Quantifying the AI Gap: A Comparative Index of Development in the United States and Chinese Regions

2025-10-22

AI Summary

This study quantifies the artificial intelligence (AI) development gap between China and the United States, as well as regional disparities within China. Method: We construct a provincial-level AI Development Index comprising seven dimensions—research, education, industry, policy, infrastructure, talent, and application—and introduce a novel hierarchical weighting framework integrating expert judgment with objective data, alongside anchor-based standardization to ensure cross-national and cross-regional comparability. Contribution/Results: The index yields composite scores of 68.1 for the U.S. and 59.4 for China, revealing a pronounced intra-national gradient: provinces in northern, eastern, and southern China lead, while central and western regions lag significantly. The index provides a rigorous, actionable quantitative foundation and methodological framework for designing differentiated regional AI strategies.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Computer Vision: Remote Sensing / Geospatial AI

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs

Abstract

This study develops a comprehensive Artificial Intelligence (AI) Index with seven primary dimensions, designed for provincial-level and industry-specific analysis. We employ an anchor point method for data normalization, using fixed upper and lower bounds as benchmarks, and devise a hierarchical indicator weighting system that combines expert judgment with objective data. The index draws from authoritative data sources across domains including official statistics, patents and research outputs, education and talent, industrial economy, policy and governance, and social impact. The China-US comparison indicates that under a unified framework, the US composite score (68.1) exceeds China's (59.4). We further dissect China into seven main areas to form a sub-national index. The findings reveal stark regional disparities in China's AI development: the North, East, and South regions lead in composite scores, whereas central and western regions lag significantly, underscoring the effects of regional concentration of innovation and industry resources. This research provides an academic reference and decision support tool for government agencies and research institutions, informing more targeted regional AI development strategies.

Problem

• Develops comprehensive AI Index to compare US and Chinese regional development
• Reveals significant regional disparities in China's AI development across provinces
• Provides decision support for targeted regional AI development strategies

Innovation

• Developed a seven-dimensional AI Index
• Used anchor point method for data normalization
• Created hierarchical indicator weighting system