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Unlocking the AI-Productivity paradox in HR: Qualitative insights across organizational levels

Author

Listed:
  • Khalil, Ashraf
  • Agarwal, Reeti
  • Yaqub, Muhammad Zafar
  • Papa, Armando

Abstract

Artificial Intelligence (AI) is widely expected to boost productivity and economic growth. As with other technological innovations, a productivity paradox emerges, stating that productivity falls upon its introduction. Therefore, while organizations consistently augment their investments in AI, they might fall short of significant productivity improvements. This study delves into this productivity paradox using a longitudinal qualitative research design with two waves of data collection. We explored four critical themes: AI’s evolving role in organizations, its tangible effects on HR productivity, the underlying reasons behind the productivity paradox, and its multifaceted impact on the employee, team, and organizational levels. Our findings reveal compelling insights into why increased AI investments may not always translate into immediate productivity gains. In addition to providing a framework outlining the relationship between AI and the productivity paradox in HR operations, the findings offer insightful information that can be extremely helpful to industry practitioners.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jbrese:v:199:y:2025:i:c:s0148296325002796
    DOI: 10.1016/j.jbusres.2025.115456
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    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. Neelam Kaushal & Rahul Pratap Singh Kaurav & Brijesh Sivathanu & Neeraj Kaushik, 2023. "Artificial intelligence and HRM: identifying future research Agenda using systematic literature review and bibliometric analysis," Management Review Quarterly, Springer, vol. 73(2), pages 455-493, June.
    3. Prikshat, Verma & Islam, Mohammad & Patel, Parth & Malik, Ashish & Budhwar, Pawan & Gupta, Suraksha, 2023. "AI-Augmented HRM: Literature review and a proposed multilevel framework for future research," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    4. Lin, Winston T. & Chen, Yueh H. & Chou, Chia-Ching, 2021. "Assessing the business values of e-commerce and information technology separately and jointly and their impacts upon US firms' performance as measured by productive efficiency," International Journal of Production Economics, Elsevier, vol. 241(C).
    5. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    6. Dwivedi, Yogesh K. & Hughes, Laurie & Ismagilova, Elvira & Aarts, Gert & Coombs, Crispin & Crick, Tom & Duan, Yanqing & Dwivedi, Rohita & Edwards, John & Eirug, Aled & Galanos, Vassilis & Ilavarasan, , 2021. "Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy," International Journal of Information Management, Elsevier, vol. 57(C).
    7. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    8. repec:bjc:journl:v:10:y:2024:i:12:p:423-444 is not listed on IDEAS
    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. Nir Kshetri, 2021. "Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence," Management Research Review, Emerald Group Publishing Limited, vol. 44(7), pages 970-990, January.
    11. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    12. Daron Acemoglu & David Autor & David Dorn & Gordon H. Hanson & Brendan Price, 2014. "Return of the Solow Paradox? IT, Productivity, and Employment in US Manufacturing," American Economic Review, American Economic Association, vol. 104(5), pages 394-399, May.
    13. Miyagawa, Tsutomu & Tonogi, Konomi & Ishikawa, Takayuki, 2021. "Does the productivity J-curve exist in Japan?-Empirical studies based on the multiple q theory," Journal of the Japanese and International Economies, Elsevier, vol. 61(C).
    14. Brendan James Keegan & Denis Dennehy & Peter Naudé, 2024. "Implementing Artificial Intelligence in Traditional B2B Marketing Practices: An Activity Theory Perspective," Information Systems Frontiers, Springer, vol. 26(3), pages 1025-1039, June.
    15. Premilla D’Cruz & Shuili Du & Ernesto Noronha & K. Praveen Parboteeah & Hannah Trittin-Ulbrich & Glen Whelan, 2022. "Technology, Megatrends and Work: Thoughts on the Future of Business Ethics," Journal of Business Ethics, Springer, vol. 180(3), pages 879-902, October.
    16. Zhang, Yi & Wang, Ting & Liu, Chun, 2024. "Beyond the modern productivity paradox: The effect of robotics technology on firm-level total factor productivity in China," Journal of Asian Economics, Elsevier, vol. 90(C).
    17. Prentice, Catherine & Wong, IpKin Anthony & Lin, Zhiwei (CJ), 2023. "Artificial intelligence as a boundary-crossing object for employee engagement and performance," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    18. Mahmood Hajli & Julian M. Sims & Valisher Ibragimov, 2015. "Information technology (IT) productivity paradox in the 21st century," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 64(4), pages 457-478, April.
    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. Nicholas Crafts, 2021. "Artificial intelligence as a general-purpose technology: an historical perspective," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 521-536.
    21. Munshi Naser Ibne Afzal & Abu Hena Nur Shohan & Shamim Siddiqui & Nishat Tasnim, 2023. "Application of AI on Human Resource Management: A Review," Journal of Human Resource Management, Comenius University in Bratislava, Faculty of Management, vol. 26(1), pages 01-11.
    22. 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).
    23. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    24. Nir Kshetri, 2021. "Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence," Management Research Review, Emerald Group Publishing Limited, vol. 44(7), pages 970-990, January.
    25. 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.
    26. Khanna, Rupika & Sharma, Chandan, 2024. "Beyond information technology and productivity paradox: Analysing the channels of impact at the firm-level," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    27. Mahmood Hajli & Julian M. Sims & Valisher Ibragimov, 2015. "Information technology (IT) productivity paradox in the 21st century," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 64(4), pages 457-478, April.
    28. Antonio, Jerome L. & Kanbach, Dominik K., 2023. "Contextual factors of disruptive innovation: A systematic review and framework," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    29. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57, National Bureau of Economic Research, Inc.
    30. Sun, Zhe & Zhao, Liang & Kaur, Puneet & Islam, Nazrul & Dhir, Amandeep, 2023. "Theorizing the relationship between the digital economy and firm productivity: The idiosyncrasies of firm-specific contexts," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    31. Zhiguang ZHANG & Haiqing HU & Winston T. LIN, 2019. "Analyzing the Impacts of Unobserved National Characteristics on Economic Performance of Information Technology based on a Partial Adjustment Approach With Dynamic and Variable Speed of Adjustment," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 128-142, March.
    32. Cubric, Marija, 2020. "Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study," Technology in Society, Elsevier, vol. 62(C).
    33. Novakova, Lucia, 2020. "The impact of technology development on the future of the labour market in the Slovak Republic," Technology in Society, Elsevier, vol. 62(C).
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