Produced by | Yiguan Finance

Author | Xuanye Baixue

In early 2026, when Alphabet, Google's parent company, witnessed its market value soar close to $4 trillion and surpass Apple, claiming the title of the world's second-most valuable publicly traded company, the market sent out a resounding signal—AI has not 'rendered search obsolete.' Instead, it has propelled search back to the forefront of the tech-business ecosystem. This latest round of valuation re-assessment is not driven by a singular technological breakthrough but rather by the capital market's tangible investment in 'AI's reshaping of the fundamental value proposition of online marketing.'

Following the explosion of ChatGPT and general-purpose large language models, debates about whether 'AI will make search engines redundant' once dominated the tech community. However, for secondary market investors, the focus has never been on abstract technical discussions but on a more pragmatic concern: If search engines no longer rely on clicks as their primary revenue generator, how will the business logic of online marketing evolve? What will platforms depend on for scalable monetization? Will advertising, the cornerstone of their revenue, be diminished or transformed?

Alphabet's market valuation trajectory offers a compelling real-world answer. Behind the façade of 'zero-click searches' and 'answers as a service,' search engines have not lost their commercial relevance. Instead, they are evolving from mere traffic distributors into super gateways that seamlessly connect user intent, content, services, and transactions. This transformation is also reshaping the product design and monetization strategies of Chinese platforms such as Baidu, Weibo, and Xiaohongshu. Amidst this evolution, opportunities and risks coexist, with quarterly financial reports gradually revealing the final outcomes.

01

Search and Marketing in the AI Era: A Paradigm Shift

As users transition from simple, short keywords to complex, natural language queries, click-through rates (CTRs) have indeed shown a declining trend.

Multiple research institutions and media outlets have reported that AI-generated automatic answers have led many users to forgo clicking on traditional search result links, resulting in a significant drop in traffic for content publishers. Some studies suggest that click-through recommendations for news websites have decreased by 10% to 25%, with certain content types experiencing even steeper declines. Industry analysts argue that search engines' direct provision of answers reduces user clicks on web links, thereby diminishing traffic to external websites.

Observing user behavior reveals a shift towards more multi-round and in-depth searches. User queries have evolved from short keywords (3-4 words) to multi-round, long-form questions (20-60 words or more), characterized by clearer intent and more specific expressions, enabling AI to better understand latent needs. Users have transitioned from passive clicking to active interaction, with tools like Wenxin Assistant, Google AI Search, and Weibo Intelligent Search transforming search and content presentation into dialogue-like experiences. User habits have shifted from pure information retrieval to problem-solving, content creation, and decision support.

Under traditional search logic, a user clicking a link marked the starting point of behavioral value and the anchor of advertising value.

However, with the rise of ChatGPT and general-purpose large language models, user behavior and information acquisition methods in search have undergone a fundamental transformation. Users now prefer directly asking AI questions, reducing their reliance on traditional search clicks. AI's advanced capabilities in answer generation and content integration have weakened the monetization model based on 'keywords and static ads.'

In the AI era, users prioritize 'directly obtaining conclusions or actionable plans.' Search is no longer just a gateway but an 'intelligent engine' that understands user intent and plans subsequent steps. This underlying behavioral shift means the traditional 'keyword-link-click-conversion' chain is being redefined.

02

Insights from Google's AI Search

To understand the impact of this transformation on business models, let's examine the performance of Google, the global industry leader. Financial data from Alphabet, Google's parent company, in 2025 provides a vivid illustration.

In the first quarter of fiscal year 2025, Alphabet reported revenue of approximately $90.23 billion, up about 12% year-over-year, with net profit reaching $34.54 billion, up about 46% year-over-year. Search and advertising remained the core revenue drivers. During the earnings call, it was disclosed that revenue from search advertising and related businesses grew by a double-digit percentage year-over-year. The AI Overviews feature boasted over 1.5 billion monthly active users, significantly boosting overall search engagement and query depth.

In the second quarter of 2025, Alphabet reported total revenue of approximately $96.4 billion, up about 14% year-over-year, with advertising continuing its strong growth trajectory. Google Search & Other revenue reached approximately $54.1 billion, maintaining healthy growth, while YouTube advertising revenue hit about $9.8 billion. These two segments constituted the main forces behind advertising monetization.

CEO Sundar Pichai emphasized during the earnings call that AI features like AI Overviews and AI Mode not only enhanced user satisfaction but also increased search query volume and actively drove steady growth in advertising revenue. AI Overviews' monthly active users surpassed 2 billion, while AI Mode had over 100 million monthly active users across multiple markets.

Delving deeper, in the third quarter of 2025, Alphabet delivered one of its strongest financial reports ever: quarterly revenue exceeded $102.3 billion for the first time, up about 16% year-over-year, with net profit nearing $35 billion. Google Search and advertising remained the core drivers, growing by a double-digit percentage. The U.S. stock market reacted positively, reflecting investor recognition of Google's AI business commercialization.

These data points underscore two key investment insights:

First, AI has not eroded the fundamental commercial value of search advertising. Instead, by improving user intent understanding and ad targeting precision, it helps advertisers achieve higher-quality traffic and conversion efficiency.

Second, Google's resilience in advertising and monetization has not been weakened by competitors like OpenAI. Instead, it has gradually absorbed this technological shock through product innovation.

The essence of this trend is not merely the continuation of 'old advertising models.' AI has made search scenarios more complex and diverse, with advertising shifting from simple keyword matching to semantic-level intent matching.

For example, when a user asks an AI search in natural language, 'I want to plan a budget and itinerary for a short European trip next month,' this query reveals numerous segmented intents, allowing advertisers to match users' commercial needs at a more granular level rather than just competing for keyword positions. The core value of this mechanism lies not in forcibly maintaining click volumes but in replacing single-click metrics with higher per-behavior conversion value.

03

The New Business Logic of AI in China

For traditional Chinese search companies, this transformation is particularly pivotal. Enterprises like Baidu and 360, which rely on online marketing as their primary revenue source, initially felt the pain of model transformation during the early AI era. Especially between 2023 and 2024, when large language models became the preferred gateway for users to acquire knowledge and decision-making advice, the traditional 'keyword advertising matrix' indeed encountered a 'decline in click-through effects.'

Rather than being overwhelmed by change, it's better to embrace it.

However, Baidu's strategy was not to cling to outdated models but to proactively integrate search with services, consultations, and conversion closures. It aimed to reconstruct AI search pages into a commercial scenario that seamlessly integrated information, tools, services, and interaction, transforming advertising from static displays into 'native commercial nodes' that help users solve specific tasks.

This transformation may indeed lower some traditional metrics in the short term, but it brings higher commercial value through more efficient user services and steadier ad conversions. This is particularly significant in investors' eyes: clicks are no longer the sole value carrier; conversion efficiency and depth of intent understanding are the sources of long-term cash flow. In the AI era, if a platform can accurately parse user intent at the early stages of demand generation and naturally embed commercial services during the resolution process, this monetization approach is more sustainable than simply competing for ad positions.

In the third quarter of 2025, Baidu disclosed for the first time in its financial report that revenue from AI-native marketing services reached 2.8 billion yuan, surging by 262% year-over-year. It explicitly identified this business segment as one of the key drivers of company growth, indicating that AI elements have moved from experimental stages to commercialization and become one of the revenue growth poles.

On the other hand, content community platforms like Weibo and Xiaohongshu derive their value more from user emotional connections and content influence. While AI can summarize information and provide suggestions, it cannot replace human experiences, emotional resonance, and social trust mechanisms. For brands, capturing a potential need through AI search is the first step in gaining user attention; however, enabling users to complete validation, identification, and even exclusive cognition within communities is the subsequent step influencing purchasing decisions. Therefore, after users find answers through AI dialogue, they often rely on community content to confirm contexts, compare experiences, and obtain personalized advice.

This explains why the commercial value of content communities does not disappear with the rise of AI. Instead, during the AI-triggered 'demand anticipation' phase, content communities become crucial nodes for receiving traffic, enhancing brand awareness, and boosting user stickiness. For advertisers, this means the marketing value of content communities is shifting from 'reliance on exposure' to 'situational influence,' with content quality, interaction, and trust becoming key factors determining commercial conversion efficiency.

04

Beyond Clicks: The New Logic of Online Marketing

In summary, AI has not ended the value of search or content platforms. What has truly been 'rendered obsolete' is the myth of clicks as the sole indicator of value. Clicks were once seen as the core metric for measuring user attention and advertising value, but in the AI era, they are being replaced by a more complex and deeper value logic. This new logic emphasizes precise understanding of user intent, timely intervention in commercial behaviors, and continuous improvement of conversion efficiency.

Google's robust financial data proves the resilience of advertising models in the AI era. Baidu demonstrates possible paths for search commercialization through product and ecosystem reconstruction, while content community platforms reinforce their core value in influencing user behavior. For investors, what truly matters is not mere traffic metrics but whether platforms can build service chains from 'user demand generation' to 'commercial behavior closure' in the AI era and whether these chains can stably generate long-term cash flow.

In this new ecosystem, rather than asking whether AI will kill clicks, it's better to ask: Who can build new, valuable commercial closures beyond clicks? Platforms and companies that can answer this question represent the true long-term investment opportunities in the AI-era online marketing landscape.