Soumyadeb Chowdhury
Unlocking the value of artificial intelligence in human resource management through AI capability framework
Chowdhury, Soumyadeb; Dey, Prasanta; Joel-Edgar, Sian; Bhattacharya, Sudeshna; Rodriguez-Espindola, Oscar; Abadie, Amelie; Truong, Linh
Authors
Prasanta Dey
Sian Joel-Edgar
SUDESHNA BHATTACHARYA S.Bhattacharya@nottingham.ac.uk
Assistant Professor in Organisational Behaviour and Human Resource Management
Oscar Rodriguez-Espindola
Amelie Abadie
Linh Truong
Abstract
Artificial Intelligence (AI) is increasingly adopted within Human Resource management (HRM) due to its potential to create value for consumers, employees, and organisations. However, recent studies have found that organisations are yet to experience the anticipated benefits from AI adoption, despite investing time, effort, and resources. The existing studies in HRM have examined the applications of AI, anticipated benefits, and its impact on human workforce and organisations. The aim of this paper is to systematically review the multi-disciplinary literature stemming from International Business, Information Management, Operations Management, General Management and HRM to provide a comprehensive and objective understanding of the organisational resources required to develop AI capability in HRM. Our findings show that organisations need to look beyond technical resources, and put their emphasis on developing non-technical ones such as human skills and competencies, leadership, team co-ordination, organisational culture and innovation mindset, governance strategy, and AI-employee integration strategies, to benefit from AI adoption. Based on these findings, we contribute five research propositions to advance AI scholarship in HRM. Theoretically, we identify the organisational resources necessary to achieve business benefits by proposing the AI capability framework, integrating resource-based view and knowledge-based view theories. From a practitioner's standpoint, our framework offers a systematic way for the managers to objectively self-assess organisational readiness and develop strategies to adopt and implement AI-enabled practices and processes in HRM.
Citation
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), Article 100899. https://doi.org/10.1016/j.hrmr.2022.100899
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 25, 2022 |
Online Publication Date | Mar 23, 2022 |
Publication Date | Mar 1, 2023 |
Deposit Date | Jan 26, 2024 |
Publicly Available Date | Mar 24, 2024 |
Journal | Human Resource Management Review |
Print ISSN | 1053-4822 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 33 |
Issue | 1 |
Article Number | 100899 |
DOI | https://doi.org/10.1016/j.hrmr.2022.100899 |
Keywords | Artificial intelligence, Organisational resources, AI capability, Human resource management, Systematic review, AI-employee collaboration |
Public URL | https://nottingham-repository.worktribe.com/output/30150440 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S1053482222000079?via%3Dihub |
Files
19363
(834 Kb)
PDF
You might also like
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search