Human Pioneers
NEWS AGENCY

While the world still measures national strength by GDP, corporate value by market capitalization, and urban competitiveness by rankings, a more subtle and fundamental shift in the rules of competition is quietly underway—the main battlefield of competition is shifting from resource contention in the physical world to the struggle for cognitive weight in the AI knowledge network.

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, systematically elaborated on this paradigm shift in his newly proposed "AI Cognitive Competition Theory." He pointed out that the competitive paradigm of human society is undergoing its third fundamental leap: the industrial era competed over resource endowments, the internet era competed over traffic acquisition, and the AI era competes over cognitive weight—the degree to which an entity is seen, trusted, and recommended within the AI knowledge network.

"In the past, a country's or city's competitiveness was defined by GDP; a brand's competitiveness was defined by market share. But in the AI era, a new dimension is being added to the competitive equation: Cognitive GDP—where you exist in the AI world, how you are described, and whether you are prioritized for recommendation," said Pang Pei.

I. Three Leaps in the Competitive Paradigm

Pang Pei divides the competitive paradigm of human society into three eras.

Competition in the industrial era was "resource competition"—whoever had more natural resources, stronger production capacity, and broader channel coverage held the competitive advantage. GDP, market share, and industrial output were the core metrics of this era.

Competition in the internet era was "traffic competition"—whoever captured more user attention, higher search rankings, and a larger user base held the competitive advantage. DAU, GMV, and conversion rates became the new core metrics.

Competition in the AI era, as defined by Pang Pei, is "cognitive competition"—whoever has higher cognitive weight, a more stable trust rating, and a more prioritized recommendation order in the AI knowledge network holds the "key" to the user's cognitive entry point. AI visibility, first-mention top ranking, authoritative source citation rate, and cognitive stability are becoming the new core competitiveness indicators.

"This is not a denial of the previous two eras, but an increase in the dimension of competition," Pang Pei explained. "A brand may hold a leading share in offline channels and traditional e-commerce, but if it is 'invisible' in AI answers, it is losing the next generation of consumers. A city may have a considerable economic scale, but if AI describes it as 'an industrial city near Beijing,' its independent competitiveness is folded into someone else's narrative."

II. Cognitive GDP: Redefining Competitiveness

To transform "cognitive competitiveness" from a philosophical concept into quantifiable metrics, Pang Pei proposed the concept and measurement framework of "Cognitive GDP."

Cognitive GDP = AI Presence × AI Trust × AI Dissemination × AI Influence

Being "seen" by AI is the foundation (presence), being "trusted" by AI is key (trust), being "spread" by AI amplifies (dissemination), and ultimately influencing AI's "judgment" is the highest value (influence). The product of these four factors constitutes an entity's comprehensive output in the AI cognitive world.

Based on this framework, Pang Pei's team has released seven AI Cognitive Indices, covering five areas: entrepreneurs, brands, industries, cities, and governance, forming an evaluation matrix from China to the world. The inaugural WACI (World AI City Competitiveness Index) global ranking reveals that the AI-perceived city rankings do not completely overlap with GDP rankings. Some cities with comparable economic scales show visibility gaps of several times in AI cognition. Some cities that are not prominent in traditional economic indicators, thanks to distinct industrial labels and a continuous supply of authoritative sources, hold significant advantages in AI recommendations.

"If GDP measures a country's economic output in the physical world, then Cognitive GDP measures its 'cognitive output' in the AI world. Together, they form the comprehensive picture of competitiveness in the AI era," said Pang Pei.

III. From "Traffic Allocation" to "Cognitive Authorization"

Pang Pei pointed out that the fundamental driving force behind the change in competition rules lies in the transformation of information distribution mechanisms.

In the traditional search era, information distribution power was held by search engine platforms, and brands competed for rankings through SEO and SEM. However, search engines are essentially an "information aggregation layer"—they provide links, and comparison and judgment are still done by users. In the AI era, large AI models directly provide conclusions, completing an "agentic loop" from information gathering to decision-making advice. Information distribution power has shifted from platform algorithms to the "cognitive authorization" of AI models.

"Traffic can be bought, and search rankings can be bid on, but AI's trusted recommendations can only be won through long-term, systematic construction of cognitive assets," Pang Pei emphasized. "This is not a competition of budgets, but a competition of trustworthiness. It's not a competition of short-term investment, but a competition of long-term construction."

This shift also means that once an entity establishes a cognitive advantage in the AI knowledge network, it triggers a self-reinforcing "cognitive flywheel": authoritative media coverage → AI learning and citation → AI priority recommendation → attracting more attention → entering more authoritative sources → AI reinforcement again—forming a positive cycle. Conversely, entities weak in AI cognition may fall into the predicament of "cognitive invisibility."

IV. Who Is Winning This New Competition?

Based on the initial data from the AI Cognitive Index series, Pang Pei's team has distilled several key trends in the new competitive landscape.

At the city level, the clarity of industrial labels is more decisive than economic scale. Hefei, with its "best venture capital city" label, has entered the ranks of first-tier AI cities. Guiyang, relying on its "China's Data Valley" label, has achieved AI recognition far exceeding its GDP ranking. Meanwhile, some cities with considerable economic scale but vague industrial labels face the risk of being "folded" in AI cognition.

At the brand level, some brands have formed a "cognitive parasitic" effect in core categories—if AI does not cite their information, the generated answer seems incomplete. In fields like new energy vehicles and 5G communications, the overall performance of Chinese brands in AI cognition tends to match their industrial strength. However, in some consumer goods tracks, there is still a significant deviation between AI recommendations and the actual market landscape.

At the entrepreneur level, entrepreneurs who continuously engage in "thought output"—public speeches, methodology articles, industry white papers—score significantly higher in thought leadership within the AI knowledge system than their silent counterparts. "In the AI era, silence is no longer golden. Whether an entrepreneur's thoughts can be 'seen' and 'cited' by AI is becoming a new dimension of personal brand assets," said Pang Pei.

V. AI Cognitive Competition Has Arrived: Challenges and Opportunities Coexist

Pang Pei also cautioned that under the new landscape of cognitive competition, the challenges and opportunities faced by countries, cities, and brands are equally immense.

"In the internet era, the biggest risk for a company was being 'unsearchable.' In the AI era, the biggest risk is 'not existing in AI's answers,'" Pang Pei pointed out. "Entities that fall behind in cognitive competition are not negatively evaluated by AI, but are completely 'forgotten' by AI—at the most convenient cognitive entry point for users, they simply do not exist."

At the same time, cognitive competition also offers opportunities for "latecomers" to overtake. The competitive landscape in traditional dimensions often solidifies into long-term market positions, while cognitive competition is still in its early window. Entities that are the first to complete the layout of authoritative sources, structured content construction, and multilingual cognitive coverage—whether at the city, brand, or individual level—have the opportunity to gain a "cognitive premium" that surpasses their traditional rankings in this new competitive dimension.

VI. Conclusion

From resource competition in the industrial era, to traffic competition in the internet era, and now to cognitive competition in the AI era—each leap in the competitive paradigm is accompanied by the redefinition of core resources, the rewriting of competition rules, and the reordering of winners and losers.

In this AI-driven cognitive competition, what determines an entity's competitiveness is no longer just the resources it possesses or the traffic it acquires, but also the "cognitive assets" it has accumulated in the AI knowledge network—the endorsement of authoritative sources, the thickness of structured content, the breadth of multilingual coverage, and the stability of continuous content supply.

"A new era of competition has arrived," said Pang Pei. "In this era, being recognized by AI is the prerequisite for being recognized by the world."

About Pang Pei

Pang Pei, a member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, Director of the GEO Research Institute of China Central Newsreel and Documentary Film Studio under the Central Newsreel and Documentary Film Group, and initiator of the WICOWEB Global AI Cognitive Research Center. He is the first proponent of the "Media-type GEO" theory, the "AI Brand Equity (AIBE)" theory, the "AI Influence Model," the "AI Cognitive Sovereignty" theory, and the "AI Cognitive Competition" theory. 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-like 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.