USING ARTIFICIAL INTELLIGENCE FOR BIG DATA ANALYSIS IN ECONOMIC RESEARCH: DEVELOPING MODELS FOR FORECASTING ECONOMIC TRENDS, ANALYZING FINANCIAL MARKETS, AND ASSESSING THE EFFECTIVENESS OF PUBLIC POLICY

Modern economics faces a growing volume of data that requires processing and analysis to derive meaningful insights. The use of artificial intelligence (AI) technologies for big data analysis significantly enhances the accuracy of economic trend forecasting, financial market analysis, and government policy effectiveness evaluation. The relevance of this study is determined by the need to develop and implement new methods and models capable of efficiently processing large volumes of data and identifying patterns that traditional analysis methods fail to uncover. The purpose of this article is to analyze the use of AI for big data processing in economics, develop models for predicting economic processes, analyzing financial markets, and assessing government policy effectiveness. The study employs machine learning, neural networks, and time series analysis methods to construct predictive models and evaluate their effectiveness. The results of the study show that the use of AI for big data analysis opens up new opportunities for more accurate economic forecasting, improved financial analysis, and better government decision-making.