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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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“Notably, despite the expectations that these advancements will have a dramatic impact on employment (Frey & Osborne, 2017), our findings suggest that we are still years away from wide-ranging consequences on HRM and levels of employment.”
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“To delineate research patterns and discern avenues for future studies related to intelligent automation in HRM, we conducted a systematic literature review following the suggestions made by Tranfield et al. (2003) as well as Crossan and Apaydin (2010).”
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“First, building on the theory of decision-making (Edwards, 1954) as well as on recent research that has analyzed how data allow HR managers to better informed about employees (Garcia-Arroyo & Osca, 2019), we found that AI algorithms and expert systems facilitate HR processes and allow better…”
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“Van Doorn et al. (2017) argue that situations defined by strong needs for empathy, in which developing original and creative solutions is required or that necessitate high levels of social intelligence are not at high risk for automation and replacement.”
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“In fact, our study responds to several calls to synthesise the current state of knowledge beyond the boundaries of individual academic disciplines in reference to intelligent automation (e.g. AI, machine learning, digitization) and work (Loebbecke & Picot, 2015; Markus, 2015).”
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“…developments, however, are increasingly providing alternatives to human resources in functions traditionally requiring human interaction and communication (Malik et al., 2019; Luo et al., 2019), thereby changing both the organizational structures and the nature of work (Colbert et al., 2016).”
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Extending application of explainable artificial intelligence for managers in financial organizations
Sabharwal, R., Miah, S. J., Wamba, S. F., & Cook, P. G. (2024) · Annals of Operations Research · doi:10.1007/s10479-024-05825-9 · Cited by 41
Artificial intelligence in talent acquisition: a multiple case study on multi-national corporations
Roppelt, J. S., Greimel, N. S., Kanbach, D. K., Stubner, S., & Maran, T. K. (2024) · Management Decision · doi:10.1108/md-07-2023-1194 · Cited by 35
Effects of algorithmic control on power asymmetry and inequality within organizations
Barati, M., & Ansari, B. (2022) · Journal of Management Control · doi:10.1007/s00187-022-00347-6 · Cited by 46
“In their review, Vrontis et al. (2022) posit that some forms of electronic performance monitoring technologies are already widely used by companies to monitor and analyze worker behavior by recording call and internet usage, medication administration records, and the like.”
BackgroundGoswami, M., Jain, S., Alam, T., Deifalla, A. F., Ragab, A. E., & Khargotra, R. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1215706 · Cited by 33
Using artificial intelligence for hiring talents in a moderated mechanism
Islam, M., Rahman, M. M., Taher, M. A., Quaosar, G. M. A. A., & Uddin, M. A. (2024) · Future Business Journal · doi:10.1186/s43093-024-00303-x · Cited by 49
“Notably, within the realm of human resource management (HRM) activities, AI’s most conspicuous application emerges in the employee recruitment process [18, 19], an area of research that exhibits a dearth of diversity and primarily centers its attention on developed countries [20, 21].”
Cognitive engagement with AI ‐enabled technologies and value creation in healthcare
Kumar, P. S., Vrontis, D., & Pallonetto, F. (2023) · Journal of Consumer Behaviour · doi:10.1002/cb.2196 · Cited by 33
Self-citationLi, H., & Tian, F. (2026) · Group Decision and Negotiation · doi:10.1007/s10726-026-09980-1 · Cited by 78
Zahoor, N., Khan, Z., Wu, J., Tarba, S. Y., Donbesuur, F., & Khan, H. (2022) · Technovation · doi:10.1016/j.technovation.2022.102588 · Cited by 32
“The success of a SLR depends on the initial formulation of a clear review question (Rojon et al., 2021; Vrontis et al., 2022).”
Self-citationDesign and Implementation of an Ultrasonic Sensor-Based Obstacle Avoidance System for Arduino Robots
Mahmud, T., Ara, I., Chakma, R., Barua, K., Islam, D., Hossain, M. S., Barua, A., & Andersson, K. (2023) · International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD) · doi:10.1109/icict4sd59951.2023.10303550 · Cited by 32
“Artificial intelligence (AI) is one of the most sought-after and actively explored disciplines as technology develops and intelligent devices become more prevalent [1].”
BackgroundFuture of work from everywhere: a systematic review
Jagadeeswari, I. U., & Warrier, U. (2023) · International Journal of Manpower · doi:10.1108/ijm-06-2022-0288 · Cited by 32
Algorithmic human resource management: toward a functional affordance perspective
Gong, Q., Fan, D., & Bartram, T. (2024) · Personnel Review · doi:10.1108/pr-01-2024-0099 · Cited by 36
Digital Transformation for Era Society 5.0 and Resilience: Urgent Issues from Indonesia
Rohayati, Y., & Abdillah, A. (2024) · Societies · doi:10.3390/soc14120266 · Cited by 97
Li, J., Wu, H.-Y., Zhang, R.-X., & Wu, T. (2025) · The International Journal of Human Resource Management · doi:10.1080/09585192.2025.2512555 · Cited by 32
“Consequently, employee-GenAI collaboration gradually gained popularity in organizations (Vrontis et al., 2022; Wu et al., 2022).”
Moore, N., Rowe, L., Stokes, P. J., Lichy, J., Rodgers, P., & Smith, S. (2022) · Production Planning & Control · doi:10.1080/09537287.2022.2083523 · Cited by 41
Ahmad, S. F., Alam, M. M., Rahmat, M. K., Shahid, M. K., Aslam, M., Salim, N. A., & Al‐Abyadh, M. H. A. (2023) · Sustainability · doi:10.3390/su15086540 · Cited by 49
Unrealistic Optimism Regarding Artificial Intelligence Opportunities in Human Resource Management
Weber, P. (2023) · International Journal of Knowledge Management · doi:10.4018/ijkm.317217 · Cited by 31
“Like Dahm & Dregger (2019), one may focus on the applicants’ perspective when surveying (Vrontis et al., 2022).”
BackgroundResultInfluentialAlenezi, A., Alshammari, M. H., & Ibrahim, I. A. (2024) · Journal of Nursing Management · doi:10.1155/2024/8371068 · Cited by 46
Ibrahim Almatrodi, N. A., Li, F., & Alojail, M. (2023) · Systems · doi:10.3390/systems11040191 · Cited by 42
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
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