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Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review
Open accessAbstract
Although academic production in intelligent automation (e.g. artificial intelligence, robotics) has grown rapidly, we still lack a comprehensive understanding of the impacts of the utilization of these technologies in human resource management (HRM) at an organizational (firms) and individual (employees) level. This study therefore aims to systematize the academic inputs on intelligent automation so far and to clarify what are its main contributions to and challenges for HRM. In a systematic search of 13,136 potentially relevant studies published in the top HRM, international business (IB), general management (GM) and information management (IM) journals, we found 45 articles studying artificial intelligence, robotics and other advanced technologies within HRM settings. Results show that intelligent automation technologies constitute a new approach to managing employees and enhancing firm performance, thus offering several opportunities for HRM but also considerable challenges at a technological and ethical level. The impact of these technologies has been identified to concentrate on HRM strategies, namely, job replacement, human-robot/AI collaboration, decision-making and learning opportunities, and HRM activities, namely, recruiting, training and job performance. This study discusses these shifts in detail, along with the main contributions to theory and practice and directions for future research.
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“When AI is used correctly, organizations can build their cultures and that strong cultures can help firms use AI more effectively (Vrontis et al., 2022).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Vrontis et al., 2022
In the citing paper
“However, AI’s cognitive capabilities differ significantly from those of traditional e-HRM tools.”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Vrontis et al., 2022
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Talwar, S., Dhir, A., Islam, N., Kaur, P., & Almusharraf, A. I. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.114135 · Cited by 100
“First, although we followed recent studies (e.g., Christofi, Pereira, et al., 2021; Vrontis et al., 2022) to execute a robust and systematic search and review of congruent studies, there might be certain keywords or studies that we have missed due to our inclusion and exclusion criteria.”
ResultChatGPT: The brightest student in the class
Cano, E. V., Ramírez‐Hurtado, J. M., López, J. M. S., & Menéses, E. L. (2023) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2023.101380 · Cited by 105
Whittaker, L., Mulcahy, R. F., Letheren, K., Kietzmann, J., & Russell‐Bennett, R. (2023) · Technovation · doi:10.1016/j.technovation.2023.102784 · Cited by 91
Zahoor, N., Donbesuur, F., Christofi, M., & Miri, D. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121610 · Cited by 98
Self-citationLin, H., Tian, J., & Cheng, B. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.108092 · Cited by 90
Dekel‐Dachs, O., Najda-Janoszka, M., Stokes, P. J., Simba, A., & Tarba, S. Y. (2021) · International Marketing Review · doi:10.1108/imr-12-2020-0303 · Cited by 81
Self-citationMadanchian, M., & Taherdoost, H. (2025) · Information · doi:10.3390/info16010051 · Cited by 120
“According to Vrontis et al. [9], AI integration into HRM processes requires cutting-edge tech like cloud computing and big data analytics.”
Mer, A., & Virdi, A. S. (2023) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80382-027-920231007 · Cited by 80
Park, H., Ahn, D., Hosanagar, K., & Lee, J. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517672 · Cited by 92
“Because AI is being used outside of its original purposes to solve existing problems (human-bound unfairness or bias), AI’s seamless application to HRM is still far away [67, 69, 83, 87].”
BackgroundInfluence of artificial intelligence (AI) perception on career resilience and informal learning
Kong, H., Jiang, X., Zhou, X., Baum, T. G., Li, J., & Yu, J. (2023) · Tourism Review · doi:10.1108/tr-10-2022-0521 · Cited by 81
Development and challenges of object detection: A survey
Li, Z., Dong, Y., Shen, L., Liu, Y., Pei, Y., Yang, H., Zheng, L., & Ma, J. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128102 · Cited by 79
How does artificial intelligence impact employees’ engagement in lean organisations?
Tortorella, G. L., Powell, D. J., Hines, P., Vergara, A. M. C., Tlapa, D., & Vassolo, R. S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2368698 · Cited by 71
Can Artificial Intelligence (AI) Manage Behavioural Biases Among Financial Planners?
Hasan, Z., Vaz, D., Athota, V. S., Désiré, S. S. M., & Pereira, V. E. (2023) · Journal of Global Information Management · doi:10.4018/jgim.321728 · Cited by 87
“AI attempts to extend human capabilities and accomplish tasks that neither humans nor machines could on their own (Jarrahi, 2018; Vrontis et al., 2022).”
BackgroundSelf-citationExploring the impact of language models, such as ChatGPT , on student learning and assessment
Zirar, A. (2023) · Review of Education · doi:10.1002/rev3.3433 · Cited by 99
Chen, R., & Zhang, T. (2024) · Chinese Management Studies · doi:10.1108/cms-11-2023-0653 · Cited by 83
Optimizing Project Management using Artificial Intelligence
Prifti, V. (2022) · European Journal of Formal Sciences and Engineering · doi:10.26417/667hri67 · Cited by 68
Christofi, M., Iaia, L., Marchesani, F., & Masciarelli, F. (2021) · International Marketing Review · doi:10.1108/imr-01-2021-0027 · Cited by 67
Self-citationServitization innovation: A systematic review, integrative framework, and future research directions
Xing, Y., Liu, Y., & Davies, P. (2022) · Technovation · doi:10.1016/j.technovation.2022.102641 · Cited by 66
Metadata
- Authors
- Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E.
- Affiliations
- University of Nicosia (CY)
- NEOMA Business School (FR)
- University of Birmingham (GB)
- Corresponding author
- Christofi, Michael
- Venue
- The International Journal of Human Resource Management
- Publisher
- Informa UK Limited
- Published
- 2021-02-12
- Volume
- 33
- Issue
- 6
- Pages
- 1237-1266
- ISSN
- 0958-5192 (ISSN-L)
- 1466-4399
- OpenAlex
- W3130894836
- Cited by
- 1,134
- References
- 94
- Citations by year
- 2026: 233 · 2025: 245 · 2024: 301 · 2023: 229 · 2022: 97 · 2021: 29
- FWCI
- 27.96
- Type
- journal article
- Language
- en
- Open access
- green
- api.elsevier.com
- Licence
- cc-by-nc-nd
- Locations
- The International Journal of Human Resource Management (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (publishedVersion)
- Ktisis at Cyprus University of Technology (Cyprus University of Technology) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Keywords
- artificial intelligence, robotics, intelligent automation, human resource management, human-robot collaboration, job replacement, recruitment, employee training, employee performance, decision-making, ethical considerations, firm performance, high technology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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