On September 4, QBitAI reported that Alibaba's Qwen Work passed 30 million users in its first month, with enterprise users accounting for more than half. Behind that number is a quiet shift: the AI search gateway is moving beyond consumer Q&A into office decision-making. Procurement, vendor selection, solution comparison and supplier searches increasingly happen inside AI office platforms. For brands, a new set of decision entrances has appeared: when an employee asks Qwen Work "which website agency is reliable" or "how do I choose a GEO optimization provider," whether the brand gets cited directly affects where new leads come from.
Why Qwen Work is a new brand gateway
Qwen Work is Alibaba's one-stop AI productivity platform, integrating documents, spreadsheets, meetings and knowledge bases. The fact that enterprise users account for more than half is the key signal: questions in office scenarios carry commercial intent. Unlike casual consumer queries, typical office questions are "compare X and Y," "find a vendor" or "cite evidence for a proposal" — the decision chain is shorter and conversion value is higher.
QuestMobile's 2026 AI Application Market Semi-Annual Report (June 2026 data, trending on Weibo on 09-08) shows Doubao with 382 million MAU, Qwen with 167 million and DeepSeek with 129 million. Qwen's push into the office track (Qwen Work plus Tongyi) is steadily raising its weight in enterprise knowledge-type queries, forming a dual-gateway landscape with Doubao Work's Feishu ecosystem (for the Agent strategy of Doubao Work, see Doubao Work enterprise Agent GEO guide).
How office AI platforms cite brands: content must answer
Office AI platforms generate answers the same way: retrieve trustworthy sources, then organize them into an answer. The difference is that office scenarios strongly prefer structured, verifiable, parameter-rich content. Compare the content preferences across the three gateways:
| Dimension | Qwen Work | Doubao Work (Feishu) | Traditional search |
|---|---|---|---|
| Typical questions | Comparison, vendor recommendation | Internal collaboration, task execution | General keyword queries |
| Source preference | Websites, documents, industry reports | Enterprise knowledge bases, Feishu docs | All web pages |
| Content form | Solution pages, FAQ, parameter tables | Structured docs, process descriptions | Long articles, list pages |
| Brand opportunity | Recommended as "the solution" | Invoked by agents | Higher ranking |
| Optimization focus | Authority and readability | Machine-readable, consistent messaging | Keywords and backlinks |
The core requirement for brands: the website and public content must directly answer procurement-level office questions — pricing ranges, service processes, delivery timelines, cases and credentials. When this information is structured as FAQ, tables and parameter pages, AI can extract and cite it easily (see structured data and LLM inclusion).
A 3-step GEO playbook for enterprise AI office scenarios
Step 1: Inventory high-frequency office questions. From a buyer's perspective, list 10-20 questions people would ask an AI: how to choose a website agency, how fast GEO optimization works, how much mini-program development costs, what cases the provider has. These questions are your content retrofit checklist (methodology in the GEO optimization starter guide).
Step 2: Structure the answers. Turn each question into an answer unit AI can extract: website FAQ, service process pages, pricing-range pages, case pages. Three things matter: consistent messaging (numbers, credentials and contact info unified across pages), verifiable evidence (certificates, cases, media coverage), and freshness (office users trust the latest information).
Step 3: Monitor and iterate across engines. Qwen Work, Doubao, DeepSeek and Yuanbao have different source preferences (see AI engine source preference comparison). Test 5-10 core procurement terms monthly on the main engines, record brand mention rate and cited sources, and fix the largest gaps first. Qwen itself iterates fast — re-check content performance within 48 hours of engine updates (latest at GEO strategy after Qwen3.8-Max).
FAQ
Are Qwen Work and Tongyi Qianwen the same thing? No. Tongyi Qianwen is the consumer AI assistant app; Qwen Work is a one-stop productivity platform for office scenarios. Both share the Qwen model foundation but differ in scenario, source preference and user structure.
What does "enterprise users over half" mean? It means office-scenario questions (selection, procurement, solution comparison) carry a large share, and these have clear commercial intent — a brand cited by AI in such answers has a higher chance of converting into a sales lead.
Should brands optimize specifically for Qwen Work? Treat Qwen Work as an enterprise-level gateway within the overall GEO system rather than a separate effort: first structure the website FAQ, parameter pages and case pages so any AI office platform can read and invoke them.
Does office-scenario GEO conflict with traditional SEO? No, they complement each other. SEO covers search ranking; GEO covers AI citation. Content assets (FAQ, cases, parameters) serve both — start with content structuring and both entrances benefit.
Is enterprise office GEO expensive for SMBs? The core cost is content restructuring, not advertising. Complete FAQ and parameter-page structuring first, then add authoritative sources and run monthly monitoring — a small team can do it.
This article was written by the Zheming Digital Communication Research Institute. Data updated to 2026.
Need GEO layout for enterprise AI office scenarios? Shanghai Zheming provides multi-engine GEO optimization for Qwen Work, Doubao and DeepSeek, starting with a brand AI mention-rate audit. Tel +86 18917757529 ｜ Email jaysun@widesight.cn.