The Practice and Challenges of Tax Technology Optimization in the Government Tax System

Abstract

With the continuous advancement of information technology, modern tax administration is undergoing profound transformation while also facing increasingly complex challenges. Traditional tax management models struggle to cope with the growing volume of economic activities, diversified taxpayer behaviors, and higher demands for transparency and service quality. In this context, the integration of emerging digital technologies-such as big data analytics, artificial intelligence-driven decision support systems, blockchain-based data security frameworks, and scalable cloud computing architectures-has become essential for enhancing the efficiency, openness, accuracy, and intelligence of tax governance. This paper systematically analyzes key technological pathways for optimizing tax technology, focusing on how data integration, intelligent risk identification, process automation, and secure information sharing can be achieved through these tools. By comparing representative domestic and international practical cases, the study summarizes effective technological strategies and explores their applicability in different tax environments. Furthermore, it proposes a set of feasible solutions aimed at improving compliance monitoring, strengthening taxpayer services, reducing administrative costs, and building resilient digital infrastructures. The findings provide valuable theoretical and practical references for future tax information management and the construction of smart tax systems.