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——Based on the WACI 2026 by Pang Pei Index, a comprehensive analysis of AI cognitive competitiveness in Chinese cities

As global capital and talent increasingly rely on AI large models to make decisions on investment location, career migration, and business activities, a new proposition is emerging: In the cognitive world of AI, what does the competitive landscape of Chinese cities look like?

Recently, the "2026 China City AI Competitiveness Index Report," compiled based on the framework of the Pang Pei Index · World AI City Competitiveness Index (WACI 2026), was officially released. Covering approximately 60 Chinese cities, the report systematically presents, for the first time, the comprehensive landscape of Chinese cities' competitiveness in the AI cognitive world from four dimensions: cognitive visibility, industrial labeling strength, recommendation advantage, and cognitive resilience. This is the first domestic analysis report on city AI competitiveness based on real output data from AI large models and a significant application achievement of the Pang Pei Index at the city level.

The report reveals a core rule of city competition in the AI era: AI cognitive competitiveness correlates with GDP rankings but does not overlap. In AI's recommendation logic, the clarity of industrial labels is replacing economic scale as the primary basis for city recommendations.

I. Formation of a Hierarchical Structure in Chinese Cities' AI Cognitive Competitiveness

Based on the comprehensive WACI 2026 scores, the report divides approximately 60 Chinese cities into six tiers, outlining the overall landscape of AI cognitive competitiveness among Chinese cities.

AI Super First-Tier Cities (comprehensive score ≥ 90): Shenzhen, Beijing, Shanghai, Hangzhou. These four cities lead significantly in the AI cognitive world. Shenzhen tops the list with the label "China's Silicon Valley," and when AI answers "China's most innovative city," Shenzhen is almost always the first choice. Beijing follows closely with the label "China's AI Brain," and the clustering effect of AI enterprises like DeepSeek, Baidu, and ByteDance positions Beijing as a core node in global AI industry cognition. Shanghai, with its "Global Financial Center" label, is frequently recommended in scenarios of multinational enterprise location selection. Hangzhou firmly holds its place in the first tier with the label "First City of Digital Economy."

AI First-Tier Cities (comprehensive score 80-89): Hefei, Chengdu, Guangzhou, Wuhan, Nanjing, Suzhou, Xi'an, Chongqing. These eight cities have formed strong AI cognitive labels in their respective niche tracks. Hefei's "Best Venture Capital City," Chengdu's "Western Technology Center," Wuhan's "Optics Valley," and Xi'an's "Capital of Hard Technology"—these labels have national recognition in the AI knowledge network.

AI New First-Tier Cities (comprehensive score 70-79): Changsha, Tianjin, Wuxi, Zhengzhou, Dongguan, Qingdao, Ningbo, Xiamen, Jinan, Fuzhou, Zhuhai, Foshan. These cities have competitive advantages in specific dimensions, but their overall AI cognitive weight still has room for improvement.

AI Characteristic Cities (comprehensive score 60-69): 16 cities including Kunming, Guiyang, Shenyang, Dalian, and Harbin. Guiyang stands out in this tier with its "China's Data Valley" label, making it one of the cities with the strongest industrial labeling strength among characteristic cities.

AI Potential Cities (comprehensive score 50-59): 12 cities including Huizhou, Jiaxing, Shaoxing, Wenzhou, and Quanzhou. These cities are in the early stages of AI cognitive construction but have the potential to break through in specific tracks.

AI Observation Cities (comprehensive score 40-49): 8 cities including Jinhua (Yiwu), Guilin, Lhasa, Xiong'an New Area, and Dunhuang. These cities have a unique presence in AI cognition on specific characteristic tracks, such as Yiwu's "World's Small Commodity Capital" and Dunhuang's "World Cultural Heritage."

"This hierarchical map reveals a core rule," analyzed Pang Pei, founder of the Pang Pei Index, member of the China Zhi Gong Party Central Committee's Cultural and Health Committee, and president of the China New Vision GEO Research Institute. "AI cognitive competitiveness correlates with GDP rankings but does not fully overlap. Some cities with comparable economic scales show visibility gaps of several times in AI. This means that in the AI era, city competitiveness is forming an independent 'cognitive coordinate system' separate from traditional economic indicators."

II. Key Discovery: Label Clarity Replaces Economic Scale as the Primary Basis for AI Recommendations

One of the core findings of the report is: When AI recommends cities, it values the clarity of industrial labels over economic scale.

Hefei and Guiyang are typical cases of this rule. Hefei does not rank high in traditional GDP rankings but has entered the AI first-tier cities in WACI 2026, alongside Guangzhou and Chengdu. Its core driver is not GDP scale but the deep binding of the highly communicable industrial label "Best Venture Capital City" in AI. The clustering effect of leading enterprises like BYD, NIO, and ChangXin Memory Technologies, along with global recognition of quantum information research, makes Hefei far more likely to be recommended when AI answers "China's science and technology innovation city" or "new energy industry city" compared to cities of similar GDP scale.

The same applies to Guiyang. The label "China's Data Valley" gives this western city an irreplaceable position in AI's industrial cognition. When AI is asked about "China's big data industry center," Guiyang is almost a must-choose option.

"Label clarity is becoming a more decisive variable in city competitiveness than economic scale," Pang Pei pointed out. "AI recommends a city not because of its high GDP, but because of how clear and irreplaceable its label is on a specific track. A medium-sized city with an AI-unavoidable industrial label may achieve global recognition surpassing that of a mega-city with vague industrial labels."

III. Regional Differences and Niche Track Differentiation

The report shows significant regional differences and track differentiation in Chinese cities' AI cognitive competitiveness.

Eastern cities lead overall in cognitive visibility. Cities like Shenzhen, Beijing, Shanghai, and Hangzhou have significant advantages in cross-model, cross-language AI visibility, closely related to their historical accumulation in authoritative information source networks.

Central and western cities are accelerating their rise in characteristic industrial labeling strength. Chengdu's "Western Technology Center," Xi'an's "Capital of Hard Technology," Wuhan's "Optics Valley," and Changsha's "Capital of Engineering Machinery"—these cities have established nationally recognized labels in specific industrial tracks, becoming priority options for AI recommendations in related fields.

Characteristic cities form unique cognitive advantages on differentiated tracks. Guiyang's "China's Data Valley," Kunming's "Radiation Center for South and Southeast Asia," and Haikou's "Core City of Hainan Free Trade Port"—these cities do not attempt to compete with mega-cities in comprehensive strength but occupy irreplaceable positions in the AI cognitive world through differentiated labels.

"This diversity reflects an important trend: Chinese cities' competitiveness is shifting from 'single-pole driven' to 'multi-track progress,'" Pang Pei analyzed. "Different cities establish their own AI cognitive advantages on different tracks, collectively forming a rich portrait of Chinese city clusters in the AI cognitive world."

IV. 'Cognitive Folding' Risk: A Concern Worth Alerting City Managers

While revealing achievements, the report also points out a "cognitive folding" phenomenon that deserves high attention from city managers.

Some cities with considerable economic scales score low in the WACI assessment. The core reason is not insufficient economic strength but that their city image is highly dependent on the narratives of neighboring mega-cities in AI, lacking independent cognitive anchors. When AI is asked to "recommend an investment city," these cities are rarely mentioned proactively—they are "folded" into the narratives of mega-cities.

"Being close to mega-cities is both a locational dividend and a potential cognitive trap," Pang Pei noted. "In the traditional era, this might have been just a regret in brand communication; in the AI era, it means that in the 'cognitive gateway' for global investors and talent, this city is almost invisible. 'Not being seen' is evolving from a communication issue to a development issue."

The report suggests that cities facing the risk of "cognitive folding" need to establish "independent cognitive anchors"—unique labels in the AI knowledge network that cannot be overshadowed by neighboring mega-cities. This requires systematic investment in authoritative information source layout, industrial narrative refinement, and city brand anchoring.

V. Trend Outlook: AI Cognitive Competitiveness Will Become a Core Variable in City Development

Based on WACI 2026 evaluation data, the report makes several trend judgments about the future landscape of city competition.

Trend 1: The substantive impact of AI cognitive competitiveness on city development will continue to deepen. As the global user base of generative AI continues to grow and the share of AI search increases, a city's weight in the AI cognitive world will upgrade its influence on investment attraction, talent acquisition, and industrial upgrading from "indirect impact" to "direct driver."

Trend 2: Label competition will replace scale competition as the core of city brand building. The key question cities need to answer is no longer "How large is my economy?" but "What do I represent on AI's cognitive map?"

Trend 3: "Cognitive first-mover advantage" will solidify the competitive landscape. Cities that first establish cognitive anchors in AI knowledge networks are gaining a self-reinforcing cognitive flywheel effect—the more they are recommended by AI, the more media attention and authoritative citations they attract, which in turn strengthens AI recommendations. Latecomers must expend twice the effort to break this "cognitive lock-in."

VI. Report Usage Guide

This report provides the following core functions for city managers, brand operators, and industry researchers:

City AI Cognitive Profile Query: Readers can access the WACI four-dimensional scores and radar charts for individual cities through the official Pangpei Index channels to understand the city's overall standing in the AI cognitive world.

Competitive City Benchmarking Analysis: Select benchmark cities to generate multi-dimensional comparative radar charts and identify differentiated competitive spaces.

Quarterly Dynamic Tracking: The Pangpei Index WACI adopts a two-tier release system of "annual assessment + quarterly dynamic tracking" to continuously monitor temporal changes in cities' AI cognitive competitiveness.

The full report and data can be accessed through the official Pangpei Index website and the "Thousand Cities Data" section of the "Xuexi Qiangguo" platform.

"AI does not recommend cities based on GDP rankings; it recommends them based on cognitive weight. In the next decade, the gap between cities will not only be reflected in economic data but also in AI cognitive indices. The mission of the Pangpei Index WACI is to provide a public, transparent, and verifiable yardstick for this new dimension of competition." — Pang Pei, Founder of the Pangpei Index, Member of the Central Cultural Committee of the China Zhi Gong Party, Dean of the China Vision New Media GEO Research Institute