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Baidu triples revenue target for its office agent

ARR for the corporate version of Baidu Dazi grew several times over month on month for two months running. Management has raised the annual target to three to five times its original level.

BusinessNewsDr. Amara PatelPublished: 25 September 20265 min readSources 2
Baidu triples revenue target for its office agent

Baidu Dazi, an AI agent built for office work, surprised its own creators. Jiemian News reported that ARR for the corporate version grew several times over month on month in July and August. Management revised the annual revenue target more than once. The latest figure is three to five times higher than the plan set at the start of the year.

The product launched in March 2026 and comes in two subscription tiers, personal and corporate. AI Newsletter's July 2026 ranking put monthly active users at 6.74 million, up 1,064 percent month over month. That is second place among office agents and first in growth rate.

Product director Li Jingqiu describes a clear split in demand. Technology, finance and manufacturing companies bring in the most revenue. Energy, public administration and transport show strong willingness to buy and are growing fastest this year. Education and retail chains have plenty of use cases, but their purchases depend on a measurable return on investment.

What Baidu is not doing right now is more interesting. People the outlet spoke to say management is not pushing hard on revenue targets or user growth. It cares instead about the agent's execution layer and whether a multi-step task gets carried through to the end. Internally, Baidu positions Dazi as the entry point to its services in the agent era. It integrates search, maps, the encyclopedia and analytics tools, and is meant eventually to connect outside developers' tools as well.

Competition is not standing still. Within a year Alibaba, ByteDance and Tencent all launched their own office products, and their interfaces look increasingly alike. Competition is therefore moving beyond the product itself, to how well complex tasks are executed and to the ecosystem around the platform. Alibaba opened a developer platform for its Workbuddy in September, letting companies bring in their own systems and industry skills.

DeepSeek offers a useful comparison. It monetises its model through a subscription for developers, and after it raised API prices its annual revenue passed a billion dollars. Baidu is taking a different route, selling a subscription for a ready-made workstation rather than access to tokens.

The difference between the subscription model and per-token billing is fundamental. With tokens, revenue grows with the number of calls, but so does the cost of serving responses, and the client sees a bill every time its employees use the tool. With a subscription, the provider carries the usage risk and sells an outcome, not a resource. That is more convenient for the buyer and harder for the seller, because it requires predicting how much work the agent will actually do. The high pace of ARR growth shows that for now corporate clients are leaning towards the second model.

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Sources

2
  1. 01【独家】百度搭子上调年度收入目标ZH
  2. 02曝 DeepSeek 确定 75 亿美元第二轮融资,年化营收突破 10 亿美元ZH

All figures and quotations in this text come from the sources listed below.

Content prepared by the editorial team with AI assistance.

Dr. Amara Patel

Dr. Amara Patel

Economy, business and world

Dr. Amara Patel covers business, world affairs and the economy for FLASH24, working from filings, central bank statements and trade data rather than press releases, and she does not let company spin stand in for numbers. She checks revenue recognition, debt covenants and currency effects line by line against audited reports and regulatory disclosures. Her week includes calls with analysts, logistics operators and trade lawyers, and she watches the calendar for rate decisions, earnings dates and port and freight updates, comparing each against prior quarters. Outside the desk she tracks tech-company accounts and rides cargo bikes, which keeps her close to both the balance sheets she reads and the supply chains she covers. She does not publish a figure she cannot trace to a primary document.

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