From Wuzhao to Zhou Jingren: Alibaba Has the Best AI and the Hardest Execution. The One Thing It Lacks Is Judgment
Let’s get the facts straight first. On June 13, word went around online that Alibaba Chief Scientist Zhou Jingren was leaving, six days after he was moved into the title. The next day Alibaba responded that this was a rumor. So as of right now, Zhou Jingren has not left. It’s only a rumor.
But the fact that so many people believed it within a single day is itself a piece of information. It says that in everyone’s gut, Alibaba’s AI team feels unstable right now, the kind of place people walk out of. And that gut feeling has hard facts underneath it.
A roster that keeps emptying out
This year, Tongyi’s core people have left one after another. In March, Qwen tech lead Lin Junyang departed with a single line: “me stepping down. bye my beloved qwen.” Right behind him, the post-training lead and several core members left too. Zhou Jingren himself changed roles three times this year: he took over Qwen in March, became Chief AI Architect in April, and on June 8 was moved again to Chief Scientist, assigned to run a future-facing research institute. Six days later, the departure rumor arrived.
Pull the camera back a little. On June 11, Wuzhao had just been pushed out of DingTalk.
Within one week, Alibaba’s two most-watched AI lines, the technical one and the product one, both had a personnel earthquake. The two events look unrelated, one a scientist, one a product manager, but set side by side they happen to expose Alibaba’s deepest problem right now.
It has everything, except judgment
The strangest thing here is that Alibaba is short on neither technology nor execution.
On technology, Tongyi Qwen is one of the most capable large models in China, open-sourced, topping benchmarks, used by developers worldwide. Calling it the face of Chinese AI isn’t a stretch. On execution, Wuzhao’s whole regime of nine-o’clock clock-ins, midnight spot checks, and cots on the office floor is the extreme end of Chinese internet execution culture. One hand holds the best model, the other holds the strongest execution. On paper that’s an unbeatable hand.
The result is the opposite. The technical people are leaving, and the product captain has been replaced. Two aces in hand, and at the table they keep losing ground.
Why? Because the AI era is repricing everything. Technology and execution happen to be exactly the two things this era is devaluing, while judgment is the only thing appreciating, and the one thing Alibaba lacks most.
Models are converging. Lead by three months today, and the moment something is open-sourced, others catch up. The technical moat keeps getting shallower. Execution is even clearer: AI has driven the cost of execution into the floor. Writing code, building apps, launching a new entry point, all of it depends less and less on throwing bodies and overtime at the problem. The two things Alibaba is proudest of are being diluted by open source and replaced by AI respectively.
The missing square in the middle is judgment: holding a model this good, what product do you build, for whom, so that people use it and don’t leave. Tongyi can’t fill that square, because it’s a technical team. Wuzhao can’t fill it either, because what he’s good at is taking something already decided and executing it to the limit, not deciding the thing.
Strategy and tactics, wrong in the same spot
Split Alibaba’s AI play into strategy and tactics, and you find both layers are wrong in the same place.
On strategy, Alibaba’s AI story is “we’ll build the strongest model and become the new entry point of the AI era.” Model-driven plus entry-point thinking is an elegant, and very typical, mobile-internet playbook: seize the technical high ground first, then the traffic gateway, and the applications will follow on their own. The trouble is that in the AI era entry points are no longer scarce, every model is an entry point, and the technical high ground can’t be held, because open source makes any lead temporary. This strategy answers “what kind of AI do we want to build” but skips the more dangerous question: what problem of the user’s own does the user take this AI to solve. Qwen is strong, but “strong” isn’t a reason a user needs you.
On tactics, Alibaba’s answer is to adjust faster, harder, and more often. Wuzhao launched DingTalk ONE in four months and dismantled it ten months later. Zhou Jingren changed roles three times in a year. After the core exits, Tongyi quickly stood up a new group, with senior group leadership stepping in to backfill personally. Every move shows astonishing organizational efficiency and execution. But when the direction itself hasn’t been thought through, the more efficient the execution, the faster it carries you somewhere unverified. Swapping leaders constantly isn’t solving the problem. It’s using personnel turbulence to paper over the absence of judgment.
Alibaba’s strategy is betting on technology and entry points; its tactics are racing on speed and execution. But in the AI era both are devaluing, and it has pushed all its chips onto assets that are shrinking.
Judgment
Wuzhao and Zhou Jingren, one the extreme of execution, one the peak of technology. Within a single week, one is out and one is rumored to be leaving. These aren’t two isolated personnel changes. They’re the same signal flashing twice: Alibaba has spent all its strength on the two things this era is least short of.
What it needs isn’t a stronger model or harder execution. It’s a kind of judgment: above the model and before the execution, working out who exactly to bring all that skill to bear for, and to solve what. You can’t fill that by poaching a scientist, and you can’t solve it by swapping in an iron-fisted CEO. It has to grow in the brains at the very top of the organization.
China is not short on the best AI technology. Alibaba is the proof. What’s genuinely scarce is the judgment, sitting between the best technology and the hardest execution, to call the shot and call it right. Whoever fills that square first is the one who has actually entered the AI era.
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