ECONOMIC ANALYSIS OF THE FUTURE: HOW ARTIFICIAL INTELLIGENCE IS CHANGING THE WAY ORGANIZATIONS ASSESS AND FORECAST ECONOMIC PROCESSES

Modern organizations face the need to quickly analyze large amounts of data in order to make management decisions. Traditional methods of economic analysis based on statistics and econometrics often struggle to cope with nonlinear relationships and rapidly changing market conditions. Artificial intelligence (AI), including machine learning (ML) and deep neural networks (DL), can significantly improve the accuracy of economic process estimation and forecasting. This article explores the potential of using AI methods to assess the economic performance of organizations in various industries. The article discusses key machine learning algorithms (linear regression, random forest, gradient boosting) and neural network models (LSTM, transformers, GNN), as well as their practical application in predicting bankruptcies, credit risks, demand, and fraud. The article provides real-life examples of AI implementation in Russian companies (Sberbank, XXNUMX Group, Russian Railways, Federal Tax Service) and abroad.