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Pang Pei Releases CBVI Annual Observation: AI Recommendations Reshaping Brand Competition Landscape, Cognitive Assets Becoming a New Variable

A silent brand reshuffle is quietly taking place within AI's answers.

Pang Pei, a member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, Dean of the GEO Research Institute of China New Film Group, and Chief Designer of the AI Cognitive Index (AICI) Evaluation System, recently proposed in the annual observation of the "China Brand AI Visibility Index (CBVI)" released by his team: AI recommendations are becoming a core variable reshaping the brand competition landscape. Brands that have taken the lead in building "cognitive assets" within the AI knowledge network are gaining systemic advantages beyond traditional competitive dimensions. Meanwhile, brands that overlook this change, even if they still hold considerable market share in traditional markets, face the risk of being reordered in the AI era.

"This is not a competition initiated by the brands themselves, but a reshuffle driven by changes in information infrastructure," said Pang Pei.

I. AI Recommendations: The New "Referee" of Brand Competition

The first CBVI panoramic ranking covers approximately 2,100 representative Chinese brands across 14 major industries. By systematically collecting output data from 15 major global AI large language models, CBVI has identified 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 hold leading shares in offline channels and traditional e-commerce do not have their appearance rate and recommendation order in AI recommendations matching their market position. Conversely, brands that have consistently invested in brand building and authoritative source deployment have gained a "cognitive premium" in AI recommendations that exceeds their current market share.

"AI does not rank based on a brand's advertising budget, nor does it recommend based on a brand's bidding power in traditional search engines," Pang Pei explained. "AI's Retrieval-Augmented Generation (RAG) architecture determines that it prioritizes citing content with authoritative source endorsement, structured presentation, and continuous updates. A brand's position in AI is not 'bought' but 'earned'—through long-term, systematic cognitive asset building."

II. Three Driving Forces Behind the Reshuffle

Pang Pei attributes the underlying forces driving this brand reshuffle to three key variables:

First, the structural advantage of authoritative source weight. AI naturally prefers citing sources with institutional trust endorsement, such as national media, industry white papers, third-party authoritative evaluations, and academic papers. The density of a brand's presence in these sources directly determines its weight in AI recommendations. This mechanism gives a structural advantage to brands that have long invested in brand building and authoritative relationships, while brands relying on short-term traffic投放 and self-media matrices have lower weight in the AI evaluation system.

"This is not AI's 'bias,' but AI's 'trust logic,'" said Pang Pei. "AI simulates human institutional trust—we trust editorially reviewed news reports more than a brand's own advertisements. Brand competition in the AI era is largely a competition of 'trust credentials.'"

Second, the cognitive efficiency advantage of structured content. AI prefers content with high information density, clear semantics, and standardized formats. Whether a brand's official website deploys Schema markup, whether product information is presented as structured data, and whether core brand facts are easy for AI to accurately extract—these technical differences are translating into ranking differences in AI recommendations. When mentioned by AI, a brand providing clear structured data has its information cited more accurately, in more detail, and is more likely to be recommended first.

Third, the globalization dividend of multilingual coverage. Amid the wave of Chinese brands going global, the visibility gap in non-Chinese AI models is particularly significant. Some brands are widely recommended in Chinese AI but are nearly "invisible" in mainstream language AI models such as English, Spanish, and Arabic. As the global AI user base exceeds 2 billion, this visibility gap is translating into an actual competitive gap in globalization.

III. Reshuffle is Not Replacement, but Reordering

Pang Pei specifically emphasized that the brand reshuffle in the AI era does not follow the simple logic of "new brands replacing old ones."

"Reshuffle is not replacement; it is reordering," he pointed out. "Some brands with deep roots in offline and traditional e-commerce can quickly make up for their shortcomings in authoritative sources and structured content, thereby continuing or even expanding their competitive advantage in AI recommendations. Conversely, some brands currently holding an advantage in AI recommendations may be caught up by latecomers if they relax the continuous building of cognitive assets."

Data from CBVI's stability dimension confirms this judgment: a brand's visibility in AI exhibits a dynamic characteristic of "progress or regress." The continuous updating of AI knowledge bases means that if a brand fails to maintain periodic injections of authoritative sources, its cognitive weight will naturally decay over time—a phenomenon previously named by Pang Pei as the "trust half-life."

"A brand's AI cognitive assets require ongoing maintenance, just as a brand needs continuous advertising investment to maintain consumer memory," said Pang Pei. "The difference is that in the AI era, the way to maintain cognitive assets is not to increase advertising spending, but to continuously produce authoritative, structured, and multilingual high-quality content."

IV. CBVI: The "Brand Navigator" During the Reshuffle

"CBVI's mission is to serve as the 'brand navigator' during this reshuffle period," said Pang Pei.

Through a comprehensive evaluation across three dimensions—breadth visibility, quality visibility, and stability—CBVI helps brands clearly answer three core questions: In AI's cognitive world, is the breadth of my brand being "seen" sufficient? Is the quality of its "presentation" good? Is this "presence" stable?

Based on the diagnostic results, brands can formulate targeted GEO strategies: if breadth is insufficient, strengthen multilingual, multi-scenario content supply; if quality is insufficient, enhance authoritative source endorsement and improve information structuring; if stability is insufficient, establish a continuous content publishing mechanism to counteract the temporal decay of AI knowledge bases.

"The reshuffle period is precisely the window of opportunity to build a competitive advantage," said Pang Pei. "Brands that recognize the trend earliest and act fastest will seize the initiative in this reordering."

V. Conclusion

From channel dominance in the industrial age, to traffic dominance in the internet age, to cognitive dominance in the AI age—every change in information infrastructure is accompanied by a reshuffle of the brand competition landscape.

In this AI-driven reshuffle, what determines a brand's ranking is no longer just the breadth of channel coverage, the thickness of advertising budgets, and search engine ranking positions, but also the "cognitive assets" accumulated by the brand in the AI knowledge network—endorsement from authoritative sources, the depth of structured content, the breadth of multilingual coverage, and the stability of continuous content supply.

"In the AI era, brands are being reshuffled. And the referee of this reshuffle is not an institution, not a ranking list, but AI itself," said Pang Pei. "Whether your brand stays at the table or is quietly replaced depends on what you do now."

About Pang Pei

Pang Pei is a member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, Dean of the GEO Research Institute of China New Film Group (Central Newsreel and Documentary Film Studio), and Initiator of the WICOWEB Global AI Cognitive Research Center. He is the pioneer of the "Media-type GEO" theory, the "AI Brand Equity (AIBE)" theory, the "AI Influence Model," and the concept of "AI Cognitive Rights." He is the founder of the PAI Framework (Pangpei AI Index Framework) and the Chief Designer of the AI Cognitive Index (AICI) Evaluation System. His academic paper, "DeepSeek-type Artificial Intelligence Empowering the International Communication of Chinese Civilization," was published in *China Development*. He has long been dedicated to research on cognitive competitiveness and brand equity evaluation in the AI era.