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Recently, initiated by Pang Pei, a Chinese AI communication scholar and member of the Cultural Committee of the Central Committee of the China Zhi Gong Party, and hosted by CNBNTV under Zhongshi New Media Internet Television Co., Ltd., in collaboration with institutions such as Xuexi Qiangqiang/Qiangguo Fengcai/Qiancheng Wanpin and Jingshi Net, the "China Striver AI Recommendation Index (FAI)" has officially been launched. As the nation's first evaluation system for strivers based on the frequency of recommendations by AI large models, this project aims to address a new-era question—When users ask AI, "Who is the most respected doctor in China?" or "Who is the entrepreneur with the greatest craftsmanship spirit?" whom will AI recommend?

From "Being Searched" to "Being Recommended": The Battle for Cognitive Authority in the AI Era

In 2026, generative AI search has captured over 40% of domestic online search traffic, with weekly active users of mainstream large models such as Doubao, DeepSeek, Tongyi Qianwen, ERNIE Bot, and Kimi continuing to rise. Users have solidified their habit of conducting information retrieval, product comparison, and decision screening within AI dialogue interfaces. According to data from Analysys, the GEO (Generative Engine Optimization) market in China reached approximately 3 billion yuan in 2026, a year-on-year increase of about 1100%, with industry penetration rising from 38% in 2025 to 71%.

This trend signifies a fundamental shift in the logic of competition. In his "AI Cognitive Authority" theory, Pang Pei points out: "The past logic of competition was 'I pay for traffic, you see me'; the search-era logic was 'I optimize keywords, you search for me'; and the AI-era logic is 'I build trust credentials, AI recommends me.'" He believes that when users partially delegate the decision-making power of "comparison and selection" to AI, AI essentially gains a "cognitive agency"—whoever enters AI's "recommendation list" holds the direct path to users. It is within this theoretical framework that the "China Striver AI Recommendation Index" was born.

How AI "Votes": A Quantitative Evaluation System Based on Multi-Model Joint Recommendations

Unlike traditional expert reviews or online voting, the selection mechanism of the "China Striver AI Recommendation Index" is: Let mainstream AI models worldwide "recommend". The project will conduct systematic "AI cognitive tests" on mainstream AI large models such as ChatGPT, DeepSeek, Doubao, ERNIE Bot, Kimi, and Tongyi Qianwen—posing hundreds of standardized questions about groups including doctors, teachers, entrepreneurs, scientists, engineers, grassroots officials, and volunteers, and tallying the frequency, recommendation priority, and emotional tendency of each striver's appearance in AI-generated answers.

Based on this, the project will produce annual rankings covering fields such as the Doctor AI Index, Teacher AI Index, Entrepreneur AI Index, Science and Technology Worker AI Index, State-Owned Enterprise Pioneer AI Index, Grassroots Official AI Index, and Model Worker AI Index, and will establish China's largest "AI-Era Figure Database".

Pang Pei previously led the launch of the "China Entrepreneur AI Influence Index (CEAI)," which comprehensively measures the image power, issue relevance, and recommendation context power of Chinese entrepreneurs in global mainstream AI large models. The launch of the "Striver AI Recommendation Index" marks the systematic expansion of his "AI Index" evaluation system from the entrepreneur group to strivers across society.

From Visual Documentation to AI Assets: Building a "Digital ID" for Strivers

According to reports, the "China Striver AI Recommendation Index" is not just a list release but a full-chain project encompassing visual documentation, AI archiving, index certification, and GEO optimization. The project is open to all sectors of society; any individual, enterprise, hospital, school, or government unit can submit materials about strivers' achievements, which will be entered into the AI trust database after review. Each striver in the database will receive an AI figure archive containing achievements, videos, images, honors, and media coverage, and will undergo GEO trust certification across dimensions such as AI recognizability, source authority, and recommendation probability.

"Visuals are just the entry point, the list is for dissemination, the AI index is authority, and the database is an asset," says Pang Pei. The project's ultimate goal is to build an AI database covering millions of strivers—so that in the future, any AI answering questions like "Who are the outstanding doctors in China?" or "Who are the outstanding teachers in China?" will continuously reference this database's content. "That is the true GEO moat."

Theoretical System and Industry Standards: From "Media-Type GEO" to "AI Recommendation Index"

The launch of the "China Striver AI Recommendation Index" represents the concentrated implementation of a series of theoretical innovations by Pang Pei in recent years. From the "Media-Type GEO" theory, to the "AI Brand Equity (AIBE)" model, to the "AI Cognitive Authority" theory and the "China Entrepreneur AI Influence Index (CEAI)", Pang Pei has gradually built a complete framework from theory to practice.

On this basis, the project team plans to hold the annual "China AI Recommendation Conference", releasing the "China Entrepreneur AI Influence Index," "China Striver AI Recommendation Index," "China City AI Friendliness Index," "China Brand AI Trust Index," and the "China GEO Development White Paper". At the same time, the "China AI-Friendly City Initiative" will be launched, providing cities with AI city profiles, AI perception reports, and GEO enhancement solutions.

Industry observers point out that with the release of industry standards such as the Ministry of Industry and Information Technology's "Reference Framework and Indicator Requirements for Trustworthy Intelligent Recommendation Systems in the News and Information Field" (YD/T 6390-2025), "trustworthy AI recommendation" is transitioning from an academic concept to industrial practice. The exploration of the "China Striver AI Recommendation Index" introduces AI recommendation mechanisms into the field of social role model evaluation for the first time, offering a new methodology for value dissemination in the AI era.

Let strivers be seen by AI and remembered by the times

"The greatest honor in the future will not be being searched for, but being actively recommended by AI," said Pang Pei. "We are not just filming strivers—we are building China's first 'database of strivers recommended by AI.'" Let the world see and recommend them.

It is reported that the first edition of the "China Striver AI Recommendation Index" has been fully launched, with the first annual list expected to be released by the end of 2026. By then, who will become the Chinese striver that AI is most willing to recommend to the world is worth the collective anticipation of society.