After finding profits, Zhihu faces new questions from AI onslaught

The online knowledge community operator briefly achieved profitability in the first half of this year, but that momentum didn’t carry into the third quarter

Key Takeaways:

• Zhihu reported its revenue fell 22% year-on-year in the third quarter, as it slipped back into the red after finding profits earlier this year
• The operator of a knowledge-sharing community, often called the “Quora of China,” said its paid membership revenue for the quarter dropped 16% year-on-year

Lee Shih Ta

Generative AI is reshaping the global content industry at an astonishing pace. For short-video platforms, the technology is rapidly eliminating content-creation barriers, paving the way for explosive growth as just about anyone can create compelling content. For search engines and text-and-image social platforms, AI is also making information retrieval faster and more interactive, significantly amplifying their user attractiveness.

Yet the very same AI wave is also creating major headaches for some traditional content platforms. One of those is Zhihu Inc. (ZH.US; 2390.HK), often called the “Quora of China,” which is renowned for its high-quality knowledge-sharing community. Paradoxically, the even more omniscient power of AI is undermining the company’s existing business model, forcing it to search for a new strategic footing.

According to its latest financial report, released last week, Zhihu’s revenue tumbled 22% year-on-year to 660 million yuan ($120 million) in the third quarter from 850 million yuan a year earlier. All three of the company’s main revenue streams declined. Advertising and marketing services revenue dropped 26% to 189 million yuan; paid membership slid 16% to 385 million yuan; and “other revenue,” including its once-promising vocational training services, fell over 30% to 83.92 million yuan from 129 million yuan.

The weak showing continued a losing streak from the first half of the year, when Zhihu’s revenue dropped 23.7%. Its revenue for all last year also decreased by 14.3%.

Despite those troubles, Zhihu had finally found a formula for profitability after reporting years of losses. But it slipped back into the red in the third quarter, ending a winning streak of three consecutive quarters in the black. It reported a net loss of 46.65 million yuan for the latest period, more than quadrupling from a 10.49 million yuan loss a year earlier. Its gross margin during the latest period also fell 2.6 percentage points to 61.3%.

The weak third quarter brought Zhihu’s revenue for the first nine months of this year to 2.11 billion yuan, down 23% year-on-year. It recorded a net profit of 15.7 million yuan, compared to a net loss of 260 million yuan in the same period last year.

Hemorrhaging users

The latest earnings report offered no specific reason for the wide-ranging revenue declines, which in some ways is fueling concerns about the stability of its business.

Zhihu’s most touted assets – its “high-quality answers” and “in-depth knowledge sharing” – are coming under siege from AI large language models (LLM). Users traditionally visited Zhihu to search for curated knowledge and experiences, seeking quality responses from experts and people with real-world experience. But AI models can deliver similarly high-quality, structured answers within seconds that incorporate vast amounts of content and offer diverse perspectives, making Zhihu look increasingly replaceable.

As users grow accustomed to querying AI directly, Zhihu’s crucial entry-point traffic is being siphoned off, reflected by its user metrics. By the end of the third quarter, Zhihu’s average monthly subscribing members totaled 14.3 million, down 13.3% from 16.5 million a year earlier. In 2024, its average monthly active users (MAU) also declined 21.2% year-on-year. The company ceased reporting MAU figures starting this year.

AI + social as a breakout strategy?

Founder Zhou Yuan hasn’t downplayed AI’s impact on content platforms, giving his views in multiple interviews. He contends that as knowledge becomes easier to access, “trust, expert networks and genuine engagement” will grow scarcer in the AI era. As that happens, he envisions Zhihu evolving into a dual-pronged medium for “information + trust,” leveraging its community for diverse perspectives to become the “trusted information infrastructure” of the AI age.

While the concept isn’t inherently flawed, it could struggle to reverse the existing business model’s weakness in the near term. Payment incentives on Zhihu lean toward the functional rather than being linked to boosting social value or identity. Its advertising context is less defined than short-video platforms, and embedding commercial content within knowledge-centric text faces inherent limitations. Unless the new social dimension Zhou envisions can translate clearly into measurable income, the strategy is unlikely to stem the company’s near-term revenue slide.

In the latter half of last year, Zhihu launched Zhihu Zhida, an AI-powered feature generating answers to user queries by synthesizing its own content and web data, offering both concise and in-depth responses. At the same time, it also introduced a knowledge base subscription product emphasizing traceable content sources to boost credibility. But such features can only offer limited differentiation from the rapidly evolving capabilities of general AI models, failing to provide a compelling reason for why people should use Zhihu instead. Consequently, those initiatives haven’t yielded significant or sustained growth in traffic or paid users since their launches.

Zhihu’s Hong Kong-listed shares fell over 8% on the day after the release of the latest earnings report. The stock has shed roughly 7% over the last six months, even as many other China tech stocks have rallied, reflecting pessimism about the company’s near-term outlook. Valuation-wise, Zhihu’s Hong Kong-listed shares trade at a price-to-sales (P/S) ratio of less than 1, lagging Kuaishou’s (1024.HK) 2.1 and Baidu’s (BIDU.US; 9998.HK) 2.2. That signals the market does not see it as an AI beneficiary, but rather as a content company losing momentum during the AI revolution.

Zhihu’s true challenge lies not in finding new technological breakthroughs, but in pinpointing and conveying its unique positioning to build value that isn’t easily replicated in the AI era. Its ability to reignite growth hinges on moving beyond its original “knowledge supply” framework and building a new type of trust that can position it in an irreplaceable niche at the intersection of AI and human capabilities. Only then can it try to translate that new proposition into sustainable commercial value.

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