Browsing by Author "Chowdhury, Soumyadeb"

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    Generative artificial intelligence in business: towards a strategic human resource management framework
    (Wiley, 2024-04-11) Chowdhury, Soumyadeb; Budhwar, Pawan; Wood, Geoffrey
    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.
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    Human resource management in the age of generative artificial intelligence: perspectives and research directions on ChatGPT
    (Wiley, 2023-07-10) Budhwar, Pawan; Chowdhury, Soumyadeb; Wood, Geoffrey; Aguinis, Herman; Bamber, Greg J.; Beltran; Boselie, Paul; Cooke, Fang Lee; Decker, Stephanie; DeNisi, Angelo; Dey, Prasanta Kumar; Guest, David; Knoblich, Andrew J.; Malik, Ashish; Paauwe, Jaap; Papagiannidis, Savvas; Patel, Charmi; Pereira, Vijay; Ren, Shuang; Rogelberg, Steven; Saunders, Mark N. K.; Tung, Rosalie L.; Varma, Arup
    ChatGPT and its variants that use generative artificial intelligence (AI) models have rapidly become a focal point in academic and media discussions about their potential benefits and drawbacks across various sectors of the economy, democracy, society, and environment. It remains unclear whether these technologies result in job displacement or creation, or if they merely shift human labour by generating new, potentially trivial or practically irrelevant, information and decisions. According to the CEO of ChatGPT, the potential impact of this new family of AI technology could be as big as “the printing press”, with significant implications for employment, stakeholder relationships, business models, and academic research, and its full consequences are largely undiscovered and uncertain. The introduction of more advanced and potent generative AI tools in the AI market, following the launch of ChatGPT, has ramped up the “AI arms race”, creating continuing uncertainty for workers, expanding their business applications, while heightening risks related to well-being, bias, misinformation, context insensitivity, privacy issues, ethical dilemmas, and security. Given these developments, this perspectives editorial offers a collection of perspectives and research pathways to extend HRM scholarship in the realm of generative AI. In doing so, the discussion synthesizes the literature on AI and generative AI, connecting it to various aspects of HRM processes, practices, relationships, and outcomes, thereby contributing to shaping the future of HRM research.