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.

翻译：本研究构建了一个包含七个主要维度的综合性人工智能（AI）指数，适用于省级层面与行业细分分析。我们采用锚点法进行数据标准化处理，以固定的上下限作为基准，并设计了一套结合专家判断与客观数据的层次化指标权重体系。该指数整合了来自官方统计数据、专利与科研成果、教育与人才、产业经济、政策治理及社会影响等多个领域的权威数据源。中美对比分析表明，在统一框架下，美国综合得分（68.1）高于中国（59.4）。我们进一步将中国划分为七大区域构建次国家级指数。研究发现中国人工智能发展存在显著区域差异：北方、东部及南部地区在综合得分上领先，而中部与西部地区明显滞后，这凸显了创新资源与产业资源区域集聚效应的影响。本研究为政府机构与科研院所提供了学术参考与决策支持工具，有助于制定更具针对性的区域人工智能发展战略。