Unlocking the value of artificial intelligence in human resource management through AI capability framework

Soumyadeb Chowdhury*, Prasanta Dey, Sian Joel-Edgar, Sudeshna Bhattacharya, Oscar Rodríguez-Espíndola, Amelie Abadie, Linh Truong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article number100899
Number of pages21
JournalHuman Resource Management Review
Issue number1
Early online date23 Mar 2022
Publication statusPublished - Mar 2023

Bibliographical note

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/.


  • AI capability
  • AI-employee collaboration
  • Artificial intelligence
  • Human resource management
  • Organisational resources
  • Systematic review


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