THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE METHODOLOGY OF COMPARATIVE STUDIES OF THE DYNAMICS OF CONTEMPORARY POLITICAL REGIMES - Novoskoltseva, Liudmyla; Demidov, Denys (Public Management and Policy, 2026)
The article examines how the use of artificial intelligence reshapes approaches to conducting comparative studies of political regime transformations. The relevance of the topic is associated with the shift from the traditional analysis of limited samples to the processing of large-scale datasets, which makes it possible to capture dynamic changes more accurately and on a broader empirical basis. The study aims to identify and assess how algorithmic tools influence the selection of indicators, measurement methods, and interpretation of results in comparative political science. The research combines qualitative case comparison, analysis of political indicator databases, and modeling based on machine learning algorithms. Particular attention is paid to the shift in research logic from explanatory to predictive models. At the same time, the changing role of the researcher under conditions of increasing reliance on digital tools is analyzed. The findings show that the use of intelligent systems makes it possible in practice to automate data collection and processing, reduce subjectivity in regime classification, and identify hidden patterns in their transformation. It is established that algorithms are capable of accounting for a significantly larger number of variables than traditional methods, which increases the accuracy of comparison. At the same time, several limitations are identified, including issues related to data quality, potential risks of model bias, and difficulties in interpreting the obtained results without a proper theoretical framework. The article proposes an approach to integrating algorithmic analysis with classical tools of political science, which involves step-by-step validation of results and maintaining analytical control by the researcher. The conclusions substantiate that the use of AI does not replace the researcher but changes the nature of their work: the importance of formulating research questions, critically evaluating data, and validating models increases. The effectiveness of comparative studies depends on the combination of algorithmic data processing and theoretical analysis, which allows for more well-grounded conclusions regarding changes in political regimes.