Transformation of Accounting Methodology Based on Artificial Intelligence and Data Science Technologies

Abstract

Abstract. Purpose. The purpose of the article is to substantiate the methodological foundations for the transformation of accounting in the context of the digital economy and Industry 4.0 through the integration of data analytics, artificial intelligence, machine learning, and blockchain technologies, as well as to develop a conceptual model of the evolution of accounting systems from retrospective recording to predictive financial information management. Methods. The study employs a systemic and institutional approach, bibliometric analysis, synthesis of scientific literature, logical modeling, and comparative analysis. Elements of empirical interpretation are applied to assess the implementation outcomes of machine learning algorithms, natural language processing tools, and stochastic modeling techniques in accounting practice. The theoretical framework is based on the concepts of Accounting Intelligence, triple-entry accounting, and digital transformation of financial systems. Results. The findings demonstrate that the integration of Data Science tools fundamentally changes the functional role of accounting systems. The application of natural language processing and machine learning significantly increases the speed of financial document processing and reduces error rates. The use of time-series analysis, recurrent neural networks, and Monte Carlo simulation improves the accuracy of cash flow forecasting and investment evaluation. The synergy between blockchain technology and algorithmic transaction analysis creates the basis for continuous auditing and real-time reporting. A three-stage evolutionary model of accounting systems is proposed, reflecting the transition from traditional recording mechanisms to hybrid analytical integration and further to fully intelligent decision-support systems. Conclusions. Digital transformation leads to the formation of a new financial information management ecosystem that combines algorithmic data verification, predictive modeling, and professional judgment. The transition to an intelligent accounting model enhances operational efficiency, transparency, and the qualitative characteristics of financial reporting.