Critical exploration of AI-driven HRM to build up organizational capabilities

Abstract

Purpose Human resource management (HRM) processes are increasingly artificial intelligence (AI)-driven, and HRM supports the general digital transformation of companies' viable competitiveness. This paper points out possible positive and negative effects on HRM, workplaces and workers’ organizations along the HR processes and its potential for competitive advantage in regard to managerial decisions on AI implementation regarding augmentation and automation of work. Design/methodology/approach A systematic literature review that includes 62 international journals across different disciplines and contains top-tier academic and German practitioner journals was conducted. The literature analysis applies the resource-based view (RBV) as a lens through which to explore AI-driven HRM as a potential source of organizational capabilities. Findings The analysis shows four ambiguities for AI-driven HRM that might support sustainable company development or might prevent AI application: job design, transparency, performance and data ambiguity. A limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused on HRM in general, recruiting and HR analytics in particular. Research limitations/implications The four ambiguities' context-specific potential for capability building in firms is indicated, and research avenues are developed. Originality/value This paper critically explores AI-driven HRM and structures context-specific potential for capability building along four ambiguities that must be addressed by HRM to strategically contribute to an organization's competitive advantage.

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