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Pang Pei Releases Global and China Brand AI Visibility Index: The Existence Domain of Brand Equity Is Extending from Consumer Minds to AI Knowledge Networks

For half a century, the iron law of marketing has remained unshaken—brand equity exists in the minds of consumers. From Aaker's brand equity five-star model to Keller's CBBE theory, all classic theories share a fundamental premise: humans are the sole subjects of brand awareness formation and association generation.

However, when 2 billion users worldwide begin asking AI large models questions like "Recommend a good domestic skincare product" or "Which brand of new energy vehicle is the safest," this iron law is quietly being rewritten. Pang Pei, a member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, Director of the China Vision New Image GEO Research Institute, and Chief Designer of the AI Cognitive Index (AICI) evaluation system, points out: "In the AI era, brand equity exists not only in users' minds but also in AI's knowledge networks. How a brand is described in AI, whether it is trusted, and whether it is prioritized in recommendations—these are becoming new dimensions of brand equity."

Based on this judgment, Pang Pei's team has officially released the "China Brand AI Visibility Index (CBVI:2026)" and the "World Brand AI Visibility Index (WBVI:2026)." The former covers approximately 2,100 representative Chinese brands across 14 major industries, while the latter covers 800 representative global brands. Both indices rely solely on real output data from 15 mainstream AI large models worldwide, providing systematic quantitative assessments of brand AI cognitive assets from three dimensions: breadth visibility, quality visibility, and stability.

I. The "Second Existence Domain" of Brand Equity

In his previously proposed "AI Brand Equity Theory (AIBE)," Pang Pei systematically argued for the first time the dualization of brand equity's existence domain. Traditional brand equity exists in consumer minds—composed of brand awareness, brand associations, and brand loyalty. In the AI era, brand equity simultaneously exists in the knowledge networks of AI large models—composed of AI visibility, AI trustworthiness, and AI recommendation strength.

"These two domains are not substitutes but overlays," Pang Pei explains. "A brand may have a strong cognitive foundation in consumer minds, but if this cognition does not enter the knowledge network in an AI-understandable and trustworthy manner, it may be marginalized in AI recommendations. Conversely, some emerging brands with limited investment in traditional brand building have gained a 'cognitive premium' beyond their traditional brand equity through systematic authoritative source deployment and structured content creation."

The initial data from CBVI confirms this judgment. In multiple consumer goods categories, some brands that hold leading shares in offline channels and traditional e-commerce have a much lower appearance rate in AI recommendations than their market share. In sectors like new energy vehicles and 5G communications, brands that have consistently invested in authoritative source building and structured content supply are gaining visibility in the AI cognitive world that exceeds their current market share.

II. How to Measure New Assets?

How to quantify a brand's "presence" in AI knowledge networks? Pang Pei's team's answer is three-dimensional measurement.

Breadth Visibility measures the frequency and scope of a brand being mentioned across multiple models, languages, and scenarios. It answers the question: "How broad is the range of AI seeing the brand?"—is it only occasionally mentioned in Chinese AI models, or widely presented in global multilingual AI?

Quality Visibility measures the accuracy of information, recommendation priority, and depth of authoritative source citations when a brand is mentioned by AI. It answers: "How well is the brand presented by AI?"—is it accurately described and prioritized, or vaguely mentioned with potential information errors?

Stability measures the sustainability and risk resistance of a brand's AI visibility over time and across different model environments. It answers: "How reliable is the brand's AI presence?"—is it as stable as a rock, or does it fluctuate significantly with model updates?

"These three dimensions together form the 'cognitive balance sheet' of a brand in the AI era," says Pang Pei. "Just as a financial balance sheet reflects a company's financial health, the AI cognitive balance sheet reflects a brand's cognitive competitiveness in the AI era."

III. From China to the World: A Panoramic Map of Brand AI Visibility

As the global extension of CBVI, WBVI achieves for the first time cross-cultural and cross-lingual comparisons of brand AI visibility. The initial edition covers 800 representative global brands across eight major industries: technology, automotive, consumer goods, luxury goods, finance, pharmaceuticals, energy, and industrial manufacturing. Data collection spans 70 languages, including Chinese, English, French, Spanish, Arabic, Japanese, and Korean.

"One of the challenges for Chinese brands going global is the lack of 'presence' on the global AI cognitive map," notes Pang Pei. "Preliminary data from WBVI shows that a considerable number of Chinese brands are widely recommended in Chinese AI models but are nearly 'invisible' in internationally mainstream languages such as English, Spanish, and Arabic. This 'language gap' is becoming a hidden barrier to brand globalization."

To address this, Pang Pei's team integrates CBVI, WBVI, and the GEO100 certification standard into a three-in-one evaluation matrix: GEO100 provides graded certification of a single brand's AI cognitive assets, CBVI offers a panoramic view of brand AI visibility in the Chinese market, and WBVI provides a cross-cultural comparison benchmark for global brands. Three tools, one methodology, with a consistent lineage.

IV. New Propositions for Brand Equity Building

Pang Pei believes that the dualization of brand equity's existence domain presents three new propositions for brand managers.

First, brands need to build assets in both domains simultaneously. Traditional brand building revolves around consumer minds—advertising, experience, word-of-mouth. In the AI era, brands also need to focus on AI knowledge networks—authoritative source deployment, structured content creation, multilingual coverage. "This is not an either-or choice but a dual-track approach," Pang Pei emphasizes.

Second, brand assets in the two domains may not be synchronized. A brand with high awareness in consumer minds does not necessarily have high visibility and recommendation strength in AI knowledge networks. The gap between the two constitutes the brand's "cognitive disparity." One of the missions of CBVI and WBVI is to help brands identify and narrow this gap.

Third, AI brand assets have a different accumulation logic from traditional brand assets. Traditional brand assets accumulate through advertising frequency and consumption experience, exhibiting a linear "input equals output" characteristic. AI brand assets accumulate through authoritative source endorsement and structured content creation, exhibiting a nonlinear "input-flywheel effect-sustained returns" characteristic. Pang Pei calls this the "cognitive flywheel" for brands in the AI era: authoritative source endorsement → AI learning and citation → AI priority recommendation → attracting more attention → entering more authoritative sources → AI reinforcement again.

V. Conclusion

From consumer minds to AI knowledge networks, the existence domain of brand equity is undergoing the most profound expansion in half a century.

In this expansion, the classic theories of brand equity born in the industrial age have not been negated—they still explain the value of brands in consumers' minds. But a new dimension is being added to the definition of brand equity: a brand's presence, trustworthiness, and recommendation strength in the AI world. The AI Cognitive Index series is providing a measurement benchmark for this new dimension.

"Future brand equity will not only exist in users' minds," says Pang Pei. "It will also exist in AI's answers. Being seen by AI is a prerequisite for being chosen by users; being trusted by AI is a shortcut to winning user trust."