Reported and anticipated workforce reconfiguration during artificial intelligence adoption: Firm-level evidence from Slovakia
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DOIhttp://dx.doi.org/10.21511/ppm.24(3).2026.37
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Article InfoVolume 24 2026, Issue #3, pp. 589–610
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Type of the article: Research Article
Abstract
Artificial intelligence (AI) is reshaping how firms design work, yet firm-level evidence compresses employment implications into a single net figure that hides simultaneous hiring and cutting within one firm. The study examines how AI adoption stage, self-assessed AI maturity, orientation, and ownership are associated with the incidence and co-occurrence of realized or planned job creation and elimination. The analytical sample is 693 AI-engaged Slovak firms from a cross-sectional survey (351 current users, 211 pilot firms, 131 planning adoption). Two binary items record whether AI-related positions have been introduced or are planned, and whether AI has led or is expected to lead to layoffs. Each item merges realized with planned or expected action, so the outcomes indicate the incidence of an actual or anticipated event, not the number of positions. We applied exact tests, logistic and multinomial logistic regression, and a bivariate probit model with Benjamin-Hochberg false-discovery-rate (FDR) adjustment. Reported or planned creation was more frequent than elimination (18.0% vs. 9.2%; p < 0.001), and the two co-occurred well beyond chance (odds ratio 7.23; ρ = 0.54). A more advanced adoption stage was associated with a higher incidence of creation (OR 1.49; FDR-adjusted p = 0.004), and employee job-threat concern was associated with a higher incidence of elimination (OR 1.58; p = 0.014). Foreign ownership was associated with joint occurrence of both outcomes in an exploratory model only (RRR 2.29; unadjusted p = 0.027). The study contributes a descriptive typology of four incidence patterns; the cross-sectional design supports associational reading only.
Acknowledgments
The authors thank the AI-ImpactSK project team and all responding firms.
This paper was supported by the European Union – NextGenerationEU through the Recovery and Resilience Plan for Slovakia under project No. 09I05-03-V02-00003/2025/VA (AI-impactSK); 100% share.
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JEL Classification (Paper profile tab)J23, J24, M12, O33
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References54
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Tables5
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Figures7
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- Figure 1. Incidence of reported or planned AI-related job creation and job elimination (N = 693), with 95% Wilson confidence intervals
- Figure 2. Conditional incidence of reported or planned AI-related job elimination by job-creation status, with measures of association
- Figure 3. Predicted probability of reporting AI-related job creation and job elimination (realized or planned) across AI adoption stages
- Figure 4. Adjusted odds ratios for reported or planned AI-related job creation and job elimination
- Figure 5. Relative risk ratios for the three active incidence patterns versus Static firms (multinomial logistic regression, 95% confidence intervals, N = 693)
- Figure 6. Standardized predictor profiles of the four incidence patterns (z-scores, N = 693)
- Figure 7. Incidence of reported or planned AI-related job creation and job elimination by sector group (unadjusted, N = 693)
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- Table 1. Composition of the analytical sample and incidence of the two outcomes
- Table 2. Logistic regressions for reported or planned AI-related job creation and job elimination
- Table 3. Multinomial logistic regression of the four incidence patterns relative to Static firms
- Table 4. Sensitivity and robustness checks: Selected focal estimates
- Table 5. Summary of hypothesis assessment
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- Abdulmawla, M., Mohamed, L. M., & Elgarhy, S. D. (2025). Effects of transformational leadership and intrinsic motivations on organizational innovation in hotels and travel agencies: The mediating roles of organizational citizenship behavior and organizational commitment. Journal of Tourism and Services, 16(30), 1-27.
- Acemoglu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. In O. Ashenfelter & D. Card (Eds.). Handbook of labor economics (Vol. 4B, pp. 1043-1171). Elsevier.
- Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3-30.
- Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188-2244.
- Aldasoro, I., Gambacorta, L., Pal, R., Revoltella, D., Weiss, C., & Wolski, M. (2026). AI adoption, productivity and employment: Evidence from European firms (BIS Working Paper No. 1325). Bank for International Settlements.
- Ali, W., & Khan, A. Z. (2025). Factors influencing readiness for artificial intelligence: A systematic literature review. Data Science and Management, 8(2), 224-236.
- Angeloska, A., Spaller, E., & Vasa, L. (2021). Foreign direct investment, digital skills and employability: Comparison between Eastern and Western Europe. In M. Kordoš (Ed.), The Impact of Industry 4.0 on Job Creation 2020: Proceedings of scientific papers from the international scientific conference (pp. 31-38). Publishing House Alexander Dubček University in Trenčín.
- Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. Quarterly Journal of Economics, 118(4), 1279-1333.
- Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, Article 103745.
- Brynjolfsson, E. (2022). The Turing trap: The promise and peril of human-like artificial intelligence. Daedalus, 151(2), 272-287.
- Brynjolfsson, E., Li, D., & Raymond, L. (2025). Generative AI at work. Quarterly Journal of Economics, 140(2), 889-942.
- Brynjolfsson, E., Rock, D., & Syverson, C. (2021). The productivity J-curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333-372.
- Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Cooke, F.L., Decker, S., DeNisi, A., Dey, P.K., Guest, D., Knoblich, A.J., Malik, A., Paauwe, J., Papagiannidis, S., Patel, Ch., Pereira, V., Ren, Sh., … Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606-659.
- Burkett, M. G., & Recuero Virto, N. (2025). Exploring the role of innovation and perceived security in contactless technology adoption: Evidence from contactless travel services. Journal of Tourism and Services, 16(31), 220-244.
- Černý, M., Andriana, B., Šagátová, S., Hanak, R., Štetka, P., Grisáková, N., Hajduova, Z., & Bolek, V. (2026). AI-IMPACT Survey Dataset (Slovakia) – AI adoption and readiness in Slovakia (Version 1) [Data set]. Zenodo.
- Czarnitzki, D., Fernández, G. P., & Rammer, C. (2023). Artificial intelligence and firm-level productivity. Journal of Economic Behavior & Organization, 211, 188-205.
- Duran, C., Uray, N., & Alkilani, S. (2024). The impact of the characteristics of self-service technologies on customer experience quality: Insights for airline companies. Journal of Tourism and Services, 15(29), 46-71.
- Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2024). GPTs are GPTs: Labor market impact potential of large language models. Science, 384(6702), 1306-1308.
- Fan, G. (2025). Influence of AI on business strategies of music culture communication companies. Transformations in Business & Economics, 24(2(65)), 355-376.
- Fang, R., Feng, X., & Tian, M. (2025). Intention to use generative artificial intelligence for hotel selection among consumers: An explanatory sequential investigation. Journal of Tourism and Services, 16(31), 195-219.
- Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254-280.
- Fügener, A., Walzner, D. D., & Gupta, A. (2026). Roles of artificial intelligence in collaboration with humans: Automation, augmentation, and the future of work. Management Science, 72(1), 538-557.
- Gayathiri, G., & Prabu, G. (2025). Artificial intelligence-driven human resource practices and employee well-being: Examining the mediating effect of employee engagement. Problems and Perspectives in Management, 23(4), 247-263.
- GLOBSEC. (2026). From access to impact: Bridging the gender gap in AI and digital transformation across Central and Eastern European SMEs. GLOBSEC.
- Goos, M., Manning, A., & Salomons, A. (2014). Explaining job polarization: Routine-biased technological change and offshoring. American Economic Review, 104(8), 2509-2526.
- Greene, W. H. (2018). Econometric analysis (8th ed.). Pearson.
- Grenčíková, A., Kordoš, M., & Berkovič, V. (2020). The impact of Industry 4.0 on jobs creation within the small and medium-sized enterprises and family businesses in Slovakia. Administrative Sciences, 10(3), Article 71.
- Grenčíková, A., Kordoš, M., & Sokol, J. (2019). The approach to Industry 4.0 within the Slovak business environment. Social Sciences, 8(4), Article 104.
- Grigoryan, A., Melkumyan, A., Karapetyan, L., Sahakyan, M., Badalyan, M., & Gabrielyan, B. (2025). Challenges and opportunities of artificial intelligence adoption in human resources management within the ICT industry in Armenia. Problems and Perspectives in Management, 23(4), 147-158.
- Hanáčková, D., & Takáč, I. (2024). Innovation performance of V4 countries. Entrepreneurship and Sustainability Issues, 11(4), 293-310.
- Hasan, M., Haque, M. O., Hossain, M. S., Habib, M. A., Amin, M. B., Rahaman, M. A., & Oláh, J. (2025). Revealing major macroeconomic growth factors for an emerging economy: Evidence from half-century of economic resilience. Discover Sustainability, 6(1), Article 589.
- Hassan, M. S., Zahra, F. T., Azad, M. A. K., Amin, M. B., Afrin, S., & Oláh, J. (2026). Mapping the intersection of FinTech and sustainable finance: A systematic bibliometric review and emerging research horizons. Green Technologies and Sustainability, 4(3), Article 100388.
- He, X., Li, T., & Wang, L. (2026). How enterprise digital transformation reshapes risk sharing between banks and enterprises: Based on multiperiod DID analysis. Transformations In Business & Economics, 25(1(67)), 383-417.
- Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes: An interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5-20.
- Křečková, R., Šálková, D., Procházková, R., & Trnka, R. (2025). Determinants of accommodation choice on digital platforms: Price, cleanliness, and trust. Journal of Tourism and Services, 16(31), 173-194.
- Kubičková, V., Mura, L., Halenárová, M., & Chaloupková Košlíková, P. (2026). A new methodological approach to assessing the potential of spa tourism. Journal of Tourism and Services, 17(32), 223-245.
- Lazaroiu, G., Gedeon, T., Valaskova, K., Vrbka, J., Šuleř, P., Zvarikova, K., Kramarova, K., Rowland, Z., Stehel, V., Gajanova, L., Horák, J., Grupac, M., Caha, Z., Blazek, R., Kovalova, E., & Nagy, M. (2024). Cognitive digital twin-based Internet of Robotic Things, multi-sensory extended reality and simulation modeling technologies, and generative artificial intelligence and cyber–physical manufacturing systems in the immersive industrial metaverse. Equilibrium. Quarterly Journal of Economics and Economic Policy, 19(3), 719-748.
- McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153-157.
- Mura, L., & Stehlíková, B. (2025). Artificial intelligence and tourism in the EU: A data-driven analysis of adoption and economic contribution. Folia Geographica, 67(1), 70-99.
- Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187-192.
- Oyasor, E. I. (2025). The role of strategic employee training and human resource management practices in enhancing organizational productivity and innovation. International Journal of Entrepreneurial Knowledge, 13(2), 93-116.
- Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192-210.
- Ramanauskė, N., & Muliuolytė, K. (2026). Rethinking the economic importance of older adults’ employment: A conceptual framework for sustainable labour market transformation in ageing societies. Transformations and Sustainability, 2(2), 116-139.
- Rammer, C., Fernández, G. P., & Czarnitzki, D. (2022). Artificial intelligence and industrial innovation: Evidence from German firm-level data. Research Policy, 51(7), Article 104555.
- Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
- Roy, J. K., & Vasa, L. (2024). Machine learning and artificial intelligence method for FinTech credit scoring and risk management: A systematic literature review. International Journal of Business Analytics, 11(1), 1-23.
- Śledziewska, K., Włoch, R., & Wilamowski, M. (2025). Adapting to digital transformation: Determinants of training motivation in response to digital automation among workers in six EU countries. Oeconomia Copernicana, 16(2), 523-555.
- Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301-328.
- Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
- Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. International Journal of Human Resource Management, 33(6), 1237-1266.
- Xue, L., Satpayeva, Z., Kangalakova, D., & Özen, E. (2025). Trends of artificial intelligence-driven enterprise management development: A bibliometric analysis. Problems and Perspectives in Management, 23(4), 1-12.
- Yu, G. (2025). Digital transformation, human capital upgrading, and enterprise ESG performance: Evidence from Chinese listed enterprises. Oeconomia Copernicana, 15(4), 1465-1508.
- Yu, G., & Qi, Y. (2025). Does AI application make enterprises productivity higher? From the perspective of employee human capital upgrading. Oeconomia Copernicana, 16(4), 1395-1446.
- Zouair, N., Abou-Shouk, M., Idriz, M., & Okleh, I. (2025). The impact of smart technologies on innovative tourist memorable experience and revisit intention: The mediation of technology-task fit. Journal of Tourism and Services, 16(31), 27-45.


