The tech world in June has been anything but calm.
A couple of days ago, Alibaba rolled out its third wave of AI organizational restructuring since 2026. This time, however, it wasn't a minor personnel shuffle. Instead, it directly merged two key AI teams—the Tongyi Large Model Division and the Future Life Lab—to form a brand new division called Token Foundry. Group CEO Eddie Wu Yongming is personally leading this new division.
Meanwhile, Zhou Jingren, the architect behind Alibaba's Qwen system, officially took up the role of Group Chief Scientist to spearhead the establishment of Alibaba's AI Future Research Institute. Zheng Bo, the former head of the Future Life Lab, led star product teams like HappyHorse and HappyOyster to be fully integrated into the new division.
As soon as the news broke, the entire industry began discussing the same question: what is Alibaba's game plan this time?
Just over three months ago, Alibaba established the Alibaba Token Hub (ATH) business group, also personally led by CEO Eddie Wu, bringing together AI-related units like the Tongyi Lab, the MaaS business line, the Qwen Division, the Wukong Division, and the AI Innovation Division under a unified organizational framework. Two months ago, he further set up a Group Technology Committee, serving as its head himself.
The signals from the previous two moves were already clear: to reduce coordination costs between different business lines and form organizational synergy around AI.
Now, with the Token Foundry division being established just a few months later, it means Alibaba's AI strategy has shifted from the "resource integration" phase to fully entering the "accelerated implementation" phase.
The Ambition of the “Token Factory”
The name Token Foundry is quite interesting. The word "Foundry" literally means a factory for casting metals. Combined with "Token," it becomes even more intriguing. Alibaba seems to be positioning itself as a "Token factory," aiming to become a foundational supplier in the AI era.
This aligns with Alibaba's strategic orientation. Back in March, when Alibaba established the ATH business group, an internal logical goal was set: "Create Tokens, Deliver Tokens, Apply Tokens." The establishment of Token Foundry now appears to be an extension and deepening of this logic.
Looking at the changes in organizational structure, before the merger, the Tongyi Large Model Division was responsible for underlying model R&D, while the Future Life Lab focused on AI scenario exploration. They were two separate teams with different reporting lines and directions, both aiming at the same overarching goal but inevitably facing coordination costs.
The Future Life Lab was previously under the Taotian Group and later moved to the newly formed ATH business group, originally tasked with exploring AI applications. The Tongyi Large Model Division was also engaged in similar work—for instance, developing video generation models, with the latest version, Wanxiang 2.7, released this year. Operating separately led to resource duplication and potential internal competition. The merger, in theory, could concentrate resources on the "most critical battlefields" and avoid fragmented efforts.
An industry insider commented to the media that the advent of the Agent era brings obvious organizational changes: For developing chatbots, the model team can operate somewhat independently from the business. But for creating Agents capable of autonomously executing workflows, the model team must understand business logic, data flows, and decision-making chains.
Another easily overlooked but noteworthy detail is that Zheng Bo led projects like HappyHorse and HappyOyster into the Token Foundry division.
The name HappyHorse actually sparked discussions in the AI community back in April. It anonymously topped the global authoritative AI blind testing platform ArtificialAnalysis in both text-to-video and image-to-video tracks, drawing significant industry attention due to its performance.
The fact that a product from the Future Life Lab could suddenly emerge and achieve world-class results indicates that Alibaba internally possesses "good stuff." The question is whether such products can be consistently produced and systematically brought to market. The integration of Zheng Bo's team suggests Alibaba intends to embed this capability into a larger framework.
Of course, whether organizational adjustments can truly resolve coordination issues remains to be seen. The merger is just the first step; subsequent cultural integration, process streamlining, and goal alignment are the real challenges. Putting two departments together is easy, but making them truly produce a chemical reaction is difficult.
Thus, Alibaba's AI organizational structure has become quite clear: The ATH business group serves as the top-level framework coordinating all AI businesses; the Token Foundry division handles model R&D and commercialization; the AI Future Research Institute focuses on frontier technology exploration; the MaaS business line builds the model-as-a-service platform; the Qwen Division develops C-end personal AI assistants; and the Wukong Division creates B-end AI-native work platforms.
This four-tier structure of "Research Institute - Foundation Models - Service Platform - Application Products" ensures both long-term technological innovation capability and meets short-term commercialization needs. Eddie Wu has built an organizational machine for Alibaba's AI that can operate efficiently, accomplishing this in just three months.
Zhou Jingren's Pivot: What Is Alibaba Thinking?
Another noteworthy role change in this restructuring is that of Zhou Jingren.
A key figure in Alibaba's Tongyi large model team, Zhou formerly served as Chief Scientist of Alibaba Cloud, responsible for data intelligence businesses like search, recommendation, and advertising for Alibaba Cloud, Taobao, and Alipay. At the end of 2022, he became Alibaba Cloud Intelligence CTO while also serving as Deputy Dean of Alibaba's AI team DAMO Academy and Head of the Tongyi Lab. He built the Tongyi large model team from scratch, driving the Qwen series models from 0 to 1 and ultimately positioning them in the global first tier.
The recently released Qwen-3.7 model achieved a global top-three, domestic number-one ranking in coding capability, gaining widespread recognition in the developer community and among industry clients. In 2025, Zhou Jingren became an Alibaba Partner, the first CTO-level executive to enter the highest decision-making body with a purely technical background.
In this latest shift to Group Chief Scientist, Zhou will no longer be responsible for specific business management tasks. Instead, he will devote himself entirely to researching cutting-edge AI technologies.
Chief Scientist is the highest academic title within Alibaba's technology system. Zhou only entered the Alibaba Partnership last year. Gaining the highest academic title in less than a year is a promotion pace worth pondering. Alibaba clearly hopes he can "travel light," freeing himself from specific business management to focus on longer-term technological challenges.
Such arrangements are not uncommon in the industry. OpenAI has its Superalignment team, and Anthropic has its own Frontier Research division. When large model technology reaches a certain stage, it becomes necessary for individuals to be liberated from the pressures of daily product iterations and commercialization to focus on longer-term technological breakthroughs.
This organizational design also reflects a layout strategy for Alibaba: one hand grasps the present, the other the future. The Token Foundry division is responsible for productization and commercialization, closely monitored by the CEO; the AI Future Research Institute focuses on frontier exploration, led by the Chief Scientist for fundamental research.
These two lines advance side-by-side, ensuring that the business doesn't fall behind in technological iterations nor loses long-term competitiveness by excessively chasing short-term gains.
Zhou Jingren previously offered a clear perspective on the development trend of large models: "Large models are undergoing a core paradigm shift, from aligning with human preferences to aligning with task objectives. In the past, we pursued models that 'speak well'; now we demand models that 'get things done.'"
Shifting from "good-looking metrics" to "reliable execution"—such an adjustment in philosophy might better represent Alibaba's true stance.
Regarding the future research directions of the AI Future Research Institute, official information is currently scarce. However, judging from Zhou Jingren's previous technical assessments, capabilities like autonomous planning, continuous iteration, and cross-tool collaboration—so-called Agent capabilities—might be a key focus.
Zhou previously explicitly stated that with the leap in capabilities of the Qwen-3.7 series models, Alibaba is working to make models truly become the intelligent core of Agents.
A “Organizational Race” is Unfolding Among Tech Giants
Looking across the entire industry, one finds that Alibaba's adjustments are not an isolated case. Over the past two years, nearly all top AI companies have undergone similar organizational restructurings, with remarkably similar steps.
Prior to this, Google merged its decade-old Brain team with DeepMind to form Google DeepMind, unified under the leadership of Demis Hassabis and reporting directly to CEO Sundar Pichai. Early last year, Google went further, consolidating all AI engineering groups scattered across product lines under DeepMind, completely achieving a unified AI organization.
On Microsoft's side, in 2026, it restructured its Copilot team, creating a new Executive Vice President role reporting directly to CEO Satya Nadella, with the same goal of shortening the decision-making chain. Meta restructured its AI organization four times within six months in 2025, with the core direction being to bridge the gap between the FAIR Lab and product AI teams. Between 2025 and 2026, Amazon merged its AGI team, in-house chip team, and quantum computing team into a unified organization, connecting the entire chain from infrastructure to model R&D.
Behind these moves, three common patterns emerge: First, AI is moving from "independent lab operation" to "deep integration with business." Second, reporting relationships are being elevated from VP-level to direct reporting to the CEO or President. Third, models, infrastructure, and products are no longer under different command systems but are integrated into the same operational unit.
Therefore, looking back at Alibaba's recent move, the establishment of the Token Foundry division is essentially following this global trend. The difference is that Alibaba has completed this intensive progression from ATH to Token Foundry in just a few months. This pace is the fastest among domestic internet giants.
In practical terms, any organizational adjustment must eventually translate into business. Behind Alibaba's sweeping consolidation of AI businesses lies a key timeline: In May, Alibaba Group Chairman Joe Tsai and CEO Eddie Wu jointly issued a letter to shareholders, announcing that Alibaba's AI business has crossed the initial investment phase and officially entered the commercialization return cycle.
In other words, AI within Alibaba needs to gradually shoulder the responsibility of "increasing revenue." Financial reports show that in the fourth quarter of fiscal year 2026, Alibaba Cloud's external commercialization revenue growth accelerated to 40%, with AI-related product revenue achieving triple-digit growth for the eleventh consecutive quarter.
Eddie Wu revealed a more specific number during the earnings call: The annual recurring revenue (ARR) for AI models and application services, including the Bailian MaaS platform, is expected to exceed RMB 10 billion in the June quarter and surpass RMB 30 billion by year-end.
He also mentioned that API demand on the Bailian platform has grown over tenfold in the past half-year, "We hardly have a single empty card in our servers; there are still many customers waiting in line." In the fiercely competitive AI landscape, this state of supply shortage represents a significant competitive advantage.
Alibaba recently released its latest Qwen-3.7 model, which ranked fifth globally and first domestically in the ArtificialAnalysis Large Model Intelligence Leaderboard, gaining widespread recognition in the developer community and among industry clients.
Of course, it's also important to recognize that while the commercialization data is impressive, competitive pressure is not insignificant compared to peers. Taking the MaaS (Model-as-a-Service) field as an example, Volcano Engine raised its MaaS target for this year from RMB 10 billion to RMB 15 billion. Liu Weiguang, Senior Vice President of Alibaba Cloud Intelligence Group, also stated that he has given the sales team a mandate: the proportion of MaaS revenue per customer must not be less than 20% by year-end.
The battle in the MaaS arena is becoming exceptionally intense, and the establishment of the Token Foundry division is, to some extent, a new move by Alibaba at the MaaS card table.
Taking a longer-term view, Alibaba's actions in the AI field this year can be described as "high-frequency." The dense pace reflects the reality that: The window of opportunity in the AI industry is rapidly narrowing.
In 2026, the fervor around the parameter race is gradually cooling, replaced by comprehensive competition in engineering capabilities, commercialization levels, and ecosystem completeness. ByteDance's Doubao boasts a daily active user (DAU) count exceeding 200 million, and Tencent's Hunyuan Hy3 Preview is being scaled in products like CodeBuddy, WorkBuddy, and Yuanbao.
It's worth mentioning that Alibaba's mention in its shareholder letter this year that "AI business has crossed the initial investment phase and officially entered the commercialization return cycle" coincided almost simultaneously with ByteDance's announcement that Doubao would begin paid subscriptions. Leading players entering the commercialization fast lane at the same time signifies that competition based purely on technological and product innovation is transforming into a three-pronged race involving technology, products, and commercialization.
The establishment of the Token Foundry division can be seen as a strategic move by Alibaba at this critical juncture: it contains both long-term planning for the future and an urgent response to the immediate present.
This article is from the WeChat public account "New Eyes" (ID: xinmouls), author: Li Xiaodong
