Leveraging AI- Perspectives: Essential Factors In Knowledge Transfer

Abstract

The transformative influence of artificial intelligence (AI) on organizational structures necessitates a deeper understanding of effective strategies for its implementation. This study delves into the nuanced aspects of transferring knowledge pertaining to AI implementation within human resource management (HRM), drawing from the perspectives of AI consultants of Noon. Employing qualitative data analysis techniques, the study combine literature review and in-depth semi structured interviews with five AI consultants, with data analysis facilitated by ATLAS.ti software of Noon in the United Arab Emirates. The findings unveil critical insights into AI implementation. Challenges include paucity of employee data, absence of a coherent vision, limited comprehension of AI decision frameworks, and managerial inclination to circumvent AI-generated decisions. Addressing these challenges, a two-pronged approach emerges: an immersive training regimen complemented by dedicated AI specialists, fostering effective knowledge transfer to HR managers. Integral to this process is the creation of robust communication channels, augmenting employees’ awareness of AI solutions' positive impact on collaborative engagement with AI-embedded counterparts. Remarkably, the study underscores that expediting AI integration amid the COVID-19 era yields favorable outcomes, with no discernible negative repercussions. However, the potential specter of AI bias looms as a plausible threat to successful implementation. This research offers a pragmatic comprehension of facilitative elements for AI integration in HRM. It yields invaluable insights empowering HR managers and AI developers to align their endeavors with best practices during the design and adoption of AI solutions. Furthermore, it enriches the academic discourse by addressing the nuanced query of optimal AI implementation delivery to HR managers and employees.