Stepping into the future: unravelling breakthrough innovations through AI ambidexterity, hybrid intelligence, and transformational leadership

Shahan Bin Tariq, Jian Zhang and Faheem Gul Gilal

International Journal of Information Systems and Change Management, 2024, vol. 14, issue 1, 3-29

Abstract: The increasing strategic use of artificial intelligence (AI) in globalisation and market dynamics has resulted in mixed outcomes. Limitations in understanding employees' psychological states towards AI in human resource management (HRM) contribute to this variability. To fill this gap, this study provides an integrated model based on social exchange theory (SET) and resource-based view (RBV) to explain how perceived AI ambidexterity (i.e., routine and innovative use) affects breakthrough innovation engagement. Moreover, it examines hybrid intelligence using mediation and transformational leadership as moderators. Data from 337 high-tech employees in Pakistan was employed for hypotheses testing using partial least square structural equation modelling (PLS-SEM). Findings revealed perceived AI routine and innovative use, and breakthrough innovation engagement's positive relationship, together with hybrid intelligence use mediation. Moreover, transformational leadership moderated perceived AI innovative use and hybrid intelligence use relationships only. By enriching perceived AI ambidexterity in HRM, this study provides significant implications and future research directions.

Keywords: AI; artificial intelligence; perceived artificial intelligence ambidexterity; HRM; human resource management; SET; social exchange theory; RBV; resource-based view; breakthrough innovation engagement; hybrid intelligence; transformational leadership; routine artificial intelligence; innovative artificial intelligence. (search for similar items in EconPapers)
Date: 2024
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