THE INFLUENCE OF AI GENERATED INVESTMENT STRATEGY ON RETAIL INVESTORS' DECISION-MAKING

Abstract

The swift development of the artificial intelligence (AI) has promoted significant change in the financial industry, especially the capital market. Based on the new AI technologies, several types of investment development, including robo-advisory services, algorithmic trading indicators, and AI-driven analytical tools, have become more and more popular among individual investors, due to their simplicity, the speed at which they operate, and data-driven nature (Baker & Dellaert, 2018). With the spread of the use of digital investment platforms, the need to study the effects of AI generated strategies on individual investors becomes not only urgent but also insoluble. Retail investors also represent a large and growing portion of the world financial markets, a phenomenon increased by the development of online trading platforms, as well as, mobile investment application. The retail participants are less financially literate than institutional investors and therefore they tend to be more dependent on outside sources of information in their decision to invest (Barber & Odean, 2013). The perception of AI-generated investment strategy is often objective, not subject to biases, and more accurate than the human judgment, which strengthens the trust and confidence of investors (Jung et al., 2018). Nevertheless, such a view can also result in the excessive delegation of power to AI systems, the loss of critical thinking, and the loss of the financial risk. In turn, the increased significance of the need to examine the degree to which retail investors understand and respond to AI-generated investment plans. Academically, the research of conventional investment decision making and behavioural finance such as biases to overconfidence, herding and risk aversion (Kahneman, and Tversky, 1979) is well-established research. Even though recent academic works have devoted much focus to AI in finance, the existing body of literature mainly focuses on technological effectiveness, algorithm precision, or institutional acceptance (Markakis, 2017). Not many researches explore the behavioural and psychological implications of AI-generated investment strategies to retail investors. The current study aims to fill this gap by examining the impact of trust, confidence, perception of risk, and decision-making process under the influence of AI. 5 The subject matter is not merely a fitting one but also timely and the views are incorporated in finance, technology, media, and management. The practical implication of investigating how the investing population will respond to AI-generated strategies can be relevant to the fintech enterprises, brokers, and financial marketers. The findings can also help organizations to create more transparent and easy-to-use AI tools, and in parallel, improve the communication approach to AI-based recommendations (Davenport & Ronanki, 2018). The regulators and policymakers can also get a holistic view of how the artificial intelligence has influenced the behaviour of retail investors and thus feed the ethical guidelines in implementing artificial intelligence as well as in how to present consumer protection policies. The study design is valid and includes a mixed-method research design that is suitable to inquiry at MBA level. Quantitative surveys will provide the data capable of supporting the trends in the use of AI, its trust, and the subsequent behaviours, whereas qualitative interview offers more profound insights into the personal experience and attitude of investors.