Human Pioneers
NEWS AGENCY

While global brand managers are still pouring huge budgets into keyword bidding and search ranking optimization, a more fundamental shift has quietly taken place—users' attention gateway is moving from the blue links of search engines to the direct answers of AI large models. In this transformation, traditional SEO logic is becoming obsolete, and a new paradigm for brand competitiveness is emerging.

Pang Pei, a member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, Dean of the China Vision New Media GEO Research Institute, and Chief Designer of the AI Cognitive Index (AICI) Evaluation System, first proposed the "Media-based GEO" theory in 2024, providing a systematic theoretical framework for brand competitiveness in the AI era. Over the past two years, this theory has evolved from a brand communication strategy into a comprehensive theoretical system covering national cognitive sovereignty, urban cognitive competitiveness, and corporate cognitive asset building.

"From search rankings to AI recommendations, this is not an upgrade of technical tools but a fundamental rewrite of the underlying logic of brand competitiveness," said Pang Pei. "The core question Media-based GEO answers is: In the AI era, how can a brand be trusted and recommended by AI? The answer to this question follows completely different rules from the answer to 'how to be indexed and ranked by search engines' in the search era."

I. Why the Rules of the Search Era Are Failing in the AI Era

In the search era, the core of brand competitiveness was "visibility"—ensuring the brand occupies a prominent position on search results pages through keyword optimization and paid rankings. The underlying logic of this system was: users actively search, search engines provide a list of links, and brands compete for click-through rates within that list. Competition was "ranking competition"—even if a brand ranked lower, it still existed in the search results, and users could find it by flipping through a few more pages.

The AI era has completely changed this logic. When a user asks an AI large model, "Recommend a good domestic skincare product," the AI does not return 10 blue links for the user to compare. Instead, it directly gives one or a few recommended answers, along with reasons and sources. Competition shifts from "ranking competition" to "existence competition"—AI typically recommends only a few options. Brands not on the recommendation list are effectively nonexistent at the most convenient entry point for user cognition.

"In the search era, a lower ranking was a disadvantage. In the AI era, not being recommended means disappearance," Pang Pei pointed out. "And this 'disappearance' is subtle—brands cannot see that AI has not recommended them; they can only see traffic from AI channels quietly declining."

An even more fundamental change lies in the trust mechanism. In the search era, brands built trust in consumers' minds through advertising, experience, and word-of-mouth. In the AI era, the trust path is intermediated—brands first need to establish trust within AI's knowledge network, and then AI "delegates" this trust to consumers. Pang Pei defines this as "trust agency transfer."

"Users no longer trust what the brand says, but what AI recommends and cites," said Pang Pei. "The path for a brand to gain AI recommendations is no longer optimizing keywords or increasing advertising budgets, but establishing a systematic presence within authoritative source networks. This is not a competition of budgets, but a competition of trust credentials."

II. Media-based GEO: Getting Brands into AI's "Trust Circle"

It is based on this insight into the transformation that Pang Pei proposed the "Media-based GEO" theory. Unlike traditional SEO, which emphasizes technical stacking and short-term rankings, Media-based GEO is a top-level strategy focused on long-term brand asset building. Its core proposition is: brands need to establish solid "trust credentials" within AI's knowledge network through authoritative source endorsements and structured content construction, thereby gaining priority citation and recommendation from AI.

"Why does AI trust media more than advertising?" Pang Pei analyzed. "This is not a value judgment but is determined by technical mechanisms. When generating answers, the RAG architecture of AI large models prioritizes retrieving high-weight source fragments from external knowledge bases for synthesis. Sources with institutional trust endorsements—national news agencies, official government websites, peer-reviewed academic journals—naturally have higher retrieval weights. Brands' self-claims and commercial advertisements face the risk of being downgraded due to AI's recognition mechanisms for commercial intent."

The implementation path of Media-based GEO is therefore clear: brands need to establish a systematic presence in high-weight sources such as in-depth reports from authoritative media, industry white papers, citations from third-party authoritative evaluations, and references from academic papers. At the same time, they should add structured data tags to core information to ensure AI can accurately parse it. Continuous content supply is needed to counter the "trust half-life"—if a brand lacks fresh authoritative sources for a long time, its AI cognitive weight will naturally decay over time.

"Media-based GEO is not about managing traffic, but about managing 'cognitive assets,'" said Pang Pei. "An in-depth report by an authoritative media outlet is not about buying one exposure, but about depositing a sum into a 'cognitive bank.' This deposit will continue to generate interest in every future relevant AI query."

III. From Brand Strategy to National Strategy: The Theoretical Evolution of Media-based GEO

After proposing the Media-based GEO theory, Pang Pei continued to advance it into broader dimensions. In 2025, he introduced the "AI Brand Equity Theory (AIBE)," expanding the domain of brand equity from "consumer minds" to "AI knowledge networks." In 2026, he further proposed the "AI Influence Model," systematically demonstrating the deep mechanisms by which AI recommendations become the dominant logic of future influence. In the same year, he put forward the "AI Cognitive Sovereignty Theory," elevating the unit of analysis from brands to countries and cities, arguing for the strategic value of cognitive sovereignty as the highest form of digital sovereignty.

"Media-based GEO is the practical cornerstone of the entire theoretical system," said Pang Pei. "If AI Cognitive Sovereignty answers 'why countries must compete for AI recommendation rights,' and the AI Influence Model answers 'why AI recommends,' then Media-based GEO answers 'how to enter AI's trust circle and win recommendations.' It is the construction blueprint from theory to practice."

Based on this theoretical system, Pang Pei's team has released seven AI cognitive indices covering five major areas—entrepreneurs, brands, industries, cities, and governance—forming a complete loop from evaluation to construction. At the city level, multiple Chinese cities have begun systematic construction of urban AI cognitive competitiveness under the WACI framework. At the brand level, CBVI and WBVI have covered over 2,900 representative brands globally.

IV. The Window of Opportunity Is Narrowing

When asked whether it is too late for brands to start deploying Media-based GEO now, Pang Pei gave a cautious yet urgent response.

"AI cognitive competition is still in its early window period. Brands that take the lead in establishing authoritative source layouts and structured content within AI's knowledge network are gaining a 'cognitive first-mover advantage,'" Pang Pei pointed out. "But the window is narrowing. As more brands realize the value of Media-based GEO, competition will become fiercer. Latecomers will need to put in twice the effort to break through 'cognitive lock-in'—AI has inertia toward cognitive patterns formed early on."

He particularly emphasized that the first-mover advantage in the AI recommendation era is more enduring than in the search era. "In the search era, rankings could be changed at any time through bidding. In the AI era, cognitive weight is built through long-term accumulation of authoritative sources, which latecomers cannot replicate through short-term investment. This means the moat for first movers is deeper than in the search era."

V. Conclusion

From search rankings to AI recommendations, from technical stacking to trust building, from traffic management to cognitive asset management—Media-based GEO represents not just a new methodology for brand building, but a microcosm of the paradigm shift in competitiveness in the AI era.

"The search era taught brands how to be found; the AI era will teach brands how to be trusted," said Pang Pei. "These are two completely different propositions, requiring two completely different capabilities. And Media-based GEO provides a complete theoretical framework and practical path for brand trust building in the AI era."