Generative Artificial Intelligence in Business: Towards a Strategic Human Resource Management Framework

IF 4.5 2区 管理学 Q1 BUSINESS British Journal of Management Pub Date : 2024-04-11 DOI:10.1111/1467-8551.12824
Soumyadeb Chowdhury, Pawan Budhwar, Geoffrey Wood
{"title":"Generative Artificial Intelligence in Business: Towards a Strategic Human Resource Management Framework","authors":"Soumyadeb Chowdhury,&nbsp;Pawan Budhwar,&nbsp;Geoffrey Wood","doi":"10.1111/1467-8551.12824","DOIUrl":null,"url":null,"abstract":"<p>As businesses and society navigate the potentials of generative artificial intelligence (GAI), the integration of these technologies introduces unique challenges and opportunities for human resources, requiring a re-evaluation of human resource management (HRM) frameworks. The existing frameworks may often fall short of capturing the novel attributes, complexities and impacts of GAI on workforce dynamics and organizational operations. This paper proposes a strategic HRM framework, underpinned by the theory of institutional entrepreneurship for sustainable organizations, for integrating GAI within HRM practices to boost operational efficiency, foster innovation and secure a competitive advantage through responsible practices and workforce development. Central to this framework is the alignment with existing business objectives, seizing opportunities, strategic resource assessment and orchestration, re-institutionalization, realignment and embracing a culture of continuous learning and adaptation. This approach provides a detailed roadmap for organizations to navigate successfully the complexities of a GAI-enhanced business environment. Additionally, this paper significantly contributes to the theoretical discourse by bridging the gap between HRM and GAI adoption, the proposed framework accounting for GAI–human capital symbiosis, setting the stage for future research to empirically test its applicability, explore its implications on HRM practices and understand its broader economic and societal consequences through diverse multi-disciplinary and multi-level research methodologies.</p>","PeriodicalId":48342,"journal":{"name":"British Journal of Management","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1467-8551.12824","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Management","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1467-8551.12824","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0

Abstract

As businesses and society navigate the potentials of generative artificial intelligence (GAI), the integration of these technologies introduces unique challenges and opportunities for human resources, requiring a re-evaluation of human resource management (HRM) frameworks. The existing frameworks may often fall short of capturing the novel attributes, complexities and impacts of GAI on workforce dynamics and organizational operations. This paper proposes a strategic HRM framework, underpinned by the theory of institutional entrepreneurship for sustainable organizations, for integrating GAI within HRM practices to boost operational efficiency, foster innovation and secure a competitive advantage through responsible practices and workforce development. Central to this framework is the alignment with existing business objectives, seizing opportunities, strategic resource assessment and orchestration, re-institutionalization, realignment and embracing a culture of continuous learning and adaptation. This approach provides a detailed roadmap for organizations to navigate successfully the complexities of a GAI-enhanced business environment. Additionally, this paper significantly contributes to the theoretical discourse by bridging the gap between HRM and GAI adoption, the proposed framework accounting for GAI–human capital symbiosis, setting the stage for future research to empirically test its applicability, explore its implications on HRM practices and understand its broader economic and societal consequences through diverse multi-disciplinary and multi-level research methodologies.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
商业中的生成人工智能:建立战略性人力资源管理框架
随着企业和社会探索生成式人工智能(GAI)的潜力,这些技术的整合为人力资源带来了独特的挑战和机遇,需要重新评估人力资源管理(HRM)框架。现有的框架往往无法捕捉 GAI 的新特性、复杂性及其对劳动力动态和组织运营的影响。本文提出了一个战略性人力资源管理框架,以可持续组织的机构创业理论为基础,将 GAI 纳入人力资源管理实践,通过负责任的实践和劳动力发展提高运营效率、促进创新并确保竞争优势。这一框架的核心是与现有的业务目标保持一致、抓住机遇、战略资源评估和协调、重新制度化、重新调整以及接受持续学习和适应的文化。这种方法为组织成功驾驭 GAI 增强型业务环境的复杂性提供了详细的路线图。此外,本文还弥合了人力资源管理与采用 GAI 之间的差距,提出了 GAI 与人力资本共生的框架,为今后的研究奠定了基础,以便通过多样化、多学科和多层次的研究方法,对其适用性进行实证测试,探索其对人力资源管理实践的影响,并了解其更广泛的经济和社会后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
10.00
自引率
12.50%
发文量
87
期刊介绍: The British Journal of Management provides a valuable outlet for research and scholarship on management-orientated themes and topics. It publishes articles of a multi-disciplinary and interdisciplinary nature as well as empirical research from within traditional disciplines and managerial functions. With contributions from around the globe, the journal includes articles across the full range of business and management disciplines. A subscription to British Journal of Management includes International Journal of Management Reviews, also published on behalf of the British Academy of Management.
期刊最新文献
Issue Information Discretion in the Governance Work of Internal Auditors: Interplay Between Institutional Complexity and Organizational Embeddedness Social Impact Business Angels as New Impact Investors Are Prestigious Directors Mere Attractive Ornaments on the Corporate Christmas Tree? Determinants of IPO Overpricing
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1