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Radonjić, A., Duarte, H. & Pereira, N.  (N/A). Artificial intelligence and HRM: HR managers’ perspective on decisiveness and challenges. European Management Journal. N/A

A. Radonjić et al.,  "Artificial intelligence and HRM: HR managers’ perspective on decisiveness and challenges", in European Management Journal, vol. N/A, N/A

@article{radonjićN/A_1715513573276,
	author = "Radonjić, A. and Duarte, H. and Pereira, N. ",
	title = "Artificial intelligence and HRM: HR managers’ perspective on decisiveness and challenges",
	journal = "European Management Journal",
	year = "N/A",
	volume = "N/A",
	number = "",
	doi = "10.1016/j.emj.2022.07.001",
	url = "https://www.sciencedirect.com/journal/european-management-journal"
}

TY  - JOUR
TI  - Artificial intelligence and HRM: HR managers’ perspective on decisiveness and challenges
T2  - European Management Journal
VL  - N/A
AU  - Radonjić, A.
AU  - Duarte, H.
AU  - Pereira, N. 
PY  - N/A
SN  - 0263-2373
DO  - 10.1016/j.emj.2022.07.001
UR  - https://www.sciencedirect.com/journal/european-management-journal
AB  - Focus
The transformative power of today's big data (BD) has allowed many companies, i.e., decision-makers, to evolve at an unprecedented pace. With regard to decision-making, artificial intelligence (AI) takes task delegation to a new level, and by employing AI-assisted tools, companies can provide their HR departments with the means to manage the existing data and HR altogether.
Objectives
To determine how HR managers assess whether BD management is facilitated by AI, and how they frame the changes necessary to meet the trends related to AI and its implementation, namely their willingness to master its implementation and to meet the possible challenges.
Methodology
Content analysis was conducted on interviews held with a sample of 16 HR practitioners from a spectrum of areas, and the findings were analysed using the big data maturity model (BDMM) framework. Domains covered by this model allow the study of decision-making trends, in terms of preparedness and willingness to tackle disruptive technology with the aim of improving and gaining the competitive edge in decision-making.
Findings
The central potential of AI lies in faster data storage and processing power, thereby leading to more insightful and effective decision-making. This article contains closer insights into the challenges underlying the implementation of AI in decision-making processes, specifically in terms of strategic alignment, governance, and implementation. The results reflect the notions regarding the nature of AI – in assisting HR – and lay out the path that precedes the extraction of BD, through the delivery of advantageous intelligence, to augment decision-making in HR.
ER  -