THE ROLE OF ARTIFICIAL INTELLIGENCE IN TRANSFORMING TAX ADMINISTRATION: INSIGHTS FROM SLOVENIA AND ESTONIA (BI-EST/25-27-001)
Head of the research group: izr. prof. Lan Umek
The emergence of artificial intelligence within tax administrations is anticipated to be a catalyst for significant improvements in operational efficiency and service quality. Specifically, tax authorities can leverage artificial intelligence to detect anomalies, combat tax evasion, and efficiently process vast amounts of data, resulting in fairer and more accurate taxation. Additionally, citizens and businesses can benefit from artificial intelligence-driven tools that simplify tax planning, reduce errors, and automate reporting, ultimately saving time and resources. However, the lack of research on the transformative potential of artificial intelligence in tax administrations necessitates a comprehensive examination across various tax systems, including those of Slovenia and Estonia. Consequently, this research will contribute to understanding the successes and challenges faced by early adopters and underscore the critical role of artificial intelligence in advancing tax administrations.
The primary aim of the research is to examine the transformative potential of artificial intelligence in tax administration by considering a comparative perspective between Slovenia and Estonia. The research will primarily focus on the main use cases of artificial intelligence in tax administration and their implications for improving tax collection processes and reducing the shadow economy. The data for the research will be obtained from several sources, such as the Tax Administration Series Database from the OECD, World Development Indicators from the World Bank and Shadow Economy Estimates from Schneider. Focusing on Slovenia and Estonia, the results will be compared within a broader context. Accordingly, several econometric models will be estimated by regressing dependent variables measuring tax administration efficiency and quality against dummy variables representing the main use cases of artificial intelligence in tax administration, along with additional control variables.
Duration (from/to):
from 1. 1. 2025 to 31. 12. 2026
Project partner:
Tallinn University of Technology
Contracting Authority:
Slovenian Research and Innovation Agency

Memebers of the research group:
izr. prof. dr. Lan Umek (vodja)
Members of the research group in the partner country:
dr. Ringa Raudla
Kerli Onno
Nastassia Harbuzova
Objectives of bilateral cooperation activities
The bilateral cooperation activity aims to help strengthen the knowledge of policy makers in Slovenia and Estonia. In addition, the bilateral cooperation activity includes important elements of scalability, as the results will provide a framework for further empirical studies that are transferable to an international context. The added value of the cooperation between researchers from Slovenia and Estonia is the exchange of specific knowledge and experience.
The main objectives of the cooperation are:
1) to combine the theoretical and empirical perspectives of the presented research topic;
2) to establish a basis for future cooperation on research projects; and
3) to strengthen/include cooperation between young and experienced researchers.
All the researchers involved in this bilateral cooperation activity are experts in their fields. The proposed research will contribute to the general literature with new theoretical and empirical evidence in a systematic and comprehensive way. The empirical analysis will be embedded in an in-depth theoretical and methodological background. The results of the present research will contribute to academic and practical knowledge and will help researchers and practitioners in the field in their research in theory and practice. Complementarity will be exercised by combining theoretical and empirical questions. In addition, the bilateral cooperation activity is a good opportunity to involve young researchers in international cooperation, as both partners involve selected young PhD students or postdoctoral researchers in their research work. Students from both institutions will also benefit, as both leaders of the bilateral cooperation activity plan to present the main results of the research during their guest lectures at the partner institutions.Joint contributions to selected international conferences are foreseen. The outcome of the collaboration should also be visible in the form of scientific articles published in some highly indexed (ISI) journals.