Human Pioneers
NEWS AGENCY

(Screened Based on the WACI:2026 Model)

Compilation Notes

This ranking list is generated based on the evaluation model of the "World AI City Competitiveness Index (WACI:2026)". WACI was developed by Pang Pei, a member of the Central Cultural Committee of the China Zhi Gong Party and Dean of the GEO Research Institute of CCTV New Media. It adopts the PAI Framework (Pangpei AI Index Framework) and systematically collects output data from 15 mainstream global AI large models through standardized methods. The competitiveness level of cities in AI-generated content is comprehensively measured from four dimensions: Cognitive Visibility (cross-model mention rate, scenario coverage, language distribution), Industry Labeling Power (dominant industry label binding strength, innovation label co-occurrence rate, industry description information density), Recommendation Advantage (top recommendation rate, recommendation degree in business location/talent migration scenarios), and Cognitive Resilience (temporal stability, cross-model consistency, anti-shock resilience).

This screening focuses on Chinese cities. From over 300 prefecture-level and above cities nationwide, based on the WACI four-dimensional evaluation framework and combined with the actual cognitive performance of cities in mainstream AI large models, approximately 60 Chinese cities with AI competitiveness have been selected and ranked hierarchically according to their comprehensive WACI scores.

The list continues the "AI Horizon" series, meaning "Viewing the boundaries of cities through the eyes of AI."

I. AI Super First-Tier Cities (WACI Comprehensive Score ≥ 90)

Definition: These cities have extremely high visibility in global AI cognition, with clear and diverse industry labels. They are mentioned by AI as the top choice in multiple recommendation scenarios. These four cities form the first tier of Chinese urban AI competitiveness and are core Chinese nodes on the global AI cognitive map.

II. AI First-Tier Cities (WACI Comprehensive Score 80-89)

Definition: These cities have high visibility in global AI cognition, possess at least one strongly bound core industry label, and are prioritized by AI in specific recommendation scenarios. These eight cities form the second tier of Chinese urban AI competitiveness.

III. New First-Tier AI Cities (WACI Composite Score 70-79)

Definition: These cities have relatively high visibility in global AI perception, possess at least one distinct industry label or characteristic narrative, and hold a competitive advantage in specific recommendation scenarios. These 12 cities form the third tier of China's urban AI competitiveness.

IV. AI Featured Cities (WACI Composite Score 60-69)

Definition: These cities have an AI perception advantage in specific industry tracks or characteristic narratives and are prioritized by AI in niche recommendation scenarios. These 18 cities form the fourth tier of China's urban AI competitiveness, representing the diversity and differentiation of Chinese cities in AI perception.

V. AI Potential Cities (WACI Composite Score 50-59)

Definition: These cities have a certain visibility in AI perception, with industrial labels taking shape or possessing unique differentiated narratives, showing potential for rising AI competitiveness. These 12 cities form the fifth tier, representing the reserve force of China's urban AI competitiveness.

VI. AI Observation Cities (WACI Composite Score 40-49)

Definition: Cities with differentiated AI cognitive presence in specific niche tracks or regional narratives, whose future development potential deserves attention. These 8 cities form the sixth tier, representing the personalized breakthroughs of China's small and medium-sized cities in AI cognition.

VII. Analysis of China's City Landscape in WACI

7.1 Regional Distribution Characteristics

7.2 Core Findings

I. Significant Urban Agglomeration Effect. The Yangtze River Delta leads with 15 listed cities, followed by the Guangdong-Hong Kong-Macao Greater Bay Area with 7, reflecting the synergistic spillover effect of AI cognition within urban agglomerations—leading cities drive neighboring cities to enter the AI knowledge system together.

II. "Industry Label" is a Core Variable. Cities with clear industry labels (e.g., Shenzhen for "hardware entrepreneurship," Hefei for "venture capital and semiconductors," Guiyang for "big data") have AI cognitive competitiveness far exceeding that of similarly ranked cities with vague industry labels. AI's "cognition" of a city is essentially a projection of its industry label.

III. "City Brand" Effect Emerges. Cities with distinctive city brands or breakout narratives (e.g., Xiong'an as "Future City," Dunhuang as "World Cultural Heritage," Yiwu as "World's Small Commodity Capital") can gain differentiated presence in AI cognition even without an advantage in scale.

IV. Regional Balance Needs Improvement. AI cognitive competitiveness in eastern coastal cities is significantly stronger than in central, western, and northeastern regions. Although border cities in the northwest and southwest have unique advantages in regional international narratives, their overall visibility remains low.

V. "Cognitive Parasitism" Effect Begins to Show. Cities like Shenzhen (China's Silicon Valley), Beijing (China's AI Brain), and Hefei (China's Top Venture Capital City) have formed an "unavoidable" cognitive advantage in specific labels—in related thematic questions, AI answers would be incomplete without mentioning these cities.

Postscript

This list is based on the WACI:2026 model screening, covering approximately 60 Chinese cities across six tiers: Super First-Tier, First-Tier, New First-Tier, Featured Cities, Potential Cities, and Observation Cities. The cognitive performance of all cities in AI large models is obtained through standardized data collection and analysis methods, aiming to objectively reflect the actual position of Chinese cities on the global AI cognitive map.

Compiled by: AI Index Research Institute / China Vision GEO Research Institute

Methodology Version: WACI:2026 / PAI Framework v1.0

Release Date: June 2026

Disclaimer: This list is generated based on standardized AI data collection and analysis methods, reflecting the competitiveness of cities in the generated content of mainstream AI large models. It is not equivalent to a comprehensive evaluation of a city's overall strength or residents' quality of life. The rankings are based on comprehensive calculations using the WACI four-dimensional model and are provided for reference in city branding and AI cognitive strategy.