Chowdhury, Soumyadeb, Dey, Prasanta, Joel-Edgar, Sian, Bhattacharya, Sudeshna, Rodríguez-Espíndola, Oscar, Abadie, Amelie and Truong, Linh (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33 (1),
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.
Publication DOI: | https://doi.org/10.1016/j.hrmr.2022.100899 |
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Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences > Aston Business School > Aston India Foundation for Applied Research College of Business and Social Sciences > Aston Business School College of Business and Social Sciences > Aston Business School > Aston India Centre for Applied Research College of Business and Social Sciences > Aston Business School > Work & Organisational Psychology Aston University (General) |
Funding Information: | The research reported in this manuscript is funded by College of Business and Social and Social Science (Aston University) Seed Grants 2020-21 for the project, ‘Developing Artificial Intelligence Capacity, Capability and Strategy’. |
Additional Information: | Copyright © 2022, Elsevier Inc. This accepted manuscript version is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/. |
Uncontrolled Keywords: | AI capability,AI-employee collaboration,Artificial intelligence,Human resource management,Organisational resources,Systematic review,Applied Psychology,Organizational Behavior and Human Resource Management |
Publication ISSN: | 1873-7889 |
Last Modified: | 13 Dec 2024 08:24 |
Date Deposited: | 04 Apr 2022 14:47 |
Full Text Link: | |
Related URLs: |
https://www.sci ... 053482222000079
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2023-03 |
Published Online Date: | 2022-03-23 |
Accepted Date: | 2022-02-25 |
Authors: |
Chowdhury, Soumyadeb
Dey, Prasanta ( 0000-0002-9984-5374) Joel-Edgar, Sian Bhattacharya, Sudeshna Rodríguez-Espíndola, Oscar ( 0000-0002-4889-1565) Abadie, Amelie Truong, Linh |
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