Analysis of the Effectiveness of AI-Based Public Service Digitalization Policies in Improving Public Satisfaction - Latifah, Almashyra Nadira (IHSA Institute, 2026)
Public service quality remains a critical issue in many countries, where traditional bureaucratic systems are often characterized by inefficiency, limited accessibility, and low levels of public satisfaction. In response, governments have increasingly adopted digitalization strategies, including the integration of Artificial Intelligence (AI), to improve service delivery. This study aims to analyze the effectiveness of AI-based public service digitalization policies in increasing public satisfaction. The research employs a quantitative approach using a survey method, with data collected through questionnaires distributed to users of digital public services. The data are analyzed using descriptive statistics and regression analysis to examine the relationship between AI-based digitalization and public satisfaction. The results indicate that AI implementation significantly improves service efficiency, accuracy, accessibility, and transparency, which in turn positively influences public satisfaction. Among these factors, service speed and ease of access are identified as the most dominant contributors. However, challenges such as digital literacy gaps and technical issues are also identified. In conclusion, AI-based public service digitalization policies are effective in enhancing public satisfaction, although their success depends on supporting factors such as infrastructure readiness, user capability, and system reliability.