工业技术经济2025，Vol.44Issue(4)：60-69,10.DOI:10.3969/j.issn.1004-910X.2025.04.005
人工智能驱动新质生产力发展的实践路径研究
Thoughts on the Practical Approach of Artificial Intelligence Driving the Development of New Quality Productivity
摘要
Abstract
The development of artificial intelligence(AI)technology is a key factor driving the formation of new quality pro-ductivity,especially the artificial intelligence achievements represented by series models such as DeepSeek-R1,V3,Coder,etc.,which have attracted wide attention from all walks of life on the development and application value of artificial intelligence.Currently,AI development has established a solid foundation for advancing new quality productivity,supported by the AI-priority development strategy and the rapid growth of AI's core components:data,algorithms,and computing power,along with the con-tinuous expansion of the AI industry.However,bottlenecks persist,including poor data quality,limited integration and innovation in digital technologies,and inadequate application of AI.Therefore,starting from Marx's theory of the basic three elements of pro-ductivity,based on the perspective of system theory,focusing on the synergistic innovation roles of data,computing power,algo-rithms,and AI applications,and through the construction of a national corpus operation platform,an AI training ground,an arith-metic power platform,an AI industry application base,and an open source ecology of AI,we can realize the expansion of the ob-ject of new-quality labor,the formation of new-quality labor means,and the shaping of new-quality labor force,and the positive cycle of"data-driven innovation-tool-enabled production-ecological cultivation of talents"will be formed,ultimately realizing a qualitative leap in productivity.关键词
人工智能/新质生产力/数据/算法/算力/语料运营平台/算力平台/AI行业应用基地Key words
artificial intelligence/new quality productivity/data/algorithm/computing power/corpus operation plat-form/arithmetic power platform/AI industry application base分类
管理科学引用本文复制引用
李兴腾,黄鹂强,郭江江,涂雨..人工智能驱动新质生产力发展的实践路径研究[J].工业技术经济,2025,44(4):60-69,10.基金项目
国家社会科学基金重大项目"人工智能前瞻精准识别高潜能未来产业研究"(项目编号:24&ZD072) （项目编号:24&ZD072）
国家自然科学基金面上项目"基于信息呈现于收费模式的平台治理研究"(项目编号:72271217) （项目编号:72271217）
中国博士后科学基金面上项目"基于公共价值的地方数字政府绩效评价及应用研究"(项目编号:2023M731171) （项目编号:2023M731171）
浙江省自然科学基金杰出青年基金项目"电子商务用户画像构建与应用研究"(项目编号:LR22G010002). （项目编号:LR22G010002）
