Competency and Diversity of Knowledge in Improving Service Performance with Artificial Intelligence-Based Technology as a Moderation

Dhani Wicaksono, Ibnu Khajar

Abstract


This study is an explanatory research aimed at examining the relationships among variables, namely service performance, the utilization of AI-based technology, knowledge diversity, and competence. The research object consists of 203 human resources at the Customs and Excise Office of Supervision and Service Type Madya Pabean a Semarang, with a sample of 112 respondents determined using the Slovin formula. The sampling technique applied was non-probability sampling with a convenience sampling method, chosen for reasons of efficiency in time and cost. Data were collected through questionnaires using an interval scale from 1 to 5 and analyzed with structural equation modeling using the Partial Least Square (PLS) approach. The findings reveal that knowledge diversity has a positive and significant effect on service performance, while competence also has a positive and significant effect on service performance. However, AI-based technology does not moderate the effect of knowledge diversity on service performance. On the other hand, AI-based technology significantly moderates and strengthens the effect of competence on service performance. Thus, this study emphasizes the importance of competence and knowledge diversity in improving service performance, as well as the strategic role of AI-based technology as a reinforcing factor in optimizing employee competence.


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