Artificial Intelligence Application and Enterprise Competitive Advantage
Research Article
Open Access
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Artificial Intelligence Application and Enterprise Competitive Advantage

Yiming Cui 1*
1 Shandong University of Technology
*Corresponding author: 1021585667@qq.com
Published on 22 October 2025
Journal Cover
AEMPS Vol.231
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-463-2
ISBN (Online): 978-1-80590-464-9
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Abstract

Significant differences have been observed in the application effects of Artificial Intelligence technology across industries, which has widened the "Digital divide" among enterprises. Using data from A-share listed companies spanning 2008 to 2023, this study employs the Two-way fixed effects model to examine how AI applications influence Enterprise competitive advantage and to investigate the moderating role of Enterprise attributes (specifically high-tech and technology-intensive industries). The results indicate that AI applications significantly boost Enterprise competitive advantage, with a more pronounced positive impact observed for High-tech enterprises and Technology-intensive enterprises. In terms of mechanism, AI exerts its effects through three channels: enhancing Operational efficiency, driving innovation, and strengthening Market response ability.This study offers a theoretical foundation for enterprises with different attributes to develop tailored AI strategy, which helps reduce the Gap in the distribution of technological dividends.

Keywords:

Artificial Intelligence, Enterprise competitive advantage, Enterprise attributes, Moderating effect, Mechanism analysis

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Cui,Y. (2025). Artificial Intelligence Application and Enterprise Competitive Advantage. Advances in Economics, Management and Political Sciences,231,68-82.

References

[1]. Aghion P, Jones B F, Jones C I. Artificial intelligence and economic growthRR. Cambridge: National Bureau of Economic Research, 2023. 2024−08−262024−08−26.

[2]. McKinsey & Company. The state of AI in 2023: Generative AI's breakout yearR/OLR/OL. New York: McKinsey & Company, 20232024−08−262024−08−26.

[3]. Yao Jiaquan, Zhang Kunpeng, Guo Lipeng, et al. How does artificial intelligence improve enterprise production efficiency?—Based on the perspective of labor skill structure adjustmentJJ. Management World, 2024, 40(02): 101-116+133+117-122.

[4]. World Bank.(2024). World Development Report 2024: Artificial Intelligence and Growth. Washington, DC: World Bank.

[5]. Brynjolfsson, E. (2021). The Productivity Paradox of AI. MIT Sloan Management Review, 63(1), 22-25.

[6]. Li Jinchang, Lian Ganghui, Xu Aiting. The way out for enterprise green transformation under the "Dual Carbon" vision—An empirical study on digitalization driving greeningJJ. Journal of Quantitative & Technological Economics, 2023, 40(9): 27~49.

[7]. Acemoglu, D., & Restrepo, P.(2020).Robots and jobs: Evidence from US labor markets.

[8]. Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future.

[9]. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power.

[10]. Bresnahan, T. F., Trajtenberg, M. (2022). General Purpose Technologies: Engines of Growth? Journal of Econometrics, 221(1), 112-134.

[11]. Yang Xingquan, Qi Yunfei, Wu Haomin. Does industry growth affect corporate cash holdings?JJ. Management World, 2016, (01): 153-169.

[12]. Yin Meiqun, Sheng Lei, Li Wenbo. Executive incentive, innovation input and corporate performance—An industry empirical study based on the endogenous perspectiveJJ. Nankai Business Review, 2018, 21(01): 109-117.

[13]. Li Weibing, Zhang Xing. Digital transformation and enterprise transaction costsJJ. Journal of Huazhong University of Science and Technology (Social Science Edition), 2023, 37(06): 8-17.

[14]. Kong Dongmin, Liu Shasha, Wang Yanan. Market competition, property rights and government subsidiesJJ. Economic Research Journal, 2013, 48(02): 55-67.

[15]. Jensen M C. The modern industrial revolution, exit, and the failure of internal control systems [J]. Journal of Finance, 1993, 48(3): 831-880.

[16]. Shleifer A, Vishny R W. A survey of corporate governance [J]. Journal of Finance, 1997, 52(2): 737-783.

References

[1]. Aghion P, Jones B F, Jones C I. Artificial intelligence and economic growthRR. Cambridge: National Bureau of Economic Research, 2023. 2024−08−262024−08−26.

[2]. McKinsey & Company. The state of AI in 2023: Generative AI's breakout yearR/OLR/OL. New York: McKinsey & Company, 20232024−08−262024−08−26.

[3]. Yao Jiaquan, Zhang Kunpeng, Guo Lipeng, et al. How does artificial intelligence improve enterprise production efficiency?—Based on the perspective of labor skill structure adjustmentJJ. Management World, 2024, 40(02): 101-116+133+117-122.

[4]. World Bank.(2024). World Development Report 2024: Artificial Intelligence and Growth. Washington, DC: World Bank.

[5]. Brynjolfsson, E. (2021). The Productivity Paradox of AI. MIT Sloan Management Review, 63(1), 22-25.

[6]. Li Jinchang, Lian Ganghui, Xu Aiting. The way out for enterprise green transformation under the "Dual Carbon" vision—An empirical study on digitalization driving greeningJJ. Journal of Quantitative & Technological Economics, 2023, 40(9): 27~49.

[7]. Acemoglu, D., & Restrepo, P.(2020).Robots and jobs: Evidence from US labor markets.

[8]. Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future.

[9]. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power.

[10]. Bresnahan, T. F., Trajtenberg, M. (2022). General Purpose Technologies: Engines of Growth? Journal of Econometrics, 221(1), 112-134.

[11]. Yang Xingquan, Qi Yunfei, Wu Haomin. Does industry growth affect corporate cash holdings?JJ. Management World, 2016, (01): 153-169.

[12]. Yin Meiqun, Sheng Lei, Li Wenbo. Executive incentive, innovation input and corporate performance—An industry empirical study based on the endogenous perspectiveJJ. Nankai Business Review, 2018, 21(01): 109-117.

[13]. Li Weibing, Zhang Xing. Digital transformation and enterprise transaction costsJJ. Journal of Huazhong University of Science and Technology (Social Science Edition), 2023, 37(06): 8-17.

[14]. Kong Dongmin, Liu Shasha, Wang Yanan. Market competition, property rights and government subsidiesJJ. Economic Research Journal, 2013, 48(02): 55-67.

[15]. Jensen M C. The modern industrial revolution, exit, and the failure of internal control systems [J]. Journal of Finance, 1993, 48(3): 831-880.

[16]. Shleifer A, Vishny R W. A survey of corporate governance [J]. Journal of Finance, 1997, 52(2): 737-783.

Cite this article

Cui,Y. (2025). Artificial Intelligence Application and Enterprise Competitive Advantage. Advances in Economics, Management and Political Sciences,231,68-82.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICEMGD 2025 Symposium: Resilient Business Strategies in Global Markets

ISBN: 978-1-80590-463-2(Print) / 978-1-80590-464-9(Online)
Editor: Florian Marcel Nuţă, Li Chai
Conference website: https://2025.icemgd.org/CAU.html
Conference date: 20 September 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.231
ISSN: 2754-1169(Print) / 2754-1177(Online)

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