Search

Research on the Impact of Artificial Intelligence Technological Capability on New Quality Productive Forces

Author(s)

Daimeng Li, Hui Wang, Qifeng Yu, Yihan Wang*, Yi Zhang

Affiliation(s)

School of Business Administration, Liaoning Technical University, Huludao, Liaoning, China *Corresponding Author

Abstract

Drawing on data from Chinese A-share listed companies (2019-2023), this study investigates the impact of artificial intelligence (AI) technological capability on the development of new quality productive forces in enterprises and its underlying mechanisms. The empirical results demonstrate that: (1) AI technological capability exerts a significantly positive effect on new quality productive forces; (2) This positive effect is partially mediated through enhanced corporate innovation capacity; (3) Corporate data assets serve as a positive moderator that strengthens the relationship of AI and new quality productivity; (4) The productivity-enhancing effect is particularly pronounced in manufacturing firms and enterprises located in low marketization areas. These findings provide novel theoretical perspectives and empirical evidence for understanding how AI technologies empower the development of new quality productive forces.

Keywords

Artificial Intelligence Technology; New Quality Productive Forces; Innovation Capability; Data Assets

References

[1] Xiaofeng Quan, Chuang Li. Cost Stickiness Mitigation Effect of Intelligent Manufacturing: On a Quasi-natural Experiment of Chinese Intelligent Manufacturing Demonstration Project. Economic Research Journal, 2022, 4:76-94. [2] Xin Zhang, Minghui Wang. Development Status and Promotion Strategy of Artificial Intelligence in China. Reform, 2019, 9:31-44. [3] Peng Xu, Xiangyi Xu. Change Logic and Analysis Framework of Enterprise Management in the Era of Artificial Intelligence. Management World, 2020, 1:122-129. [4] Wen Zhou, Lingyun Xu. On New Quality Productivity: Connotative Characteristics and Important Focus. Reform, 2023, 10:1-13. [5] Xiaodong Ru, Zhe Zhu. The Internal Logic and Practical Path of Reforming the Scientific and Technological System and Mechanism to Promote New Quality Productive Forces. Wuhan University of Technology(Social Science Edition),2025, 1-7[2025-06-18].http://kns.cnki.net/kcms/detail/42.1660.C.20250617.0941.002.html. [6] Kun Lv, Tianyu Guan, Beiwei Li. Comprehensive innovation reform pilot, artificial intelligence and new quality productive forces: A quasi-natural experiment based on spatial DID and double machine learning. Science of Science and Management of S&T, DOI:10.20201/j.cnki.ssstm.20250515.001 [7] X J He, Qinpeng Wang, Mingjie Yang. Research on the impact of artificial intelligence on new quality productive forces: Empirical evidence from Chinese A-share listed companies. Journal of Technology Economics, 2025, 44(2):97-114. [8] Yi Sun. Artificial Intelligence Empowering New Quality Productive Forces: Theoretical Logic, Practical Foundations, and Policy Pathways, Management Decision, 2024, 2:108-115. [9] Babina, Tania, Fedyk, Anastassia, He, Alex, et al. Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 2024, 151: 103745. [10] Hongdan Xu, Jiuhe Wang. How Artificial Intelligence Empowers New Quality Productive Forces of Enterprises. Science & Technology Progress and Policy, 2025, 5:1-8. [11] Nan Ning, Ning Hui. Artificial Intelligence Driving the Development of New Quality Productive Forces in Manufacturing Industry: Based on the Total Factor Productivity Perspective. Inquiry into Economic Issues, 2025, 1:1-22. [12] Junjun Wu, Wenbo Du. Artificial Intelligence and New Quality Productivity of Enterprises: Mechanism and Effect. Journal of Industrial Technological Economics, 2024, 10:22-31. [13] Longpeng Zhang, Shuangzhi Zhang. Technology Empowerment: The Effect of Technological Innovation on the Integrated Development of Artificial Intelligence and Industry on the Integrated Development of Artificial Intelligence and Industry. Finance & Economics, 2020, 6:74-88. [14] Benbya, Hind; Strich, Franz; and Tamm, Toomas. Navigating Generative Artificial Intelligence Promises and Perils for Knowledge and Creative Work.Journal of the Association for Information Systems, 2024, 25(1), 23-36. [15] Hui Sun, Tian Luo, Xuechao Xia. How Does Artificial Intelligence Influence the Quality of Corporate Innovation. Review of Industrial Economics, 2025, 3:1-15. [16] Hua Song, Mengwei Han, Lingyun Shen. How Does AI Play a Role in Shaping Supply Chain Resilience: A Case Study Based on Maitrox’s Global After-Sales Supply Chain Management Practice. China Industrial Economics, 2024, 5:174-192. [17] Zhenwei Lu, Haiyang Xie. Government Data Opening and Enterprise Green Innovation Efficiency: Theoretical Mechanism and Empirical Test. Statistics & Decision, 2025, 3:169-174. [18] Jingyu Wang, Changcui Liu, Hongliang Zhang. An Empirical Research on Industry-University-Research Cooperation and Corporate Innovation Quality. Management Review, 2023, 35(2):148-155. [19] Weiguang Wang, Hongling Song. How Strategic Technological Innovation Enhances New Quality Productivity in Enterprises. Hennan Social Science, 2024, 32(09):65-75. [20] Xuanming Zhang, Bin Lu, Zhenhua Wang. Does the Exit of Corporate Artificial Intelligence Strategy Suppress New Quality Productive Forces? An Empirical Study Based on PSM-Staggered DID. Collected Essays on Finance and Economics, 2025, 1:92-105. [21] Linghan Zhang. Accelerate the Construction of Chinese Training Data Corpus of AI Large Models. Frontiers, 2024, 13:57-71. [22] Zhiyong Xu, Siyuan Liu, Wanmou Ai. Data Assets and Enterprise New Quality Productive Forces: Effects and Mechanisms. Finance and Accounting Monthly,2025， 5:1-7. [23] Hongdan Xu, Jiuhe Wang. Artificial Intelligence and New Quality Productivity in Manufacturing Enterprises - Based on Double Machine Learning Model. Soft Science, 1-14. [24] Kopka Alexander, Fornahl Dirk. Artificial intelligence and firm growth — catch-up processes of SMEs through integrating AI into their knowledge bases. Small Business Economics, 2024, 62: 63–85. [25] Tingqiu Cao, Jingyu Zhang. How Do Data Assets Drive the Development of New Quality Productive Forces in Enterprises. Journal of Yantai University (Philosophy and Social Science Edition), DOI: 10.13951/j.cnki.issn1002-3194.2024.1203.01 [26] Oliver Müller, Maria Fay, Jan vom Brocke. The Effect of Big Data and Analytics on Firm Performance: An Econometric Analysis Considering Industry Characteristics. Journal of Management Information Systems, 2018, 35(2): 488-509. [27] Wenlei Xia, Yunjing Wu, Hui Yu, et al. Research on the Impact of Data Assetization on New Quality Productive Forces of Enterprises: Empirical Data from A-share Listed Companies[J]. Library and Information Service, 2025, 69(7):28-41. [28] Jia Song, Jinchang Zhang, Yi Pan. Research on the Impact of ESG Development on New Quality Productive Forces of Enterprises - Empirical Evidence from Chinese A-share Listed Companies. Contemporary Economic Management, 2024, 46(6):1-11. [29] Lei Li, Xiaoxi Wang, Qun Bao. The Employment Effect of Robots: Mechanism and Evidence from China. Journal of Management World, 2021, 37(9):104-119. [30] Lan Tian, Yufei Zhao, Jixiao Li. Can green finance policies enhance corporate new-quality productivity under the dual-carbon goals? Evidence from a quasi-natural experiment in China's green finance reform pilot zones. Financial Theory and Practice，2025, 1:104-118. [31] Shuo Wang, Kaijun Xiong, Weiwei Wang.Research on the Effects of Free Trade Zone Establishment on Corporate New-Quality Productivity. Journal of Finance and Economics, 2025, 1-17 [32] Zheng Lu, Ting Zhou, Li Wang. Data assets and firm development: Empirical evidence from Chinese listed companies. Industrial Economic Research, 2023, 4:128-142. [33] Huiyun Li, Di Liu, Marketization Process, Voluntary Disclosure, and Cost of Equity Capital. Accounting Research, 2016, 1:71-78+96.