The DOI matches its Crossref record; 94 of the 94 references it cites were found in a registry or an index.
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
Citations
Cites
Tranfield, D., Denyer, D., & Smart, P. (2003) · British Journal of Management · doi:10.1111/1467-8551.00375 · Cited by 15,386 · cited 3×
“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).”
MethodThe future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727 · cited 1×
“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.”
BackgroundArtificial intelligence in service
Huang, M.-H., & Rust, R. T. (2018) · Journal of Service Research · doi:10.1177/1094670517752459 · Cited by 3,978 · cited 3×
“AI concerns, inter alia, information processing, logical reasoning and mathematical skills (Huang & Rust, 2018).”
BackgroundInfluentialA Multi‐Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature
Crossan, M. M., & Apaydın, M. (2009) · Journal of Management Studies · doi:10.1111/j.1467-6486.2009.00880.x · Cited by 3,667 · cited 3×
“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).”
MethodAlgorithms at Work: The New Contested Terrain of Control
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0174 · Cited by 2,732 · cited 1×
“Algorithmic technologies can also help employers direct, evaluate and discipline workers (Kellogg et al., 2020).”
BackgroundThe theory of decision making.
Edwards, W. (1954) · Psychological Bulletin · doi:10.1037/h0053870 · Cited by 2,710 · cited 1×
“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…”
Methodvan Doorn, J., Mende, M., Noble, S. M., Hulland, J., Ostrom, A. L., Grewal, D., & Petersen, J. A. (2017) · Journal of Service Research · doi:10.1177/1094670516679272 · Cited by 1,344 · cited 2×
“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.”
BackgroundLoebbecke, C., & Picot, A. (2015) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2015.08.002 · Cited by 1,317 · cited 2×
“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).”
BackgroundLuo, X., Tong, S., Fang, Z., & Qu, Z. (2019) · Marketing Science · doi:10.1287/mksc.2019.1192 · Cited by 1,262 · cited 1×
“…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).”
BackgroundInformation Technology and the Changing Fabric of Organization
Zammuto, R. F., Griffith, T. L., Majchrzak, A., Dougherty, D. J., & Faraj, S. A. (2007) · Organization Science · doi:10.1287/orsc.1070.0307 · Cited by 1,213 · cited 1×
“Zammuto et al. (2007) describe five affordances – visualizing entire work processes, real-time/flexible product and service innovation, virtual collaboration, mass collaboration, and simulation/synthetic reality – that can result from this interplay.”
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Vural, M. F. (2026) · Journal of Management Archive · doi:10.70877/joma.48
“HRM performs a central function in organizations in determining job descriptions, competency frameworks, performance metrics, and career paths (Vrontis et al., 2022).”
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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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