This research aims to explore the factors influencing the intention to use Artificial Intelligence (AI) among civil servants in Indonesia and South Korea through a cross-country comparative approach. As AI continues to transform governance and public service delivery, understanding how public sector employees perceive and adopt this technology becomes increasingly important for ensuring its effective implementation. The study focuses on identifying key determinants that shape civil servants’ behavioral intention to adopt AI, including technology readiness, perceived usefulness, perceived ease of use, and social influence.

Using a quantitative research design, data were collected through structured surveys distributed to civil servants in both Indonesia and South Korea. The analysis was conducted using Structural Equation Modelling (SEM) to examine the relationships among variables and to identify significant predictors of AI adoption intention. This approach allows for a comprehensive understanding of both individual and organizational factors influencing technology acceptance in different national contexts.

The findings reveal that civil servants in both countries generally demonstrate a positive attitude toward AI adoption. However, notable differences emerge in the relative influence of certain factors, particularly social influence and perceived usefulness, which vary between Indonesia and South Korea. Additionally, government support and levels of digital literacy are found to play a significant role in shaping the intention to use AI in both contexts, highlighting the importance of institutional readiness and capacity building.

This study contributes to the growing body of knowledge on digital governance and technology adoption in the public sector by offering empirical insights from a comparative perspective. Furthermore, it provides practical recommendations for policymakers to design more effective strategies for AI integration, emphasizing the need for tailored approaches that consider cultural, organizational, and institutional differences across countries.