China’s Alibaba shifts towards revenue over open-source AI
Move may affect a global developer community that relies on Qwen models from the Chinese company
Zhou Jingren, left, was brought in to lead AI model training by Alibaba chief executive Eddie Wu, right © FT montage/Getty Images
Chinese tech giant Alibaba has brought in a business veteran to lead its AI division as part of a strategic shift towards models it can monetise.
Zhou Jingren, the former chief technology officer of Alibaba Cloud, has taken control after internal disagreements over strategy led to the departure of senior figures from its flagship Qwen team, according to two people with knowledge of the matter and a memo sent to staff.
Qwen is one of the most popular open-source options so Alibaba’s focus on models it can monetise may affect AI development worldwide. Meta has made a similar shift of focus away from its Llama open-source models.
“The market dynamics are evolving,” said Brian Wong, a former Alibaba executive and author of
The Tao of Alibaba. “If you’re only building models and relying on APIs or open-source ecosystems, you’re going to be in a difficult position.”
The moves reflect a growing consensus across the industry that, with value shifting to AI applications such as coding and agents, simply building powerful models is not enough to succeed.
Alibaba currently generates the bulk of its AI-related cloud revenue from leasing out graphics processing units (GPUs) to customers. But it is now seeking to capture a greater share of spending by offering its proprietary models and integrating AI tools across its ecommerce ecosystem.
Chief executive Eddie Wu said in last month’s earnings call that its nascent “model-as-a-service” would become a key driver in the cloud division.
MaaS, where companies pay based on usage of AI models, currently accounts for only a small share of Alibaba’s cloud revenue and remains low margin due to intense competition.
Wu last month announced the formation of the Alibaba Token Hub, a business unit combining its model training team and enterprise and consumer applications under a single structure designed to accelerate commercialisation.
The internal shake-up — which includes a new leadership committee on AI strategy headed by Wu — comes as Alibaba faces
rising competition from ByteDance, the creator of TikTok.
ByteDance has shaped its cloud sales strategy around the consumption of “tokens”, the units of data processed by AI models.
The rapid rise of “agentic” AI systems, which are capable of executing multi-step tasks and independently planning with limited human supervision, requires far more computing resources than traditional chatbot queries and is driving a surge in
token consumption.
Duncan Clark, founder of consultancy BDA, said Alibaba’s pivot amounted to “an attempt to reposition itself as the ‘Google of China’ — anchoring its business around cloud infrastructure, proprietary models and in-house chips”.
“Monetisation from models is small and low margin for now,” Clark said. “But rising use of agentic AI is providing supportive momentum.”
The shift comes amid a broader change in investor sentiment, as enthusiasm for model performance gives way to scrutiny over returns.
Many investors now believe advances in large language models are becoming incremental, while the real opportunity lies in embedding them into products that drive sustained usage and revenue.
Among those who have left Alibaba are Lin Junyang, Qwen’s former technical lead, and Hui Binyuan, a researcher focused on coding. Lin was a leading proponent of Qwen’s open-source approach, offering free, downloadable models that run efficiently on devices at low cost.
The strategy won strong support from the global developer community and positioned Alibaba as a leader in China’s open-source AI push.
However, it also raised concerns internally about the lack of a clear path to commercialisation, according to several people familiar with the matter. Those concerns intensified as investor focus shifted from benchmark performance to monetisation.
Lin had come under increasing pressure from senior management about the large resources being spent training open-source models, particularly after rival Chinese labs — including MiniMax, Zhipu and Moonshot — released new models around the lunar new year that outperformed Qwen in coding, a fast-growing area of AI demand.
“Junyang’s team was too focused on benchmark rankings and open source, which doesn’t provide value for the cloud business,” said a person familiar with Alibaba’s strategy.
They added that Zhou would prioritise aligning model development with the company’s cloud and revenue goals. Alibaba has already released a flurry of closed-source models this month, keeping its leading models proprietary for customers accessing them through its cloud business.
The person added that Alibaba planned to continue releasing advanced open-source models in some areas.
Earlier this week a popular, new open-source AI video generation model called Happy Horse was released anonymously, but was developed by Alibaba, according to the person.
One Alipay AI engineer who has worked with Zhou described the executive as “highly technical” and well-positioned to redirect its training efforts.
“People have been carried away by Qwen’s reputation and academic success. But Jingren is capable and in control of the team, with support from Alibaba leadership,” said the person familiar with Alibaba’s strategy.
Alibaba declined to comment.
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