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Intelligent human resources for the adoption of artificial intelligence: a systematic literature review

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This study is dedicated to critically analysing research addressing human resource management (HRM) and the adoption of artificial intelligence (AI) with the purpose of driving development in the field of human resources (HR) at the strategic and managerial level. Design/methodology/approach – A systematic literature review (SLR) was conducted using the Scopus database, which gathered 61 articles between 2002 and 2022. The SLR process has the potential to, in addition to generating knowledge and theories, support and guide policy development and practice in many disciplines. Findings – The results of this study allowed the author to identify three main conclusions: (a) there are four thematic clusters – (i) Strategic HR and AI, (ii) Recruitment and AI, (iii) Training and AI and (iv) Future of work; (b) there is a growing academic interest in studying the implementation of AI to develop the HR sector and (c) the application of AI stands out in the strategic HR and AI cluster as a means of achieving profit maximisation and the overall development of the organisation. Originality/value – This study is the first SLR to present a strategic and managerial view on AI applications associated with specificHRMdimensions. The study is also the first SLR to identify key trends in the literature, drivers and obstacles to the development of AI in HRM and then place them within the landscape of positive and negative approaches in a framework. Also, as a contribution, the study has practical implications for HR managers and practitioners in adopting AI as a decision support in the area’s processes.

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Human resources Artificial intelligence Disruptive technologies Future of work Systematic literature review

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Citação

Jatobá, Mariana Namen; Ferreira, João J.; Fernandes, Paula O.; Teixeira, João Paulo (2023). Intelligent human resources for the adoption of artificial intelligence: a systematic literature review. Journal of Organizational Change Management.

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