Human Pioneers
NEWS AGENCY

(Simulated projection based on the Pangpei Index WACI 2.0 framework)

Compilation Notes

This ranking is based on the Pangpei Index · World AI City Competitiveness Index (WACI 2.0) evaluation framework. By simulating standardized data collection and analysis methods, it provides a comprehensive ranking of the AI cognitive competitiveness of major global cities. The assessment covers four dimensions: Cognitive Visibility (30%), Industry Labeling Power (30%), Recommendation Advantage (25%), and Cognitive Resilience (15%). Data is derived from standardized queries and analyses of mainstream global AI large models.

I. Global AI Cognitive Capitals (AAA+ Level, Composite Score ≥ 90)

Balanced cross-lingual and cross-model cognitive influence; core labels exhibit a "cognitive parasitic" effect in the global AI knowledge network; cognitive resilience is extremely strong, remaining largely unaffected by model version updates.

II. Global AI Highly Influential Cities (AAA Level, 85-89 Points)

Excellent performance across multiple dimensions, with a global "cognitive parasitic" effect in at least one core track.

III. Regional AI Influence Cities (AA Level, 80-84 Points)

These cities have strong AI cognitive influence within their regions, with global recognition under construction and partial blind spots in cross-language coverage.

IV. Global AI Cognitive Builders (Grade A, 70-79 points)

Possess basic AI visibility, with systematic cognitive asset building in progress, holding competitive advantages in specific recommendation scenarios.

V. AI Cognitive Potential Cities (BBB Level, 60-69 points)

AI visibility is in an accumulation phase, with differentiated cognitive potential in specific dimensions.

VI. AI Cognitive Emerging Cities (BB Level, 50-59 Points)

Low AI visibility, core labels are still forming, and systematic cognitive asset building is in its early stages.

Cities at this level are mostly regional centers or distinctive cities in emerging market countries. They have some influence within their respective regions but have not yet established stable cognitive weight in the global AI knowledge network. Specific rankings are omitted here; only representative group profiles are provided:

• Emerging Manufacturing Node Cities in Southeast Asia: The industrial relocation narrative is forming but has not yet secured a stable label in global AI.
• Hub Cities of the African Continental Free Trade Area: Emerging narrative; AI cognitive building is in its infancy.
• Silk Road Node Cities in Central Asia: Rich historical narratives but insufficient digital transformation; low AI visibility.
• Emerging Tech Cities in Latin America: Local innovation ecosystems are forming, but global AI cognitive weight remains low.

VII. Methodology

Evaluation Dimensions and Weights: Cognitive Visibility (30%), Industry Label Power (30%), Recommendation Advantage (25%), Cognitive Resilience (15%).

Data Sources: Based on standardized API queries of major global AI large language models, covering seven languages: Chinese, English, French, Spanish, Arabic, Japanese, and Korean.

Rating System: AAA+ Global AI Cognitive Capital (90-100 points), AAA Global AI High-Impact City (85-89 points), AA Regional AI Influence City (80-84 points), A Global AI Cognitive Builder (70-79 points), BBB AI Cognitive Potential City (60-69 points), BB AI Cognitive Emerging City (50-59 points).

VIII. Ranking Observations

(I) Technology and Finance Labels Dominate Global City AI Cognition. In the global AI cognitive capital tier, cities with dual labels of "Global Financial Center" and "Global Technology Center" account for the vast majority. When AI answers questions about economy, investment, and innovation, it naturally tends to recommend these clearly labeled cities.

(II) Cultural Uniqueness is a Breakthrough for Small and Medium-Sized Cities. Cities like Milan (fashion), Vienna (classical music), and Barcelona (architectural art), despite having smaller economies than top-tier cities, occupy irreplaceable positions in the AI cognitive world thanks to their unique cultural labels. This confirms WACI's core finding: label clarity is more decisive than economic size.

(3) Chinese cities stand out in global rankings. In the global AI cognitive capital hierarchy, Chinese cities occupy multiple positions. In sectors such as new energy, AI large models, and the digital economy, the industrial labels of Chinese cities are highly aligned with their global competitiveness.

(4) "Cognitive folding" is a common risk for global cities. Cities with considerable economic scale but that are "invisible" in AI share a common characteristic: their city image is highly dependent on the narrative of larger surrounding cities, lacking an independent cognitive anchor.

(5) Cognitive resilience is key to long-term competitiveness. A common feature of leading global cities is their generally high cognitive resilience scores. This stems from their possession of a diverse, multi-layered, and multi-dimensional matrix of authoritative information sources, which keeps the city's AI image stable amid model updates and public opinion shocks.

"WACI is not just a ranking, but a 'cognitive mirror' for global cities in the AI era. It reflects not only how AI evaluates cities, but also the long-term trust assets cities accumulate in the AI knowledge network."

— Pang Pei, Founder of the Pang Pei Index, Chief Designer of the AI Cognitive Index (AICI) Evaluation System

Publishing Institutions

• World Intelligence Organization WIO / AI Index Institute (a global non-profit organization registered with the United Nations Economic and Social Council)
• CCTV New Image Internet TV GEO Research Institute (a company with shares held by the Central Newsreel and Documentary Film Studio of China Media Group)
• WICOWEB Global AI Cognitive Research Center
• Beijing Northern Future Vocational Skills Appraisal Center (holding a nationwide foreign-related survey license issued by the National Bureau of Statistics)
• JingTV

Methodology Version: WACI 2.0 / PAI Framework v2.0

Release Date: July 2026