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Baidu CTO Wang Haifeng says the company's ChatGPT-like Ernie Bot now has 100M+ users, after launching the chatbot to the public in August 2023

Baidu's (9888.HK) ChatGPT-like Ernie Bot has garnered more than 100 million users, chief technology officer of the Chinese internet company Wang Haifeng said on Thursday.

Reuters

Context & Ripple Effects

Baidu positioned Ernie as a strategic response to generative AI early in 2023, first announcing plans to bring it into search and then asserting stronger Chinese-language capabilities in a later model update. The public launch turned that product ambition into a test of consumer adoption.

Crossing 100 million users gives Baidu a meaningful distribution base for an assistant product, rather than leaving Ernie as a search feature proposal. It also provides a benchmark for the subsequent report of 200 million-plus users and enterprise adoption.

First-order effects

  • Baidu can point to 100 million-plus Ernie users as evidence that its public chatbot rollout has reached mass-market scale.
  • A larger active user base gives Baidu more interaction data and a broader audience for future Ernie integrations, following its earlier plan to add the service to search.

Second-order effects

  • Chinese AI competitors face a clearer adoption benchmark: model claims alone are less persuasive when Baidu can cite a large public user base.
  • Ernie's scale increases the commercial importance of integrating generative AI into Baidu's existing services; later coverage said the chatbot had begun augmenting the ads business.

Third-order effects

  • If large Chinese internet platforms can convert chatbot launches into sustained usage, AI assistants may become a distribution layer embedded in search and other consumer services rather than a standalone novelty.
  • The lasting competitive question shifts from initial user counts to retention, model quality, and whether assistant traffic can support enterprise and advertising businesses.

The trend: Chinese internet platforms are racing to turn foundation models into mass-distribution assistant layers tied to their existing consumer services.