The use of artificial intelligence in the management of investment portfolios

The ever-increasing complexity of financial markets, characterized by high market volatility, economic uncertainty, and the massive influx of various data pose a significant challenge in investment portfolio management. Traditional methods can fall short in addressing these challenges, requiring too much from an individual managing investment portfolios. The ability of AI to process a tremendous number of large datasets and to detect patterns offers a significant advantage for a manager, providing for more informed and timely investment decisions. The purpose of this annex is to encapsulate findings of the primary paper on the use of AI in investment portfolio management, highlighting the benefits and challenges, and also identifying areas for improvement and further research. The paper explores the possibility of using AI to enhance the effectiveness of an investment portfolio manager, through the improvement of analysis’ quality, help in data collection and processing, recognition of complex patterns, and faster decision-making. This could help optimize investment strategies through risk reduction, improved forecasting, and faster adaptation to market fluctuations. In addition, the paper aims to identify potential risks associated with AI integration, for example quality of data, algorithm transparency, and cybersecurity issues. Literature analysis demonstrated that application of AI can increase the efficiency of investment portfolio management. This is possible because of AI systems' ability to conduct advanced data search and analysis, providing for better decision-making. The use of AI algorithms allows investment portfolio managers to identify market trends more easily, optimize asset allocations, as well as minimize market volatility risks. А good example is BlackRock's Aladdin expert system, which provides comprehensive data insights, providing a competitive advantage. However, the paper also demonstrates, that implementation of AI systems is associated with several challenges, particularly - quality of provided data and opacity of AI algorithms, which can raise doubts regarding their effectiveness. Moreover, cybersecurity remains a significant concern. Overall, the use of AI presents opportunities for investment portfolio managers to improve results by providing competitive advantages. However, certain challenges need to be overcome. AI holds great promise for investment portfolio management, and future studies need to focus on AI integration, cybersecurity, and improvement of data quality.