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.
