IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v84y2026ics0160791x25003318.html

Corporate productivity transformation under the innovation paradigm: The role and impact of artificial intelligence

Author

Listed:
  • Fu, Yu
  • Chen, Yijun
  • Zhang, Yulin
  • Wang, Menghan
  • Yu, Yuanchun

Abstract

Faced with the slowdown in global economic growth and intensified market competition, artificial intelligence (AI), an emerging general-purpose technology, has become a key driver for enterprises to maintain market competitiveness and promote the modernization of productivity. Based on data from Chinese listed companies from 2012 to 2022, this study employs textual analysis to measure the level of AI application in enterprises and empirically examines the impact of AI on corporate productivity transformation under the innovation paradigm, its mechanism of action, and heterogeneous characteristics. The findings indicate that AI application significantly improves corporate productivity, and this conclusion remains robust after diverse robustness tests. Specifically, AI promotes the modernization of productivity by optimizing the allocation of innovative resources, enhancing dual innovation capabilities, and improving the quality and efficiency of innovation outputs. Moreover, enterprises in environments with high market competition intensity, with rich AI application experience, in the core digital economy, and in high-tech industries can leverage AI technology more effectively to achieve significant productivity improvements. This study provides a new perspective for understanding how AI substantially affects corporate productivity and offers policy implications for supporting the efficient application of AI technology in enterprises.

Suggested Citation

  • Fu, Yu & Chen, Yijun & Zhang, Yulin & Wang, Menghan & Yu, Yuanchun, 2026. "Corporate productivity transformation under the innovation paradigm: The role and impact of artificial intelligence," Technology in Society, Elsevier, vol. 84(C).
  • Handle: RePEc:eee:teinso:v:84:y:2026:i:c:s0160791x25003318
    DOI: 10.1016/j.techsoc.2025.103141
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X25003318
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techsoc.2025.103141?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Guan, Jiancheng & Liu, Na, 2016. "Exploitative and exploratory innovations in knowledge network and collaboration network: A patent analysis in the technological field of nano-energy," Research Policy, Elsevier, vol. 45(1), pages 97-112.
    3. Salman Bahoo & John W. Goodell & Rachid Rhattat & Subhan Shahid, 2025. "Artificial Intelligence in Economics Research: What Have We Learned? What Do We Need to Learn?," Journal of Economic Surveys, Wiley Blackwell, vol. 39(5), pages 2194-2214, December.
    4. Olivier Bertrand & Michael J. Mol, 2013. "The antecedents and innovation effects of domestic and offshore R&D outsourcing: The contingent impact of cognitive distance and absorptive capacity," Strategic Management Journal, Wiley Blackwell, vol. 34(6), pages 751-760, June.
    5. Carol Corrado & Jonathan Haskel & Cecilia Jona-Lasinio, 2021. "Artificial intelligence and productivity: an intangible assets approach," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 435-458.
    6. Auboin, Marc & Koopman, Robert & Xu, Ankai, 2021. "Trade and innovation policies: Coexistence and spillovers," Journal of Policy Modeling, Elsevier, vol. 43(4), pages 844-872.
    7. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    8. Lee, Yong Suk & Kim, Taekyun & Choi, Sukwoong & Kim, Wonjoon, 2022. "When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy," Technovation, Elsevier, vol. 118(C).
    9. Kakatkar, Chinmay & Bilgram, Volker & Füller, Johann, 2020. "Innovation analytics: Leveraging artificial intelligence in the innovation process," Business Horizons, Elsevier, vol. 63(2), pages 171-181.
    10. Ioanna Kastelli & Petros Dimas & Dimitrios Stamopoulos & Aggelos Tsakanikas, 2024. "Linking Digital Capacity to Innovation Performance: the Mediating Role of Absorptive Capacity," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 238-272, March.
    11. Alghamdi, OmarA. & Agag, Gomaa, 2024. "Competitive advantage: A longitudinal analysis of the roles of data-driven innovation capabilities, marketing agility, and market turbulence," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    12. Timothy J. Bartik, 1991. "Who Benefits from State and Local Economic Development Policies?," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wbsle.
    13. William D. Nordhaus, 2021. "Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 299-332, January.
    14. Stefano Baruffaldi & Brigitte van Beuzekom & Hélène Dernis & Dietmar Harhoff & Nandan Rao & David Rosenfeld & Mariagrazia Squicciarini, 2020. "Identifying and measuring developments in artificial intelligence: Making the impossible possible," OECD Science, Technology and Industry Working Papers 2020/05, OECD Publishing.
    15. Tsang, Albert & Wang, Kun Tracy & Liu, Simeng & Yu, Li, 2021. "Integrating corporate social responsibility criteria into executive compensation and firm innovation: International evidence," Journal of Corporate Finance, Elsevier, vol. 70(C).
    16. Gao, Yang & Liu, Siqiang & Yang, Lu, 2025. "Artificial intelligence and innovation capability: A dynamic capabilities perspective," International Review of Economics & Finance, Elsevier, vol. 98(C).
    17. Kopalle, Praveen K. & Gangwar, Manish & Kaplan, Andreas & Ramachandran, Divya & Reinartz, Werner & Rindfleisch, Aric, 2022. "Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities," International Journal of Research in Marketing, Elsevier, vol. 39(2), pages 522-540.
    18. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).
    19. Mikalef, Patrick & Islam, Najmul & Parida, Vinit & Singh, Harkamaljit & Altwaijry, Najwa, 2023. "Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective," Journal of Business Research, Elsevier, vol. 164(C).
    20. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    21. An, Hyoung Joon & Ahn, Sang-Jin, 2016. "Emerging technologies—beyond the chasm: Assessing technological forecasting and its implication for innovation management in Korea," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 132-142.
    22. Robert J. Gordon, 2018. "Why Has Economic Growth Slowed When Innovation Appears to be Accelerating?," NBER Working Papers 24554, National Bureau of Economic Research, Inc.
    23. Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    24. Yu, Yiyong & Cheng, Li & Zhang, Danni, 2024. "How does market competition affect enterprise cooperative innovation? The moderating role of intellectual property protection and government subsidies," Technovation, Elsevier, vol. 137(C).
    25. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    26. Quintana-Garci­a, Cristina & Benavides-Velasco, Carlos A., 2008. "Innovative competence, exploration and exploitation: The influence of technological diversification," Research Policy, Elsevier, vol. 37(3), pages 492-507, April.
    27. Tekic, Zeljko & Füller, Johann, 2023. "Managing innovation in the era of AI," Technology in Society, Elsevier, vol. 73(C).
    28. Mariani, Marcello M. & Nambisan, Satish, 2021. "Innovation Analytics and Digital Innovation Experimentation: The Rise of Research-driven Online Review Platforms," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    29. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    30. Gordon, Robert J., 2018. "Why Has Economic Growth Slowed When Innovation Appears To Be Accelerating?," CEPR Discussion Papers 13039, C.E.P.R. Discussion Papers.
    31. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    32. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    33. Mao, Connie X. & Zhang, Chi, 2018. "Managerial Risk-Taking Incentive and Firm Innovation: Evidence from FAS 123R," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 867-898, April.
    34. Bertomeu, Jeremy & Lin, Yupeng & Liu, Yibin & Ni, Zhenghui, 2025. "The impact of generative AI on information processing: Evidence from the ban of ChatGPT in Italy," Journal of Accounting and Economics, Elsevier, vol. 80(1).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    2. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    3. Anastasios Evgenidis & Apostolos Fasianos, 2025. "AI news shocks and the macroeconomy: evidence from UK patent data," IFS Working Papers W25/48, Institute for Fiscal Studies.
    4. Nils Grashof & Alexander Kopka, 2023. "Widening or closing the gap? The relationship between artificial intelligence, firm-level productivity and regional clusters," Bremen Papers on Economics & Innovation 2304, University of Bremen, Faculty of Business Studies and Economics.
    5. Roth, Felix & Rammer, Christian, 2025. "Intangible Assets and Productivity at the Firm Level: R&D versus non-R&D Intangibles," Hamburg Discussion Papers in International Economics 20, University of Hamburg, Department of Economics.
    6. Andres, Raphaela & Niebel, Thomas & Sack, Robin, 2025. "Big data and firm-level productivity – A cross-country comparison," Information Economics and Policy, Elsevier, vol. 71(C).
    7. Wu, Yongqiu & Lin, Zhiwei & Zhang, Qingcui & Wang, Wei, 2024. "Artificial intelligence, wage dynamics, and inequality: Empirical evidence from Chinese listed firms," International Review of Economics & Finance, Elsevier, vol. 96(PC).
    8. Zhai, Shaoxuan & Liu, Zhenpeng, 2023. "Artificial intelligence technology innovation and firm productivity: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PB).
    9. Khalil, Ashraf & Agarwal, Reeti & Yaqub, Muhammad Zafar & Papa, Armando, 2025. "Unlocking the AI-Productivity paradox in HR: Qualitative insights across organizational levels," Journal of Business Research, Elsevier, vol. 199(C).
    10. He, Ling-Yun & Wang, Liang, 2025. "Can artificial intelligence curb greenwashing? Firm-level evidence based on large language model," Energy Economics, Elsevier, vol. 152(C).
    11. Wang, Zongrun & Zhang, Taiyu & Ren, Xiaohang & Shi, Yukun, 2024. "AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies," Energy Economics, Elsevier, vol. 132(C).
    12. Ma, Dechao & Wu, Weiwei, 2024. "Does artificial intelligence drive technology convergence? Evidence from Chinese manufacturing companies," Technology in Society, Elsevier, vol. 79(C).
    13. Xueyuan Gao & Hua Feng, 2023. "AI-Driven Productivity Gains: Artificial Intelligence and Firm Productivity," Sustainability, MDPI, vol. 15(11), pages 1-21, June.
    14. Zhaozhong Zhang & Fangfang Deng, 2023. "How can artificial intelligence boost firms’ exports? evidence from China," PLOS ONE, Public Library of Science, vol. 18(8), pages 1-24, August.
    15. Yingjie Xu & Bingchao Zheng & Baojie Guo, 2025. "How Do Industrial Robots Affect the Total Factor Productivity in Manufacturing Enterprises?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(4), pages 14057-14093, October.
    16. Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2025. "AI innovation and the labor share in European regions," European Economic Review, Elsevier, vol. 177(C).
    17. Marioni, Larissa da Silva & Rincon-Aznar, Ana & Venturini, Francesco, 2024. "Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 228(C).
    18. Jacques Mairesse & Pierre Mohnen & Ad Notten, 2025. "Innovation and productivity: the recent empirical literature and the state of the art," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(1), pages 1-27, March.
    19. gert Bijnens & Joep Konings & Aaron Putseys, 2025. "Unveiling the J-curve: How Intangibles Drive Productivity Mismeasurement," Working Papers of VIVES - Research Centre for Regional Economics 779815, KU Leuven, Faculty of Economics and Business (FEB), VIVES - Research Centre for Regional Economics.
    20. An, Meng & Lin, Jiabao & Luo, Xin (Robert), 2024. "The impact of human AI skills on organizational innovation: The moderating role of digital organizational culture," Journal of Business Research, Elsevier, vol. 182(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:84:y:2026:i:c:s0160791x25003318. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.