Abstract
The financial sector has undergone profound changes over the past twenty years, affecting the ways in which both individuals and organizations interact. The active introduction of artificial intelligence (AI) and big data analytics has significantly changed the approaches to the activities of financial institutions and their interaction with customers and other organizations. It is expected that these changes will continue to gain momentum due to the development of technologies that allow us to focus on innovation and solving complex problems. Every day, the financial industry records billions of events in the markets, which generates significant amounts of diverse data related to the Big Data category. AI algorithms and models that work with big data to analyze patterns and generate recommendations in areas such as portfolio strategies and fraud detection are becoming increasingly important in the financial sector. However, the level of their application and development differs significantly depending on the capabilities and competencies of different organizations. These differences, as well as the impact of new technologies on the financial sector, are becoming central topics of discussion among industry professionals. This article is devoted to the study of the use of AI and big data analytics in stock trading, as well as the analysis of the consequences of their use. The research examines current trends and practices that allow us to draw conclusions about the impact of these technologies on the strategies and decision-making processes of market participants.