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News3 min read·2026-10-21DisconfirmAI Editorial

Shu Junliang of Qwen Office: The Battleground for Enterprise AI is Customer Choice; Context Should Be an Independent Infrastructure

In an interview during the Yunqi Conference, Shu Junliang, head of Alibaba's newly integrated Qwen Office, stated that the real competition in enterprise AI lies in customer adoption rather than product volume. He argued that context should not be locked into a single product but serve as an independent data infrastructure owned by the enterprise. Furthermore, he highlighted that the fundamental difference between enterprise agents and personal assistants lies in identity, permissions, auditing, and accountability.

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Original publication time 2026-09-27 16:38 GMT+8

During the September 2026 Yunqi Conference, Shu Junliang, head of "Qwen Office"—Alibaba's newly consolidated AI office brand—gave a group interview addressing the fierce competition among global tech giants in enterprise office scenarios. Shu presented several core judgments regarding the implementation of enterprise-level AI. He argued that although underlying technologies and user needs are changing rapidly, the true battleground at this stage is not product volume, but the actual choice and depth of use by enterprise customers.

Regarding Alibaba's strategic move to integrate teams like QoderWork and DingTalk Wukong into Qwen Office, Shu confirmed that internal efforts are converging toward a unified capability outlet. However, he emphasized that Qwen Office should not be defined as a fixed desktop agent or entry point, but as a capability system. In relation to traditional office software like DingTalk, the two are not simply replacing each other but undergoing bidirectional integration: DingTalk's accumulated data assets and business logic will serve as the foundation, while Qwen Office provides stronger natural language interaction and generalization capabilities. Whether they eventually merge into a single product will be determined by user demand and industry evolution.

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On the technical architecture level, Shu proposed a key viewpoint: "Context should follow the subject, not a specific Agent product." He believes that enterprise context should become a data infrastructure independent of specific applications, belonging to the enterprise itself. This means that whether an enterprise chooses to develop its own AI or procure other products in the future, it should be able to derive capabilities from this unified context. This decoupled design aims to solve the problem of data silos between different AI tools, allowing context to become a universal digital asset for enterprises, much like a database.

Additionally, Shu analyzed the essential differences between enterprise-level Agents and personal assistants. He pointed out that personal assistants typically represent the user themselves, with operations under individual control. Once an Agent enters organizational processes, it must answer questions such as "Who brought it in," "What can it access," and "Who is responsible if something goes wrong." Therefore, identity, permissions, data ownership, auditing, and responsibility constitute the basic requirements for enterprise AI. In terms of product implementation, Qwen Office emphasizes pre-defined boundaries, execution within sandboxes, manual confirmation for high-risk operations, and post-auditing to meet enterprise security and compliance needs.

Although full-stack AI capabilities are seen as Alibaba's phased advantage, Shu remained cautious, acknowledging that competition has just begun and no fundamental differentiation exists yet. He admitted that while pay-for-results is the ideal direction, it is difficult to standardize measurement in enterprise scenarios. Current pricing models are more a result of the industrial stage; as software homogenization alleviates, the scarcity customers are willing to pay for will shift from pure model costs to truly differentiated software design and functionality.

Sources

  • 原始出处geekpark.net↗
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