Human Pioneers
NEWS AGENCY

When a user opens an AI application and asks in natural language, "Recommend a new energy vehicle suitable for a family," a turning point in an era is occurring—not keyword spelling in a search box, not pay-per-click rankings on search results pages, but one or several recommended answers directly provided by AI.

Pang Pei, a member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, Dean of the Zhongshi Xinying GEO Research Institute, and Chief Designer of the AI Cognitive Index (AICI) Evaluation System, believes that this shift in interaction mode is heralding the end of one era and the beginning of another. "The search era is being replaced by the AI recommendation era. This is not a technological upgrade, but a fundamental rewriting of the rules of competition."

I. The Rules of the Search Era Are Becoming Obsolete

In the search era, brand competition revolved around a set of established rules: optimizing keywords, improving search rankings, purchasing pay-per-click ads, and converting click traffic. The underlying logic of this system was—users actively search, search engines provide a list of links, and brands compete for visibility and click-through rates within that list.

But in the AI era, users no longer browse through lists of links; they directly receive answers. AI completes an "agentic loop" from information gathering to decision-making: it handles the entire process of searching, filtering, comparing, and judging for the user, outputting only a few recommended results.

"In the search era, a brand might rank lower but still exist, and users could find you by flipping through a few pages," Pang Pei pointed out. "In the AI era, answers only push a few options. If you're not in the recommendation list, it's as if you don't exist in the most accessible cognitive entry point for users."

The core of this shift lies in the transfer of information distribution rights. In the search era, information distribution rights were held by search engine platforms, and brands competed for rankings through SEO and SEM. In the AI era, information distribution rights have shifted to the "cognitive authorization" of AI models—AI decides who gets recommended and who gets ignored. And the basis for AI's decision is not a brand's advertising budget, but its "trust weight" within the network of authoritative sources.

II. Brands in the Eyes of AI: New Rules Are Already in Effect

The inaugural panoramic list of the "China Brand AI Visibility Index (CBVI)," developed under Pang Pei's leadership, covers approximately 2,100 representative Chinese brands across 14 major industries. Based on standardized data collection from 15 mainstream global AI large models, CBVI reveals an accelerating trend: there is a significant deviation between a brand's visibility ranking in AI answers and its traditional market share ranking.

In several consumer goods categories, some brands that lead in sales through offline channels and traditional e-commerce have a much lower appearance rate in AI recommendations than their market share would suggest. Conversely, a group of brands that have consistently invested in building authoritative sources and providing structured content are gaining a "cognitive premium" in the AI cognitive world that exceeds their current market share.

"AI doesn't sort by advertising budget, nor does it rank by search bidding," Pang Pei explained. "AI's Retrieval-Augmented Generation architecture determines that it prioritizes citing content that has authoritative source endorsement, structured presentation, and continuous updates. This means a brand's position in AI is not 'bought,' but 'earned'—through long-term, systematic cognitive asset building."

The initial data from CBVI reveals a clear landscape: a few brands have formed a "cognitive parasitism" effect in core categories—if AI doesn't cite information from these brands, the generated answer feels incomplete. These brands are not only widely mentioned but are also cited as industry benchmarks. A large number of brands, however, are in a state of "insufficient AI presence"—their mention rate in mainstream AI models is low, and they rarely appear in priority positions for recommendation-type questions.

"What needs the most vigilance is not being negatively evaluated, but being forgotten," Pang Pei said. "Brands may still be operating normally in the real world, but in the cognitive world of AI, they are being 'covered' by competitors. This process is subtle—you can't see that AI didn't recommend you; you only know that traffic from AI channels is quietly declining."

III. The Essence of the New Rules: From "Highest Bidder Wins" to "Most Trusted Wins"

Pang Pei attributes the change in brand competition rules to a core judgment: the competitive logic has shifted from "highest bidder wins" to "most trusted wins."

In the search era, pay-per-click rankings allowed brands with sufficient budgets to purchase better display positions. Brands could invest short-term, see immediate results, and adjust at any time. Competition was immediate and reversible. In the AI era, the core path for a brand to gain AI recommendations is to establish a systematic presence within the network of authoritative sources—accumulating "trust assets" through in-depth reports from national media, publication of industry white papers, citations from third-party authoritative evaluations, and references in academic papers. This path is highly path-dependent, difficult to replicate in the short term, and accumulates over the long term.

"This is not a competition of budgets, but a competition of trust qualifications. It's not a competition of short-term investment, but a competition of long-term construction," Pang Pei emphasized.

From a technical perspective, this shift stems from the RAG (Retrieval-Augmented Generation) architecture commonly adopted by large AI models. When generating answers, AI prioritizes retrieving high-weight source fragments from external knowledge bases for synthesis. Sources with institutional trust endorsement—national news agencies, official government websites, peer-reviewed academic journals—naturally have higher retrieval weights. A brand's self-claims and commercial advertisements face the risk of being down-weighted due to AI's mechanism for identifying commercial intent.

"AI isn't biased; it's simulating human institutional trust," Pang Pei said. "We trust editorially reviewed news reports more than a brand's own advertisements. A brand's competition in the AI era is essentially about vying for this 'qualification to be trusted by AI.'"

IV. From "Managing Traffic" to "Managing Cognitive Assets"

Faced with the change in competition rules, Pang Pei advises brand managers to undergo a fundamental shift in thinking: from "managing traffic" to "managing cognitive assets."

In the search era, the core work for brands was managing traffic—optimizing keywords, improving conversion rates, calculating ROI. In the AI era, brands need to simultaneously manage "cognitive assets"—establishing a systematic presence in authoritative sources, adding structured markup to core information, building visibility in multilingual AI models, and countering the "trust half-life" with a continuous supply of content.

"The fundamental difference between cognitive assets and traffic assets is: traffic is one-time, disappearing after a click; cognitive assets are continuously effective, generating returns with every AI recommendation," Pang Pei stated. "An in-depth report about a brand in an authoritative media outlet is not buying a single exposure, but making a deposit in a 'cognitive bank'—this deposit will continuously accrue interest in every future related query."

Based on this philosophy, Pang Pei's team is upgrading the AI Cognitive Index series from an evaluation tool to a management tool. CBVI not only tells a brand "where it ranks in AI," but also "why it ranks there" and "what it should do"—through diagnostics across three dimensions: breadth visibility, quality visibility, and stability, brands can formulate targeted cognitive asset building strategies.

V. Conclusion

From search to recommendation, from ranking to trust, from traffic to cognition—these three "from...to..." shifts outline the complete picture of brand competition entering the AI era.

The search era hasn't truly "ended," but it is no longer the only game in town. In an era where AI recommendations increasingly dominate the entry point for consumer decisions, the rules of brand competition are being rewritten. Those brands that first understand the new rules and complete their cognitive asset layout the fastest will seize the advantage in this rule change.

"The search era taught brands how to be found; the AI era will teach brands how to be trusted," Pang Pei said. "These are two completely different propositions, requiring two completely different capabilities."