Iqtisodiy prognozlashda sun'iy intellektning roli
Аннотация
This thesis examines the role of artificial intelligence in economic forecasting, focusing on its impact on improving the accuracy, efficiency, and adaptability of predictive models. The study analyzes traditional forecasting methods, including econometric models and expert-based approaches, and identifies their limitations in handling complex and large-scale economic data. Furthermore, the paper explores modern AI technologies, such as machine learning and deep learning, and their integration with big data in forecasting processes. Particular attention is given to the practical applications of AI in predicting macroeconomic indicators, financial market trends, and business demand. The research also highlights the key advantages of AI, including enhanced predictive accuracy, rapid data processing, and the reduction of human error. At the same time, it addresses existing challenges, such as data quality issues, lack of model transparency, and ethical concerns. The findings suggest that artificial intelligence significantly enhances economic forecasting and serves as a valuable tool for supporting decision-making in complex and dynamic economic environments.