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

IF 8.2 1区 管理学 Q1 MANAGEMENT
Soumyadeb Chowdhury , Prasanta Dey , Sian Joel-Edgar , Sudeshna Bhattacharya , Oscar Rodriguez-Espindola , Amelie Abadie , Linh Truong
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引用次数: 0

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.

通过人工智能能力框架释放人工智能在人力资源管理中的价值
人工智能(AI)因其为消费者、员工和组织创造价值的潜力而越来越多地被人力资源管理(HRM)所采用。然而,最近的研究发现,尽管投入了时间、精力和资源,但组织尚未体验到人工智能应用带来的预期好处。现有的人力资源管理研究考察了人工智能的应用、预期效益及其对劳动力和组织的影响。本文的目的是系统地回顾来自国际商业、信息管理、运营管理、综合管理和人力资源管理的多学科文献,以全面客观地了解在人力资源管理中发展人工智能能力所需的组织资源。我们的研究结果表明,组织需要超越技术资源,重点发展非技术资源,如人类技能和能力、领导力、团队协调、组织文化和创新思维、治理战略和人工智能员工整合战略,以从人工智能的采用中受益。基于这些发现,我们提出了五个研究命题,以推进人力资源管理中的人工智能学术。从理论上讲,我们通过提出人工智能能力框架,整合基于资源的观点和基于知识的观点理论,确定实现商业利益所需的组织资源。从从业者的角度来看,我们的框架为管理者提供了一种系统的方式,让他们客观地自我评估组织准备情况,并制定策略,在人力资源管理中采用和实施人工智能实践和流程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
20.20
自引率
7.00%
发文量
0
审稿时长
48 days
期刊介绍: The Human Resource Management Review (HRMR) is a quarterly academic journal dedicated to publishing scholarly conceptual and theoretical articles in the field of human resource management and related disciplines such as industrial/organizational psychology, human capital, labor relations, and organizational behavior. HRMR encourages manuscripts that address micro-, macro-, or multi-level phenomena concerning the function and processes of human resource management. The journal publishes articles that offer fresh insights to inspire future theory development and empirical research. Critical evaluations of existing concepts, theories, models, and frameworks are also encouraged, as well as quantitative meta-analytical reviews that contribute to conceptual and theoretical understanding. Subject areas appropriate for HRMR include (but are not limited to) Strategic Human Resource Management, International Human Resource Management, the nature and role of the human resource function in organizations, any specific Human Resource function or activity (e.g., Job Analysis, Job Design, Workforce Planning, Recruitment, Selection and Placement, Performance and Talent Management, Reward Systems, Training, Development, Careers, Safety and Health, Diversity, Fairness, Discrimination, Employment Law, Employee Relations, Labor Relations, Workforce Metrics, HR Analytics, HRM and Technology, Social issues and HRM, Separation and Retention), topics that influence or are influenced by human resource management activities (e.g., Climate, Culture, Change, Leadership and Power, Groups and Teams, Employee Attitudes and Behavior, Individual, team, and/or Organizational Performance), and HRM Research Methods.
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