Yksityissijoittajien generatiivisen tekoälyn omaksuminen sijoittamiseen liittyvissä tehtävissä : eksploratiivinen kyselytutkimus

This thesis examines the retail investors’ adoption of generative artificial intelligence (GenAI) in investment-related tasks. The rapid development and availability of GenAI tools have opened new possibilities for processing financial information. Limited research has focused on how individual investors actually use them in their own investment-related tasks. This thesis aims to examine the gap in how retail investors use GenAI for these tasks. In addition, the study explores what motivates the use of GenAI, what prevents its adoption, and what alternative tools investors use instead. The thesis focuses on retail investors and approaches the topic from their point of view. The study was conducted using quantitative research methods, and the data were collected through an online survey. In total, 114 responses were received. The survey data were analysed descriptively to identify general patterns in reported behavior. The results indicate that most respondents do not use GenAI in their investment-related tasks. Among those who use it, the use is occasional rather than continuous. GenAI is mainly used to compare investment options, generate ideas, explain financial concepts, and summarise financial reports or market information. The most often mentioned reason for using GenAI was that it allows information processing to be more efficient and reduces the effort required for analysis. Among non-users, many reported that their current methods already work well for them. Concerns about the reliability and accuracy of AI-generated outputs were also raised, especially in relation to financial decision-making. Instead of GenAI, respondents most often rely on financial news websites and stock market platforms. Although some retail investors have started to experiment with GenAI, traditional information sources continue to dominate investment practices.