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Communication Dans Un Congrès Année : 2024

Career sustainability at the time of working with artificial intelligence: A resource-based framework focused on sustainable career resources

Résumé

The existing literature has provided distinctive reflection on sustainable development (Gladwin et al., 1995), digital sustainability (George et al., 2021), sustainable careers (de Vos et al., 2020; Len & Brown, 2020) and sustainable human capital (Campbell et al., 2012; Aust et al., 2020). In parallel, scholars have equally highlighted that artificial intelligence (AI) demonstrates increasing potential capacities to perform a number of vocational activities (Bailey et al. 2012), and AI-provided resources—the algorithmic processes that achieve activities for or beside human professionals—are regularly evoked as the potential substitutes of a series of vocational activities (Fleming, 2019; Tschang & Almirall, 2021). In this context, it appears judicious to question how and why working with AI could reframe career sustainability, which consists of an inquiry that could potentially contribute to enhancing knowledge on career sustainability and inspiring career decision-making (Len & Brown, 2020) for individuals and organizations. For this purpose, the research presented in this conceptual paper advances a framework by focusing on the notion of sustainable career resources—notion advanced by adopting the resource-based view (Barney, 1986, 1991; Barney et al., 2011), initially elaborated in the context of firm strategy—to understand if AI-provided resources could reframe potential career resources, and, consequently, reframe career sustainability. The research findings contribute to the knowledge on how to preserve and renew sustainable career resources at the time of working with AI. Beyond their conceptual interest, these findings could inspire possible empirical undertaking from which individuals and organizations could attempt to preserve the career resources that favor career sustainability at the time of AI implementations.
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Dates et versions

hal-04503629 , version 1 (13-03-2024)

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  • HAL Id : hal-04503629 , version 1

Citer

Hongxia Peng. Career sustainability at the time of working with artificial intelligence: A resource-based framework focused on sustainable career resources. Common-Good HRM Spring Workshop 2024, Vienna University of Economics and Business (WU), Université Catholique de Louvain (UCLouvain), The Open University (UK), Mar 2024, Online, Austria. ⟨hal-04503629⟩
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