Affiliation:
1. Information, Operations and Management Sciences Department TBS Business School 1 Place Alphonse Jourdain Toulouse 31068 France
2. Aston Business School Aston University Aston Triangle Birmingham B4 7DA UK
3. DAN Department of Management & Organizational Studies Western University 1151 Richmond Street London Ont. N6G 2V4 Canada
4. Cranfield University College Road Cranfield MK43 0AL UK
5. University of Bath Claverton Down Bath BA2 7AX UK
Abstract
AbstractAs 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.
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