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AI-driven renaissance: Revolutionizing technology through industrial artificial intelligence in European economies

Author

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  • Anser, Muhammad Khalid
  • Adebayo, Tomiwa Sunday

Abstract

Industrial Artificial Intelligence is critical in shaping technological innovation by optimizing research and development, enhancing decision-making, and improving industrial efficiency. This research investigates the asymmetric relationship between industrial artificial intelligence and technological innovation in the top ten European nations, utilizing industrial artificial intelligence (Germany, the UK, France, Sweden, the Netherlands, Switzerland, Belgium, Spain, Italy, and Poland). Unlike previous investigations that employed panel data methods, this study implements the Quantile-on-Quantile technique to capture country-specific asymmetric dynamics between variables. Findings reveal a predominantly positive relationship between industrial artificial intelligence and technological innovation, varying across different quantiles and nations. The degree of asymmetry suggests that policy decisions should consider fluctuations in the adoption and innovation levels of artificial intelligence across countries. These insights provide valuable guidance for policymakers and industries seeking to maximize the benefits of artificial intelligence-driven technological advancements.

Suggested Citation

  • Anser, Muhammad Khalid & Adebayo, Tomiwa Sunday, 2026. "AI-driven renaissance: Revolutionizing technology through industrial artificial intelligence in European economies," Technology in Society, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:teinso:v:84:y:2026:i:c:s0160791x25003197
    DOI: 10.1016/j.techsoc.2025.103129
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    References listed on IDEAS

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    1. David Autor & Anna Salomons, 2018. "Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share," NBER Working Papers 24871, National Bureau of Economic Research, Inc.
    2. Usman, Ojonugwa & Ibrahim, Blend & Ozkan, Oktay & Ike, George N., 2025. "Role of fourth industrial revolution on dirty and clean energy under bearish, neutral and bullish market conditions: A quantile-on-quantile Granger causality approach," Energy, Elsevier, vol. 322(C).
    3. Patnaik, Priyadarsini & Bakkar, Mahmoud, 2024. "Exploring determinants influencing artificial intelligence adoption, reference to diffusion of innovation theory," Technology in Society, Elsevier, vol. 79(C).
    4. Jiang, Wei & Hu, Yanhui & Zhao, Xiangyu, 2025. "The impact of artificial intelligence on carbon market in China: Evidence from quantile-on-quantile regression approach," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
    5. Rampersad, Giselle, 2020. "Robot will take your job: Innovation for an era of artificial intelligence," Journal of Business Research, Elsevier, vol. 116(C), pages 68-74.
    6. David Autor & Anna Salomons, 2018. "Is Automation Labor Share–Displacing? Productivity Growth, Employment, and the Labor Share," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 49(1 (Spring), pages 1-87.
    7. Sharif, Arshian & Mishra, Shekhar & Sinha, Avik & Jiao, Zhilun & Shahbaz, Muhammad & Afshan, Sahar, 2020. "The renewable energy consumption-environmental degradation nexus in Top-10 polluted countries: Fresh insights from quantile-on-quantile regression approach," Renewable Energy, Elsevier, vol. 150(C), pages 670-690.
    8. Léo-Paul Dana & Aidin Salamzadeh & Samira Mortazavi & Morteza Hadizadeh, 2025. "Correction: Dana et al. Investigating the Impact of International Markets and New Digital Technologies on Business Innovation in Emerging Markets. Sustainability 2022, 14 , 983," Sustainability, MDPI, vol. 17(18), pages 1-1, September.
    9. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    10. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    11. Xiao, Zhijie, 2009. "Quantile cointegrating regression," Journal of Econometrics, Elsevier, vol. 150(2), pages 248-260, June.
    12. Sun, Zhiyao & Che, Shuai & Wang, Jie, 2024. "Deconstruct artificial intelligence's productivity impact: A new technological insight," Technology in Society, Elsevier, vol. 79(C).
    13. DonHee Lee & Seong No Yoon, 2021. "Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges," IJERPH, MDPI, vol. 18(1), pages 1-18, January.
    14. Su, Chi-Wei & Pang, Li-Dong & Tao, Ran & Shao, Xuefeng & Umar, Muhammad, 2022. "Renewable energy and technological innovation: Which one is the winner in promoting net-zero emissions?," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    15. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    16. 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).
    17. Li, Yaya & Zhang, Yuru & Pan, An & Han, Minchun & Veglianti, Eleonora, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Technology in Society, Elsevier, vol. 70(C).
    18. Benlu Hai & Ximing Yin & Jie Xiong & Jin Chen, 2022. "Could more innovation output bring better financial performance? The role of financial constraints," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    19. Yaya Li & Yuru Zhang & An Pan & Minchun Han & Eleonora Veglianti, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Post-Print hal-04522085, HAL.
    20. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    21. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    22. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(1), pages 1-21, March.
    23. repec:bin:bpeajo:v:49:y:2019:i:2018-01:p:1-87 is not listed on IDEAS
    24. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    25. Razzaq, Asif & Wang, Yufeng & Chupradit, Supat & Suksatan, Wanich & Shahzad, Farrukh, 2021. "Asymmetric inter-linkages between green technology innovation and consumption-based carbon emissions in BRICS countries using quantile-on-quantile framework," Technology in Society, Elsevier, vol. 66(C).
    26. Muhammad Asif Qureshi & Jawaid Ahmed Qureshi & Ammar Ahmed & Shahzad Qaiser & Ramsha Ali & Arshian Sharif, 2020. "The Dynamic Relationship Between Technology Innovation and Human Development in Technologically Advanced Countries: Fresh Insights from Quantiles-on-Quantile Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(2), pages 555-580, November.
    27. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
    28. Fernández-Macías, Enrique & Klenert, David & Antón, José-Ignacio, 2021. "Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 76-89.
    29. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
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