Wu Yongming Seeks to Diversify Revenue Streams for Alibaba AI.

Author | Jing Xing

Editor | Gu Nian

GMV (Gross Merchandise Volume) used to be the primary metric for growth in Alibaba's e-commerce empire. Whoever could attract more merchants, orders, and transactions was seen as being closer to the heart of Alibaba's power.

In the age of AI, Alibaba has started to adopt this familiar business language, but the focus has shifted from measuring commodity transaction volumes to measuring Token consumption.

In mid-March, Alibaba established the ATH Business Group. On April 8, Wu Yongming issued another internal memo, further restructuring the AI organization: Tongyi Lab was upgraded to a business division, led by Zhou Jingren; Li Feifei was appointed as CTO of Alibaba Cloud, focusing on AI cloud infrastructure; Wu Zeming became the group's CTO, responsible for the AI inference platform; and a Technology Committee was formed, led by Wu Yongming himself. Following these moves, Alibaba is elevating AI from being merely a module within its cloud services to a cornerstone of its group-wide commercial strategy.

Previously, Alibaba AI's revenue generation was primarily tied to increased cloud business revenue. Now, Alibaba aims to sell 'new products' tailored for the AI era—Tokens—and has reorganized its structure around their creation, distribution, and consumption. Traditionally, Alibaba's organizational adjustments have often followed the Double 11 shopping festival, mainly to optimize for GMV.

Within the new ATH Business Group, Tokens have become Alibaba AI's equivalent of GMV. Around this new transaction model, Alibaba has built an 'AI power grid' on the supply side: Tongyi provides the models, Alibaba Cloud supplies the infrastructure, the inference platform ensures efficiency, and Wukong, Qianwen, and innovative businesses transform capabilities into products.

In his internal memo, Wu Yongming described AI Agents as a historic opportunity: 'On the eve of AGI's breakthrough, a vast number of digital tasks will be supported by billions of intelligent agents, with Token generation from models underpinning their operation and becoming the primary medium for interaction between humans and the digital world.'

Concurrently, Alibaba introduced an internal AI incentive plan, offering employees free Token quotas for using paid AI tools and allowing reimbursement for externally developed tools.

Tokens may serve as Alibaba AI's GMV, but for them to be as convincing as e-commerce GMV, consumption cannot be limited to Alibaba's ecosystem. Especially in a conglomerate with diverse businesses and rich internal scenarios like Alibaba, if significant Token consumption occurs within Taobao, Tmall, DingTalk, and other proprietary ecosystems, it can enhance organizational synergy and strengthen AI's strategic position. However, whether this translates into genuinely new commercial revenue depends on whether external clients and developers are willing to continue paying.

Developers contribute to Alibaba Cloud, while external clients may rely on Taobao and Tmall. This is another layer of meaning behind 'Alibaba AI Takes on the GMV Challenge': at the e-commerce level, AI products must ultimately drive GMV for merchants.

Also on April 8, it was revealed that Alibaba's China E-commerce Business Group had undergone changes. Zhang Kaifu, previously in charge of AI business, had his role adjusted, and the 'Intelligent Search and Recommendation Product Division' he led over the past year was formally split, with its core multimodal R&D team integrated into the ATH Business Group. This indicates that Taobao and Tmall's previously 'in-house' AI systems are being restructured into the group's Token commercialization framework.

A surprising outcome is that HappyHorse, a viral video generation model from Alibaba's ATH Innovation Division, originated from Taobao and Tmall Group's Future Lab. The project is led by Zhang Di, formerly the technical lead for Kuaishou's Kling.

Meanwhile, Taobao and Tmall began recruiting AI Agent service providers, with the Qianniu platform upgrading to 'Qianniu Claw,' planned for promotion around the 618 shopping festival. Merchants using Qianniu Claw consume Tokens, with costs shared by merchants or jointly borne with service providers. After these adjustments, selling Agents to merchants and validating Token value through business results have become key.

This brings Alibaba AI's commercialization back to a classic Alibaba-style question: Can AI drive GMV? If Tokens represent GMV within ATH, then real GMV from merchant businesses is the ultimate test for external markets. The former addresses organizational operation, while the latter determines commercial viability.

In the past, Taobao and Tmall carried transaction pressure. Now, ATH carries consumption pressure, with Alibaba demanding that AI, like its past e-commerce business, undergo results-oriented, commercial conversion, and growth assessments.

GMV once defined Alibaba's e-commerce empire. Now, Alibaba wants to first define its AI business with Tokens. This aligns perfectly with Wu Yongming's statement at Alibaba's earnings call: using Tokens as products, AI applications as distribution channels, and high-quality models as advertising to drive MaaS business growth. Facing the historic opportunity of intelligent agents, Alibaba has chosen to take AI 'out of the cloud' and focus on profitability.

However, AI has not yet become Alibaba's next Taobao or Tmall, but it has already taken on Taobao-style GMV assessments.

AI-Driven E-Commerce

Compared to previous years of large model exploration, a significant shift in Alibaba's strategy is the reversal of the primary-secondary relationship between its e-commerce main business and AI business. AI is transitioning from a supporting role in superficial e-commerce transformations to the core engine of Alibaba's future growth. Whether AI capabilities can be sold and services consumed using e-commerce transaction logic will determine if Token consumption can replace GMV as Alibaba's new growth metric.

'In the past, merchants spent hours daily on store visits, advertising placements, and SEO optimizations. In the future, a 7x24 intelligent team will take over operations,' summarized an e-commerce industry observer regarding Taobao's merchant intelligent agent features.

On March 26, the head of Taobao and Tmall Group's merchant platform announced the launch of the 'Lobster Version' Business Assistant, providing merchants with full-link, low-cost intelligent agent operational capabilities.

Currently, Alibaba has built a matrix of six intelligent agent products available to merchants, initiating a massive 'horse racing' competition.

Even before ATH's establishment, Alibaba's various business divisions independently developed and iterated intelligent agent products, such as Alibaba International's Accio Work, Alibaba.com's AI Business Assistant, 1688's Aoxia, and Alimama's AI Wanxiang. With the addition of the Wukong platform from the ATH Business Group, Alibaba is offering merchants a full-spectrum, all-type intelligent agent matrix.

Previously, Alibaba's AI strategic focus leaned toward the C-side market. Last year, Alibaba separated the Tongyi application team from Alibaba Cloud and placed it under the Smart Information Business Group to ensure Tongyi's influence among C-side users. It merged the Tmall Genie team with the Quark team to explore market opportunities for AI hardware.

Subsequently, it merged the Smart Information and Smart Connectivity Business Groups to form the Qianwen C-side Business Group, covering Qianwen, Quark, AI hardware, Shuqi, and UC. Alibaba attempted to position Qianwen as a super AI-to-C gateway, extending from online platforms to scenarios like glasses, computers, and cars, bringing Qianwen closer to ordinary users.

However, as the intelligent agent market rapidly matured, Alibaba swiftly pivoted, targeting the B-side market with greater Token consumption potential as its next primary objective. With the integration of the e-commerce intelligent search and recommendation multimodal team into ATH, Qianniu Claw replaced scattered merchant AI tools, becoming the core carrier of AI-driven e-commerce.

For Alibaba, focusing intelligent agent revenue on the B-side is not just about merchants' greater need for Agents but also about upgrading revenue models and profitability. Under the MaaS model, merchant intelligent agents will directly drive massive subscription fees and Token usage fees, extending the platform's revenue reach beyond advertising and commissions. Meanwhile, B-side merchant payments offer advantages of high average revenue per user, high willingness to pay, high profit margins, and low customer acquisition costs.

Financial report data more intuitively demonstrates the potential of e-commerce intelligent agents.

In the fourth quarter of 2025, Alibaba's China E-commerce Customer Management (primarily commission and advertising revenue) reached RMB 102.664 billion, with an adjusted profit margin of around 22%, but revenue growth was only 1% year-over-year. Cloud services (including revenue from API calls, model services related to large models) amounted to RMB 43.284 billion, with an adjusted profit margin of 9%, but revenue growth reached 36% year-over-year. The AI Agent layout for B-side merchants means finding a larger, more mature, and more profitable market for AI.

For merchants, this necessitates a shift in past cost accounting methods.

Previously, Taobao and Tmall's revenue mainly came from merchant transaction commissions, advertising placements, and value-added services for operational tools, with merchants calculating ROI based on advertising consumption. In the large model era, AI began intervening in merchant decision-making, assisting in after-sales service, advertising placements, and inventory management. In the Agent era, the platform and merchants' ROI calculation systems are completely restructured. When AI Agents can monitor competitor prices 24/7, automatically optimize advertising strategies, batch-generate product materials, and handle intelligent customer service inquiries, merchants must factor in saved labor and traffic costs to assess the value of purchasing intelligent agents.

Leaked user screenshots show that Alibaba's Wukong offers around 5 million free Tokens daily, but they are consumed extremely quickly. A Wukong user told 'Shixiang' that they primarily experimented with the free trial Tokens but found the testing effects unsatisfactory, with the free quota insufficient to complete effective tasks.

This is also a pain point the ATH Business Group urgently needs to address—how to make intelligent agents move beyond ineffective thinking and address merchants' core issues, enabling the Token economy to bridge the last mile.

Beyond Alibaba Cloud

Alibaba's moves have been notably aggressive.

In early March this year, Lin Junyang, the core leader of Alibaba's Tongyi Qianwen, and several key R&D personnel resigned, likely due to conflicts between R&D goals and commercialization KPIs.

After Lin Junyang's departure, the Qwen3.5-Omni version ceased open-sourcing, revoking developers' free download and secondary training permissions, and tightening model control to support the paid system. Concurrently, Alibaba Cloud service prices increased, and the Wukong intelligent agent saw frequent releases, further accelerating Alibaba's AI commercialization pace.

Compared to ByteDance's 2024 AI business organizational adjustments, both Alibaba and ByteDance chose to centralize resources, mobilizing the entire organization through a unified command center to strengthen core model departments.

ByteDance upgraded its AI business to a first-tier strategic department, on par with Douyin's business line, reporting directly to CEO Liang Rubo. It established two major AI teams—Seed, focusing on large model R&D, and Flow, focusing on AI products.

The strategic thinking behind this was to create independent innovation departments, prioritizing rapid trial-and-error to explore future intelligent application forms and avoid interference from existing businesses.

In contrast, Alibaba chose to have its group CEO personally lead, integrating scattered initiatives like Tongyi, Qianwen, and Maas into ATH. The new business group is no longer an independent innovation zone but the group's main force, configured with the highest-caliber team to pursue ultimate commercialization. Wu Yongming explicitly stated that Alibaba Cloud and AI commercialization revenue should exceed $100 billion within five years.

Among global internet giants, Alibaba is making an unprecedentedly aggressive adjustment—taking AI 'out of the cloud.'

Through the ATH Business Group layout, Alibaba is deploying an AI 'power grid,' with Tokens as electricity, Tongyi as the power plant, MaaS and inference platforms as the transmission network, and application platforms like Qianwen and Wukong as consumption terminals. The entire network is directly scheduled by the CEO, with unified decision-making by the Technology Committee to ensure efficient operation from power generation to consumption.

Microsoft, Amazon, and Google all adhere to a cloud+AI strategy, deeply integrating their large model teams with cloud service departments. The reason is that models can reuse the existing computing clusters and government-enterprise customer resources of cloud businesses, strengthening unit prices and payment willingness as value-added items for cloud services, forming a commercial closed loop of cloud infrastructure + large models + industry applications, rather than independently exploring commercialization paths.

Now, with the establishment of the ATH Business Group, Alibaba is overhauling its approach by leveraging AI beyond the cloud. As intelligent agent technology matures, the commercialization of large models no longer revolves around private deployments for government-enterprise clients but targets all types of enterprises, developers, and even ordinary merchants and users across the market, distributing Agent capabilities as Token channels.

Should this vision come to fruition, the daily Token consumption of a single e-commerce merchant could potentially outstrip that of previous enterprise clients.

From the perspective of the capital market, Alibaba is in dire need of a more expansive narrative. As Chinese e-commerce growth grinds to a halt at 1%, its core business is teetering on the brink of stagnation. Alibaba is in a desperate search for an AI story to prop up its group valuation.

Previously, certain investors in the capital market were of the opinion that Alibaba was overreaching by simultaneously waging two capital-intensive battles: flash sales and AI. The independence of ATH and its equal standing with e-commerce and Alibaba Cloud signal a transformation in Alibaba's valuation rationale, with e-commerce, flash sales, cloud services, and Token narratives providing multi-pillar support.

However, bold transformations are inevitably accompanied by growing pains.

Take e-commerce scenarios as a case in point: Both ATH and Taobao-Tmall are vying for the same pool of merchant marketing budgets. While ATH aims to maximize Token consumption and enhance merchant marketing efficiency through AI Agents, Taobao-Tmall merchants are also contemplating harnessing AI to optimize advertising placements, thereby achieving higher transaction volumes at lower traffic costs.

On the consumer side, Taobao's shopping assistant already performs fundamental functions such as product search, price comparisons, review checks, and generating consumption advice. This runs counter to Taobao-Tmall's growth strategy of maximizing user browsing and ad exposure/conversion. ATH is solely responsible for driving Token consumption, while the potential shrinkage and losses of intermediate links must be shouldered by Taobao-Tmall.

This was one of the reasons why mainstream apps like Taobao, Meituan, Pinduoduo, WeChat, and Gaode banned Doubao's mobile AI assistant. It now presents a dilemma that Alibaba must address.

For the time being, AI represents Alibaba's most reliable growth engine and is widely recognized by the capital market as the core driver. By sacrificing centralization for execution efficiency and closed-sourcing for commercial output, seizing this wave of intelligent agent dividends means that Alibaba will use Tokens to replace GMV (Gross Merchandise Volume), thereby acquiring a new valuation benchmark.

In the meantime, Alibaba must ensure that the Tongyi model maintains its leading position in complex task capabilities, with sustained popularity in intelligent agent demand, a soaring willingness to pay among B-end customers, and the next wave of AI boom not arriving too soon. Within this limited window of opportunity, Alibaba must race against the clock.