),本文为作者独立观点,不代表亿邦动力立场。

文章来源:明亮公司

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