The impact of artificial intelligence on labor productivity
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Abstract Recent evidence indicates an upsurge in artificial intelligence and robotics (AI) patenting activities in the latest years, suggesting that solutions based on AI technologies might have started to exert an effect on the economy. We test this hypothesis using a worldwide sample of 5257 companies having filed at least a patent related to the field of AI between 2000 and 2016. Our analysis shows that, once controlling for other patenting activities, AI patent applications generate an extra-positive effect on companies’ labor productivity. The effect concentrates on SMEs and services industries, suggesting that the ability to quickly readjust and introduce AI-based applications in the production process is an important determinant of the impact of AI observed to date.
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The rapid development of AI creates many economic benefits.
“The rapid development of AI creates many economic benefits (Damioli et al., 2021; Sequeira et al., 2021).”
From Impacts of generative artificial intelligence on the future of labor market: a systematic review (2025) · cites this paper as Damioli et al., 2021
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Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1998) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00009-8 · Cited by 22,571 · see citing works
Artificial intelligence: a modern approach
Kumar, D. A., Balasubramanian, S., Byeon, D. H., & Manerkar, P. G. V. (1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 22,182 · see citing works
Endogenous Technological Change
Romer, P. M. (1990) · Journal of Political Economy · doi:10.1086/261725 · Cited by 17,711 · see citing works
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1995) · Working Paper Series · doi:10.1920/wp.ifs.1995.9517 · Cited by 14,755 · see citing works
Endogenous Technological Change
Romer, P. (1989) · National Bureau of Economic Research · doi:10.3386/w3210 · Cited by 13,312 · see citing works
Technical Change and the Aggregate Production Function
Solow, R. M. (1957) · The Review of Economics and Statistics · doi:10.2307/1926047 · Cited by 12,259 · see citing works
Artificial intelligence: A modern approach
Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,726 · see citing works
How to do Xtabond2: An Introduction to Difference and System GMM in Stata
Roodman, D. (2009) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0900900106 · Cited by 9,848 · see citing works
Journal of Economic Literature
Durlauf, S. N. (2019) · AEA Papers and Proceedings · doi:10.1257/pandp.109.633 · Cited by 7,666 · see citing works
“A Model of Growth: Through Creative Destruction”
Aghion, P., & Howitt, P. (1992) · Econometrica · doi:10.2307/2951599 · Cited by 7,529 · see citing works
The Skill Content of Recent Technological Change: An Empirical Exploration
Autor, D. H., Levy, F., & Murnane, R. J. (2003) · The Quarterly Journal of Economics · doi:10.1162/003355303322552801 · Cited by 6,205 · see citing works
Patent Statistics as Economic Indicators: A Survey
Griliches, Z. (1990) · National Bureau of Economic Research · doi:10.3386/w3301 · Cited by 5,824 · see citing works
A Note on the Theme of Too Many Instruments *
Roodman, D. M. (2009) · Oxford Bulletin of Economics and Statistics · doi:10.1111/j.1468-0084.2008.00542.x · Cited by 5,678 · see citing works
A Model of Growth Through Creative Destruction
Aghion, P., & Howitt, P. W. (1990) · National Bureau of Economic Research · doi:10.3386/w3223 · Cited by 5,670 · see citing works
Robots and Jobs: Evidence from US Labor Markets
Acemoglu, D., & Restrepo, P. (2020) · Journal of Political Economy · doi:10.1086/705716 · Cited by 4,088 · see citing works
The growth of low-skill service jobs and the polarization of the US labor market
Autor, D. H., & Dorn, D. (2013) · American Economic Review · doi:10.1257/aer.103.5.1553 · Cited by 3,824 · see citing works
Market value and patent citationsPreprint
Hall, B. H., Jaffe, A. B., & Trajtenberg, M. (2005) · RePEc: Research Papers in Economics · Cited by 3,314 · see citing works
Acemoglu, D., & Restrepo, P. (2018) · American Economic Review · doi:10.1257/aer.20160696 · Cited by 3,121 · see citing works
The Skill Content of Recent Technological Change: An Empirical Exploration
Autor, D., Levy, F. S., & Murnane, R. J. (2001) · National Bureau of Economic Research · doi:10.3386/w8337 · Cited by 2,633 · see citing works
Automation and New Tasks: How Technology Displaces and Reinstates Labor
Acemoglu, D., & Restrepo, P. (2019) · Journal of Economic Perspectives · doi:10.1257/jep.33.2.3 · Cited by 2,612 · see citing works
The productivity paradox of information technology
Brynjolfsson, E. (1993) · Communications of the ACM · doi:10.1145/163298.163309 · Cited by 2,526 · see citing works
Graetz, G., & Michaels, G. (2018) · The Review of Economics and Statistics · doi:10.1162/rest_a_00754 · Cited by 2,002 · see citing works
The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms
Makridakis, S. (2017) · Futures · doi:10.1016/j.futures.2017.03.006 · Cited by 1,866 · cited 1× · see citing works
“…Telecommunication Union, Geneva, Switzerland 4 UNU-MERIT, Maastricht, The Netherlands 2 Eurasian Business Review (2021) 11:1–25 1 3 services, transportation and logistics, or service provision have triggered an intense debate on the present and future impact of AI on society (Makridakis 2017).”
BackgroundGMM estimation with persistent panel data: an application to production functions
Blundell, R. W., & Bond, S. R. (1999) · Working paper series - Institute for Fiscal Studies/Working papers · doi:10.1920/wp.ifs.1999.9904 · Cited by 1,671 · see citing works
GMM Estimation with persistent panel data: an application to production functions
Blundell, R. W., & Bond, S. R. (2000) · Econometric Reviews · doi:10.1080/07474930008800475 · Cited by 1,623 · see citing works
Rand Corporation (2010) · The RAND Journal of Economics · doi:10.1111/(issn)1756-2171 · Cited by 1,589 · see citing works
Citations, family size, opposition and the value of patent rights
Harhoff, D., Scherer, F. M., & Vopel, K. (2002) · Research Policy · doi:10.1016/s0048-7333(02)00124-5 · Cited by 1,510 · see citing works
The Rise and Fall of American Growth
Gordon, R. J. (2016) · Princeton University Press eBooks · doi:10.1515/9781400873302 · Cited by 1,312 · see citing works
The Burden of Knowledge and the “Death of the Renaissance Man”: Is Innovation Getting Harder?
JONES, B. F. (2009) · Review of Economic Studies · doi:10.1111/j.1467-937x.2008.00531.x · Cited by 1,058 · see citing works
Exploring the relationship between R&D and productivity in French manufacturing firms
Hall, B. H., & Mairesse, J. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01604-x · Cited by 1,045 · see citing works
Are Ideas Getting Harder to Find?
Bloom, N., Jones, C. I., Van Reenen, J., & Webb, M. (2020) · American Economic Review · doi:10.1257/aer.20180338 · Cited by 1,002 · see citing works
Artificial Intelligence, Automation and Work
Acemoglu, D., & Restrepo, P. (2018) · doi:10.3386/w24196 · Cited by 962 · see citing works
Robots and Jobs: Evidence from US Labor Markets
Acemoğlu, D., & Restrepo, P. (2017) · National Bureau of Economic Research · doi:10.3386/w23285 · Cited by 924 · see citing works
Revision of the High-Technology Sector and Product Classification
Hatzichronoglou, T. (1997) · doi:10.1787/050148678127 · Cited by 860 · see citing works
Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics
Brynjolfsson, E., Rock, D., & Syverson, C. (2017) · National Bureau of Economic Research · doi:10.3386/w24001 · Cited by 805 · see citing works
The rise and fall of American growth: the U.S. standard of living since the Civil War
(2016) · Choice Reviews Online · doi:10.5860/choice.196563 · Cited by 781 · see citing works
Handbook of Labor, Human Resources and Population Economics
Moramarco, D., Palmisano, F., & Peragine, V. (2019) · Springer eBooks · doi:10.1007/978-3-319-57365-6 · Cited by 616 · see citing works
The Impact of Artificial Intelligence on Innovation
Cockburn, I., Henderson, R. M., & Stern, S. (2018) · National Bureau of Economic Research · doi:10.3386/w24449 · Cited by 579 · see citing works
The Choice between Formal and Informal Intellectual Property: A Review
Hall, B. H., Christian Helmers, B., Rogers, M. L., & Sena, V. (2014) · Journal of Economic Literature · doi:10.1257/jel.52.2.375 · Cited by 553 · see citing works
Furman, J., & Seamans, R. (2018) · Innovation Policy and the Economy · doi:10.1086/699936 · Cited by 512 · see citing works
Hall, B. H., Jacques Mairesse, B., & Mohnen, P. (2009) · National Bureau of Economic Research · doi:10.3386/w15622 · Cited by 463 · see citing works
Squicciarini, M., Dernis, H., & Criscuolo, C. (2013) · OECD science, technology and industry working papers · doi:10.1787/5k4522wkw1r8-en · Cited by 310 · see citing works
The impact of the economic crisis on innovation: Evidence from Europe
Archibugi, D., Filippetti, A., & Frenz, M. (2013) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2013.05.005 · Cited by 293 · see citing works
OECD Science, Technology and Industry Scoreboard 2017
OECD (2017) · OECD science, technology and industry scoreboard · doi:10.1787/9789264268821-en · Cited by 285 · see citing works
The Productivity Effects of Internal and External R&D: Evidence from a Dynamic Panel Data Model*
Boris Lokshin, A., Belderbos, R., & Carree, M. (2008) · Oxford Bulletin of Economics and Statistics · doi:10.1111/j.1468-0084.2008.00503.x · Cited by 258 · see citing works
Measuring Total Factor Productivity at the Firm Level using OECD-ORBIS
Gál, P. (2013) · OECD Economics Department working papers · doi:10.1787/5k46dsb25ls6-en · Cited by 237 · see citing works
Global Productivity: Trends, Drivers, and Policies
Dieppe, A. (2020) · World Bank, Washington, DC eBooks · doi:10.1596/978-1-4648-1608-6 · Cited by 204 · see citing works
Innovation and Employment: Evidence from Italian Microdata
Piva, M., & Vivarelli, M. (2005) · Journal of Economics · doi:10.1007/s00712-005-0140-z · Cited by 203 · see citing works
Trends and priority shifts in artificial intelligence technology invention: A global patent analysis
Fujii, H., & Managi, S. (2018) · Economic Analysis and Policy · doi:10.1016/j.eap.2017.12.006 · Cited by 202 · see citing works
Roy, V. V., Vértesy, D., & Vivarelli, M. (2018) · Research Policy · doi:10.1016/j.respol.2018.06.008 · Cited by 191 · see citing works
R&D, Scope Economies, and Plant Performance
Klette, T. J. (1996) · The RAND Journal of Economics · doi:10.2307/2555841 · Cited by 178 · see citing works
R&D and employment: An application of the LSDVC estimator using European microdata
Bogliacino, F., Piva, M., & Vivarelli, M. (2012) · Economics Letters · doi:10.1016/j.econlet.2012.01.010 · Cited by 175 · see citing works
The economics of technology and employment : theory and empirical evidence
Vivarelli, M. (1995) · Medical Entomology and Zoology · Cited by 154 · see citing works
The Economics of Technology and Employment
Vivarelli, M. (1995) · Edward Elgar Publishing eBooks · doi:10.4337/9781035303151 · Cited by 150 · see citing works
IS SILENCE GOLDEN? PATENTS VERSUS SECRECY AT THE FIRM LEVEL
Hussinger, K. (2006) · Economics of Innovation and New Technology · doi:10.1080/10438590500510467 · Cited by 123 · see citing works
Artificial intelligence : a European perspective
Annoni, A., Benczúr, P., Bertoldi, P., Delipetrev, B., Prato, G. D., Feijoo, C., Macias, E. F., Gutierrez, E. G., Portela, M. I., Junklewitz, H., et al. (2018) · EUR · doi:10.2760/11251 · Cited by 121 · see citing works
Utilization of R&D Results in the Home and Foreign Plants of Multinationals
Fors, G. (1997) · Journal of Industrial Economics · doi:10.1111/1467-6451.00052 · Cited by 117 · see citing works
AI, Labor, Productivity and the Need for Firm-Level Data
Seamans, R., & Raj, M. (2018) · doi:10.3386/w24239 · Cited by 117 · see citing works
Why Has Economic Growth Slowed When Innovation Appears to be Accelerating?
Gordon, R. J. (2018) · National Bureau of Economic Research · doi:10.3386/w24554 · Cited by 113 · see citing works
The Economics of Artificial Intelligence: An Agenda
Agrawal, A. K., Gans, J. S., & Avi Goldfarb, B. (2019) · RePEc: Research Papers in Economics · doi:10.7208/chicago/9780226613475.001.0001 · Cited by 112 · see citing works
Artificial intelligence : a European perspective
(2018) · EUR · doi:10.2760/936974 · Cited by 111 · see citing works
Technology, Employment and Skills: An Interpretative Framework
Vivarelli, M. (2013) · Eurasian economic review : · doi:10.14208/bf03353818 · Cited by 110 · see citing works
Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence
Agrawal, A. K., Gans, J. S., & Avi Goldfarb, B. (2018) · National Bureau of Economic Research · doi:10.3386/w24243 · Cited by 106 · see citing works
Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth
Agrawal, A., McHale, J., & Oettl, A. (2018) · National Bureau of Economic Research · doi:10.3386/w24541 · Cited by 83 · see citing works
Belderbos, R., Boris Lokshin, A., & Sadowski, B. M. (2014) · Journal of International Business Studies · doi:10.1057/jibs.2014.63 · Cited by 81 · see citing works
Bartelsman, E. J., Falk, M., Hagsten, E., & Polder, M. (2018) · Eurasian economic review : · doi:10.1007/s40821-018-0113-0 · Cited by 74 · see citing works
AI, Labor, Productivity, and the Need for Firm-Level Data
Raj, M., & Seamans, R. (2019) · University of Chicago Press eBooks · doi:10.7208/chicago/9780226613475.003.0022 · Cited by 72 · see citing works
International and domestic technology transfers and productivity growth: firm level evidence
Belderbos, R., Roy, V. V., & Duvivier, F. (2012) · Industrial and Corporate Change · doi:10.1093/icc/dts012 · Cited by 64 · see citing works
R&D and productivity in the US and the EU: Sectoral specificities and differences in the crisis
Castellani, D., Piva, M., Schubert, T., & Vivarelli, M. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2018.10.001 · Cited by 60 · see citing works
The productivity impact of R&D investment: are high-tech sectors still ahead?
Ortega‐Argilés, R., Piva, M., & Vivarelli, M. (2014) · Economics of Innovation and New Technology · doi:10.1080/10438599.2014.918440 · Cited by 58 · see citing works
Job Creation in Europe: A firm-level analysis
Hallak, I., & Peter, H. (2019) · Joint Research Centre (European Commission) · doi:10.2760/590043 · Cited by 57 · see citing works
Klinger, J. A., Mateos-Garcia, J. C., & Stathoulopoulos, K. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3233463 · Cited by 55 · see citing works
Accumulation of R&D Capital and Dynamic Firm Performance: A Not-so-Fixed Effect Model
Klette, & Johansen (1998) · Annales d Économie et de Statistique · doi:10.2307/20076123 · Cited by 51 · see citing works
Roy, V. V., Vértesy, D., & Damioli, G. (2020) · Springer eBooks · doi:10.1007/978-3-319-57365-6_12-1 · Cited by 48 · see citing works
Self-citationIs Innovation Destroying Jobs? Firm-Level Evidence from the EU
Piva, M., & Vivarelli, M. (2018) · Sustainability · doi:10.3390/su10041279 · Cited by 45 · see citing works
Artificial Intelligence, Jobs, Inequality and Productivity: Does Aggregate Demand Matter?Preprint
Gries, T., & Naudé, W. A. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3301777 · Cited by 44 · see citing works
Testing the Employment and Skill Impact of New Technologies
Barbieri, L., Mussida, C., Piva, M., & Vivarelli, M. (2020) · Springer eBooks · doi:10.1007/978-3-319-57365-6_1-1 · Cited by 39 · see citing works
Gambardella, A., Harhoff, D., & Verspagen, B. (2008) · European Management Review · doi:10.1057/emr.2008.10 · Cited by 29 · see citing works
Breakthrough Technologies - Robotics, Innovation and Intellectual PropertyPreprint
Keisner, C. A., Raffo, J. D., & Wunsch-Vincent, S. A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4434131 · Cited by 16 · see citing works
Robots at Work: Automatable and Non Automatable JobsPreprint
Josten, C., & Lordan, G. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3435395 · Cited by 14 · see citing works
The AI Techno-Economic Segment AnalysisPreprint
Giuditta, D. P., Montserrat, L. C., Samoili, S., Righi, R., Miguel, V.-P. B., & Melisande, C. (2019) · RePEc: Research Papers in Economics · doi:10.2760/576586 · Cited by 7 · see citing works
Flagged first, then by citations
3 of the 84 references couldn’t be matched to a known paper.
Research works printed but not linked: 5
- Bianchini, S., Muller, M., & Pelletier, P. (2020b). Deep learning in science . arXiv :2009.01575 v2. · arXiv
- Ertel, W. (2018). Introduction to artificial intelligence: Undergraduate topics in computer science . New-York: Springer International Publishing.
- European Commission (2003). Commission recommendation of 6 May 2003 concerning the definition of micro, small and medium-sized enterprises. Official Journal of European Union , L124/36.
- Ernst, H. (1995). Patenting strategies in the German mechanical engineering industry and their relationship to firm performance. Technovation, 15 (225), 240.
- Solow, R. (1987). We'd better watch out, New York Times Book Review, July 12, p. 36.
Cited by
Sorted by citations
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927 · see citing works
Yang, C. (2022) · Research Policy · doi:10.1016/j.respol.2022.104536 · Cited by 579 · see citing works
Artificial intelligence and firm-level productivity
Dirk Czarnitzki, A., Fernández, G. P., & Rammer, C. (2023) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2023.05.008 · Cited by 496 · see citing works
Khogali, H. O., & Mekid, S. (2023) · Technology and Society · doi:10.1016/j.techsoc.2023.102232 · Cited by 253 · see citing works
The Regional Development Trap in Europe
Diemer, A., Iammarino, S., Rodríguez‐Pose, A., & Storper, M. (2022) · Economic Geography · doi:10.1080/00130095.2022.2080655 · Cited by 244 · see citing works
Li, C., Xu, Y., Zheng, H., Wang, Z., Han, H., & Zeng, L. (2023) · Resources Policy · doi:10.1016/j.resourpol.2023.103324 · Cited by 231 · see citing works
Artificial Intelligence Technology Innovation and Firm Productivity: Evidence from China
Zhai, S.-X., & Liu, Z.-P. (2023) · Finance Research Letters · doi:10.1016/j.frl.2023.104437 · Cited by 215 · see citing works
AI-generated research paper fabrication and plagiarism in the scientific community
Elali, F. R., & Rachid, L. N. (2023) · Patterns · doi:10.1016/j.patter.2023.100706 · Cited by 197 · see citing works
Artificial intelligence and radical innovation: an opportunity for all companies?
Grashof, N., & Kopka, A. (2022) · Small Business Economics · doi:10.1007/s11187-022-00698-3 · Cited by 192 · see citing works
Artificial intelligence and productivity: global evidence from AI patent and bibliometric data
Parteka, A., & Kordalska, A. (2023) · Technovation · doi:10.1016/j.technovation.2023.102764 · Cited by 168 · see citing works
Artificial intelligence, firms and consumer behavior: A survey
Abrardi, L., Cambini, C., & Rondi, L. (2019) · Journal of Economic Surveys · doi:10.1111/joes.12455 · Cited by 212 · see citing works
Identifying artificial intelligence (AI) invention: a novel AI patent dataset
Giczy, A. V., Pairolero, N. A., & Toole, A. A. (2021) · The Journal of Technology Transfer · doi:10.1007/s10961-021-09900-2 · Cited by 155 · see citing works
Madanaguli, A. T., Sjödin, D., Parida, V., & Mikalef, P. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123189 · Cited by 185 · see citing works
Hajkowicz, S. A., Sanderson, C., Karimi, S., Bratanova, A., & Naughtin, C. K. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102260 · Cited by 155 · see citing works
Zhang, Z. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122881 · Cited by 155 · see citing works
Kassa, B. Y., & Worku, E. K. (2025) · Journal of Open Innovation Technology Market and Complexity · doi:10.1016/j.joitmc.2025.100474 · Cited by 196 · see citing works
Yang, S., & Liu, F. (2023) · Ecological Economics · doi:10.1016/j.ecolecon.2023.108021 · Cited by 129 · see citing works
Kar, S., Kar, A. K., & Gupta, M. P. (2021) · Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management · doi:10.1002/isaf.1503 · Cited by 122 · see citing works
Wang, K.-L., Sun, T.-T., & Xu, R.-Y. (2022) · Economic Change and Restructuring · doi:10.1007/s10644-022-09467-4 · Cited by 129 · see citing works
Ayinaddis, S. G. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100682 · Cited by 172 · see citing works
Lee, C., Fang, Y., Quan, S., & Li, X. (2024) · Energy Economics · doi:10.1016/j.eneco.2024.107654 · Cited by 112 · see citing works
Generative AI: Opportunities, challenges, and research directions for supply chain resilience
Boone, T., Fahimnia, B., Ganeshan, R., Herold, D. M., & Sanders, N. R. (2025) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2025.104135 · Cited by 109 · see citing works
Soomro, R., Al-rahmi, W., Dahri, N. A., Almuqren, L., Almogren, A. S., & Aldaijy, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-86464-3 · Cited by 112 · see citing works
Feng, C. Q., Ye, X., Li, J., & Yang, J. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2023.119923 · Cited by 103 · see citing works
Song, M., Pan, H., Shen, Z., & Tamayo‐Verleene, K. (2024) · Energy Economics · doi:10.1016/j.eneco.2024.107392 · Cited by 97 · see citing works
Kopka, A., & Fornahl, D. (2023) · Small Business Economics · doi:10.1007/s11187-023-00754-6 · Cited by 91 · see citing works
Hwang, W., & Kim, H.-S. (2021) · Small Business Economics · doi:10.1007/s11187-021-00554-w · Cited by 78 · see citing works
AI technologies and employment: micro evidence from the supply side
Damioli, G., Roy, V. V., Vértesy, D., & Vivarelli, M. (2022) · Applied Economics Letters · doi:10.1080/13504851.2021.2024129 · Cited by 79 · see citing works
Self-citationThe role of industrial intelligence in peaking carbon emissions in China
Wang, L., Chen, Q., Dong, Z., & Cheng, L. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123005 · Cited by 72 · see citing works
The empirics of technology, employment and occupations: Lessons learned and challenges ahead
Montobbio, F., Staccioli, J., Virgillito, M. E., & Vivarelli, M. (2023) · Journal of Economic Surveys · doi:10.1111/joes.12601 · Cited by 66 · see citing works
Luo, Q., & Feng, P. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2024.142739 · Cited by 72 · see citing works
Wang, S., Huang, X., Xia, M., & Shi, X. (2024) · Journal of the Knowledge Economy · doi:10.1007/s13132-023-01707-w · Cited by 68 · see citing works
Saba, C. S., & Ngepah, N. N. (2024) · Research in Globalization · doi:10.1016/j.resglo.2024.100213 · Cited by 73 · see citing works
AI-Powered E-Learning for Lifelong Learners: Impact on Performance and Knowledge Application
Ahn, H. Y. (2024) · Sustainability · doi:10.3390/su16209066 · Cited by 56 · see citing works
Artificial intelligence and green transformation of manufacturing enterprises
Zhou, C., Zhang, H., Ying, J., He, S., Zhang, C., & Yan, J. (2025) · International Review of Financial Analysis · doi:10.1016/j.irfa.2025.104330 · Cited by 51 · see citing works
Kalai, M., Becha, H., ABDALLAH, A. B., & Helali, K. (2024) · Journal of Economic Structures · doi:10.1186/s40008-024-00345-y · Cited by 59 · see citing works
Impacts of generative artificial intelligence on the future of labor market: a systematic review
Salari, N., Beiromvand, M., Hosseinian-Far, A., Habibi, J., Babajani, F., & Mohammadi, M. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100652 · Cited by 49 · see citing works
“The rapid development of AI creates many economic benefits (Damioli et al., 2021; Sequeira et al., 2021).”
Yılmaz, Ö. (2024) · Educational Technology Quarterly · doi:10.55056/etq.744 · Cited by 49 · see citing works
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Self-citationDoes Artificial Intelligence Promote or Inhibit On-the-Job Learning? Human Reactions to AI at Work
Li, C., Zhang, Y., Niu, X., Chen, F., & Zhou, H. (2023) · Systems · doi:10.3390/systems11030114 · Cited by 52 · see citing works
Sun, T., Li, R., & Wang, Q. (2025) · Sustainable Development · doi:10.1002/sd.70547 · Cited by 46 · see citing works
Liu, X., & Li, Y. (2025) · Behavioral Sciences · doi:10.3390/bs15020206 · Cited by 58 · see citing works
Wu, X., & Zhu, Y. (2025) · Journal of Asian Economics · doi:10.1016/j.asieco.2025.101893 · Cited by 43 · see citing works
Is artificial intelligence leading to a new technological paradigm?
Damioli, G., Roy, V. V., Vértesy, D., & Vivarelli, M. (2024) · Structural Change and Economic Dynamics · doi:10.1016/j.strueco.2024.12.006 · Cited by 48 · see citing works
Self-citationInvestment, innovation activities and employment across European regions
Destefanis, S., & Rehman, N. U. (2023) · Structural Change and Economic Dynamics · doi:10.1016/j.strueco.2023.03.013 · Cited by 37 · see citing works
Artificial Intelligence and Firm Performance: Does Machine Intelligence Shield Firms from Risks?
Ho, L., Gan, C., Jin, S., & Le, B. (2022) · Journal of Risk and Financial Management · doi:10.3390/jrfm15070302 · Cited by 28 · see citing works
Automation and Related Technologies: A Mapping of the New Knowledge Base
Santarelli, E., Staccioli, J., & Vivarelli, M. (2022) · The Journal of Technology Transfer · doi:10.1007/s10961-021-09914-w · Cited by 42 · see citing works
The impact of Artificial Intelligence on productivity, distribution and growth
Filippucci, F., Gál, P., Jona‐Lasinio, C., Leandro, Á., & Nicoletti, G. (2024) · OECD artificial intelligence papers · doi:10.1787/8d900037-en · Cited by 85 · see citing works
Arboh, F., Zhu, X., Atingabili, S., Yeboah, E., & Drokow, E. K. (2025) · Journal of Health Organization and Management · doi:10.1108/jhom-06-2024-0229 · Cited by 42 · see citing works
A portrait of AI adopters across countries
Calvino, F., & Fontanelli, L. (2023) · OECD science, technology and industry working papers · doi:10.1787/0fb79bb9-en · Cited by 68 · see citing works
Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe
Marioni, L. D. S., Rincón-Aznar, A., & Venturini, F. (2024) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2024.106762 · Cited by 37 · see citing works
Virtual influencers and corporate reputation: from marketing game to empirical analysis
Xin, B., Hao, Y., & Xie, L. (2024) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-10-2023-0330 · Cited by 30 · see citing works
Environmental protection taxes and green productivity: Evidence from listed companies in China
Yan, Z., Jia, Y., & Zhang, B. (2024) · Economic Systems · doi:10.1016/j.ecosys.2024.101213 · Cited by 36 · see citing works
Wang, L., Cao, Z., & Dong, Z. (2023) · Structural Change and Economic Dynamics · doi:10.1016/j.strueco.2023.05.010 · Cited by 32 · see citing works
The impact of digital infrastructure on labor productivity
Zhao, X., & Liu, J. (2025) · Economic Analysis and Policy · doi:10.1016/j.eap.2025.03.030 · Cited by 29 · see citing works
The role of intangibles in firm-level productivity – evidence from Germany
Roth, F., Şen, A., & Rammer, C. (2022) · Industry and Innovation · doi:10.1080/13662716.2022.2138280 · Cited by 29 · see citing works
Reslan, F. B., & Maalouf, N. J. A. (2024) · Journal of risk and financial management · doi:10.3390/jrfm17120577 · Cited by 46 · see citing works
Towards AI ethics-led sustainability frameworks and toolkits: Review and research agenda
Cumming, D., Saurabh, K., Rani, N., & Upadhyay, P. (2024) · Journal of Sustainable Finance and Accounting · doi:10.1016/j.josfa.2024.100003 · Cited by 16 · see citing works
Innovation and productivity: the recent empirical literature and the state of the art
Jacques Mairesse, B., Mohnen, P., & Notten, A. (2025) · Eurasian economic review : · doi:10.1007/s40821-025-00295-w · Cited by 24 · see citing works
Impact of industrial robot on labour productivity: Empirical study based on industry panel data
Zhao, Y., Said, R. B., Ismail, N. W., & Hamzah, H. Z. (2024) · Innovation and Green Development · doi:10.1016/j.igd.2024.100148 · Cited by 23 · see citing works
D’Amico, E., Belitski, M., Braga, A., & Savoie, R. (2025) · The Journal of Technology Transfer · doi:10.1007/s10961-025-10217-7 · Cited by 30 · see citing works
Torrent‐Sellens, J., Enache, M., & Ficapal‐Cusí, P. (2025) · Business Strategy and the Environment · doi:10.1002/bse.70068 · Cited by 28 · see citing works
Chen, Y., Huang, X., & Liu, C. (2025) · Journal of Environmental Management · doi:10.1016/j.jenvman.2025.126455 · Cited by 21 · see citing works
Does artificial intelligence (AI) reduce ecological footprint? The role of globalization
Wang, Q., Sun, T., & Li, R. (2023) · Environmental Science and Pollution Research · doi:10.1007/s11356-023-31076-5 · Cited by 21 · see citing works
Translating technological innovation into efficiency: the case of US public P&C insurance companies
Lanfranchi, D., & Grassi, L. (2021) · Eurasian economic review : · doi:10.1007/s40821-021-00189-7 · Cited by 20 · see citing works
Experimental Evidence on Negative Impact of Generative AI on Scientific Learning OutcomesPreprint
Ju, Q. (2023) · Research Square · doi:10.21203/rs.3.rs-3371292/v1 · Cited by 20 · see citing works
Disrupting regional efficiency gaps via Industry 4.0 firm investments
Forgione, A. F., & Migliardo, C. (2022) · Industry and Innovation · doi:10.1080/13662716.2022.2063111 · Cited by 19 · see citing works
The AI trilemma: Saving the planet without ruining our jobs
Ernst, E. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.886561 · Cited by 21 · see citing works
Adopting Artificial Intelligence in Healthcare
Mouloudj, K., Vu Lan Oanh, L. E., Bouarar, A., Bouarar, A. C., Asanza, D. M., & Srivastava, M. (2023) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/978-1-6684-9324-3.ch001 · Cited by 19 · see citing works
Li, C., Zhang, Y., Li, X., & Hao, Y. (2023) · Resources Policy · doi:10.1016/j.resourpol.2023.104469 · Cited by 20 · see citing works
Artificial intelligence and financial fraud
Sun, G., Ling, Z., Li, Y., & Xie, C. (2025) · Pacific-Basin Finance Journal · doi:10.1016/j.pacfin.2025.102830 · Cited by 23 · see citing works
Top R&D investors, structural change and the R&D growth performance of young and old firms
Moncada-Paternò-Castello, P. (2022) · Eurasian economic review : · doi:10.1007/s40821-022-00206-3 · Cited by 17 · see citing works
Li, Y., Deng, J., Hu, Z., & Gong, B. (2022) · Emerging Markets Finance and Trade · doi:10.1080/1540496x.2022.2096433 · Cited by 17 · see citing works
Multifactor productivity growth enhancers across industries and countries: firm-level evidence
Nakatani, R. (2024) · Eurasian economic review : · doi:10.1007/s40821-024-00265-8 · Cited by 17 · see citing works
Artificial intelligence and socioeconomic forces: transforming the landscape of religion
He, Y. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03137-8 · Cited by 16 · see citing works
Mammadov, H., Gándara, Á. R., Abril, L. G., & Romero, I. (2024) · Amfiteatru Economic · doi:10.24818/ea/2024/67/848 · Cited by 16 · see citing works
Niu, X., Li, C., Li, X., & Zhang, Y. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e25087 · Cited by 17 · see citing works
The Impact of Artificial Intelligence on Human Workers
Farhan, A. (2023) · Journal Of Communication Education · doi:10.58217/joce-ip.v17i2.350 · Cited by 16 · see citing works
AI, Demand and the Impact of Productivity-enhancing Technology on Jobs: Evidence from Portugal
Bação, P., Lopes, V. G. B., & Simões, M. C. N. (2022) · Eastern European Economics · doi:10.1080/00128775.2022.2064307 · Cited by 16 · see citing works
Wang, Z., Feng, T., & Zhang, Y. (2025) · Journal of Environmental Management · doi:10.1016/j.jenvman.2025.126596 · Cited by 16 · see citing works
Experimental Evidence on Negative Impact of Generative AI on Scientific Learning OutcomesPreprint
Ju, Q. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4567696 · Cited by 14 · see citing works
Zhang, W., Fu, S., Chiu, Y., & Hsiao, C. Y. (2025) · Energy Economics · doi:10.1016/j.eneco.2025.108687 · Cited by 13 · see citing works
Chowdhury, F., Link, A. N., & van Hasselt, M. (2022) · The Journal of Technology Transfer · doi:10.1007/s10961-022-09943-z · Cited by 13 · see citing works
AI-driven carbon total factor productivity: Strategic lens on industrial enterprises
Han, Z., & Wang, L. (2025) · Energy · doi:10.1016/j.energy.2025.138259 · Cited by 12 · see citing works
The impact of artificial intelligence on unemployment: a review
Virgilio, G. P. M., Hoyos, F. S., & Ratzemberg, C. B. B. (2024) · International Journal of Social Economics · doi:10.1108/ijse-05-2023-0338 · Cited by 19 · see citing works
Climate policy and corporate artificial intelligence: Evidence from low-carbon city pilots in China
Longsheng, W., Qi, L., Lam, J. F. I., & Chen, G. (2024) · Environmental and Sustainability Indicators · doi:10.1016/j.indic.2024.100446 · Cited by 12 · see citing works
A Review of AI and Its Impact on Management Accounting and Society
Kerr, D., Smith, K., Smith, L., & Xu, T. (2025) · Journal of Risk and Financial Management · doi:10.3390/jrfm18060340 · Cited by 14 · see citing works
A new green transition driver: How does artificial intelligence affect the green economic efficiency
Lin, B., & Zhou, D. (2025) · Energy · doi:10.1016/j.energy.2025.137808 · Cited by 12 · see citing works
Modliński, A. (2022) · AI & Society · doi:10.1007/s00146-022-01534-8 · Cited by 12 · see citing works
Board busyness and firm productivity
Bazrafshan, A., & Hesarzadeh, R. (2021) · Personnel Review · doi:10.1108/pr-07-2019-0375 · Cited by 12 · see citing works
Identifying and characterising AI adopters
Calvino, F., Samek, L., Squicciarini, M., & Morris, C. (2022) · OECD science, technology and industry working papers · doi:10.1787/154981d7-en · Cited by 24 · see citing works
Han, X., Xu, W., & Jian-ping, Z. (2026) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100926 · Cited by 11 · see citing works
Popkova, E. G., Bogoviz, A. V., Ekimova, K. V., & Sergi, B. S. (2023) · International Journal of Innovation Studies · doi:10.1016/j.ijis.2023.05.001 · Cited by 11 · see citing works
Artificial intelligence and religious freedom: divergent paths converging on economic expansion
He, Y. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-02642-0 · Cited by 14 · see citing works
The upheaval years: a literature review on firms’ digitalization new era
Jung, J., & Bengoechea, G. G. (2024) · Economics of Innovation and New Technology · doi:10.1080/10438599.2024.2328538 · Cited by 12 · see citing works
Singh, S., Yadav, S., Singh, A., Krishna, Y. J., & Singh, A. (2024) · Studies in systems, decision and control · doi:10.1007/978-3-031-63402-4_30 · Cited by 11 · see citing works
Yapay Zekâ ve Sinema: Film Yapımında Olanaklar ve Fırsatlar
Türten, B. (2024) · Anadolu ve Balkan Araştırmaları Dergisi · doi:10.32953/abad.1539736 · Cited by 11 · see citing works
Does regional AI development improve corporate supply chain efficiency? Evidence from China
Wang, W., Huang, H. F., & Fu, X. (2025) · International Review of Economics & Finance · doi:10.1016/j.iref.2025.104597 · Cited by 12 · see citing works
AI technology adoption and corporate financial misconduct
Khalid, F., Srivastava, M., & Toumi, F. (2025) · Journal of financial reporting & accounting · doi:10.1108/jfra-06-2025-0474 · Cited by 10 · see citing works
Park, G., Kang, S., Yi, S., & Kim, J. (2025) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2025.124471 · Cited by 13 · see citing works
- Authors
- Damioli, G., Van Roy, V., & Vertesy, D.
- Affiliations
- Joint Research Centre (IT)
- Corresponding author
- Damioli, Giacomo
- ORCID
- Damioli, Giacomo
- Venue
- Eurasian Business Review
- Published
- 2021-01-21
- Volume
- 11
- Issue
- 1
- Pages
- 1-25
- ISSN
- 1309-422X (ISSN-L)
- 1309-4297
- 2147-4281
- OpenAlex
- W3124534840
- Cited by
- 345
- References
- 84
- Citations by year
- 2026: 87 · 2025: 112 · 2024: 76 · 2023: 40 · 2022: 22 · 2021: 8
- FWCI
- 27.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Eurasian economic review : (publishedVersion, cc-by)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion, cc-by)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- Horizon 2020 Framework Programme (857088)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Growth and Productivity
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Firm Innovation and Growth
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- artificial intelligence, labor productivity, AI patents, robotics, firm productivity, small and medium-sized enterprises, service sector, technology adoption, patent activity
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