重庆理工大学学报2026，Vol.40Issue(6)：13-27,15.DOI:10.3969/j.issn.1674-8425(s).2026.03.002
企业人工智能发展水平测度与分析
Measurement and analysis of the development levels of AI in enterprises:A new approach based on large language models
摘要
Abstract
Artificial Intelligence(AI)is widely recognized as a core engine of economic growth.However,in-depth research on its development patterns and heterogeneous characteristics at the micro-enterprise level remains scarce due to challenges in data acquisition and measurement.Innovatively,this study employs web-scraping techniques to collect annual reports of listed companies from 2007 to 2020,which are further processed into sentence-level coropora for meticulous manual annotation.Subsequently,pre-trained language model BERT is utilized for training and supervised fine-tuning to construct a multidimensional evaluation system.This system assesses the development of AI across the entire enterprise spectrum,as well as specifically within the infrastructure,technology,and application layers,with model performance validated via a confusion matrix.The findings indicate that at the enterprise level,the development of AI in the technology layer lags relatively behind,with significant internal disparities among firms.Specifically,smaller,long-established,and non-state-owned enterprises(non-SOEs)exhibit higher levels of AI development.Geographically,enterprises in five major eastern provinces and cities,including Beijing and Shanghai,lead in AI advancement,while regional development patterns across provinces demonstrate a phased characteristic of initial divergence followed by convergence.In terms of sector-wise analysis,the enterprises in information transmission,software,and IT service industries shows the highest penetration of AI.Manufacturing firms are the most mature in AI application,whereas the enterprises in agriculture,forestry,animal husbandry,and fishery industries remain relatively weak in both the breadth and depth of AI integration.This study reveals the current status and trends of corporate AI development,providing a robust empirical basis for governments to formulate precise AI policies and for enterprises to advance their digital transformation.关键词
人工智能/大语言模型/测度/企业Key words
artificial intelligence/large language model/measurement/enterprise分类
社会科学引用本文复制引用
吴静茹,张博,江源,谭富文..企业人工智能发展水平测度与分析[J].重庆理工大学学报,2026,40(6):13-27,15.基金项目
重庆市社会科学规划博士项目"新质生产力形成目标下的居民数字素养高质量培育机制和收入分配效应研究"(2023BS018) （2023BS018）
国家社会科学基金项目"居民数字技能激发新型消费的动力机制及效应研究"(23BJY243) （23BJY243）
重庆市教委人文社科项目"共同富裕目标下数字资本赋能农村相对贫困治理的效应测度和提升路径研究"(23SKGH271) （23SKGH271）
云南省基础研究计划项目"财政金融协同驱动'专精特新'企业突破式创新的机理与路径研究"(202501CI070231) （202501CI070231）
