APPLICATION OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNINGIN MODELING ECONOMIC PROCESSES: PROSPECTS AND CHALLENGES

Abstract

In the modern economy, innovative technologies, including artificial intelligence and machine learning, are increasingly used to analyse large volumes of data and forecast economic processes more effectively. These technologies open new horizons in economic management, allowing for more accurate and faster predictions, as well as optimizing business processes at all levels. Undoubtedly, economic processes are becoming increasingly complex due to globalization and digitalization, which introduce their own features into market and financial system structures. Adequate modeling of these complex processes requires new approaches that provide not only flexibility and accuracy in forecasting but also the ability to adapt to a rapidly changing environment. Modern machine learning algorithms can detect trends and patterns in data that might be invisible to the human eye, significantly enhancing the effectiveness of analysis. However, with the introduction of new technologies, questions arise about their impact on the labor market, as automation may lead to a reduction in the number of jobs in certain sectors. This presents challenges for policymakers, who must find ways to balance technological advancements with maintaining employment rates and supporting social welfare. On one hand, new technologies offer numerous opportunities for modeling, including the ability to analyse big data in real-time, which allows for more informed decision-making. On the other hand, this raises concerns about the accuracy, ethics, and security of using artificial intelligence in these processes. It is important to ensure that the use of such technologies adheres to ethical standards and does not lead to discrimination or other social issues. Additionally, transparency in how these systems operate is critical to maintaining public trust. Thus, integrating innovative technologies into economic practice requires a careful approach and ongoing monitoring of their impact on society and the economy as a whole, to ensure they benefit all and contribute to sustainable development.