A Study on the Impact of AI-Powered Investment Apps on Investment Decisions among Young Investors in Chennai City

Author

Mithra Shree S, Dr. G.H. Kerinab Beenu, Dr. John Walsh


Abstract

 This study examines how features of AI-powered investment apps (usability, alerts, relevance, trust and personalization) influence the investment decisions of young investors in Chennai City, how these features relate to perceived financial literacy, and whether demographic factors are associated with usage frequency. A descriptive research design was adopted and primary data were collected through a structured questionnaire administered via Google Forms. Using convenience sampling, 65 valid responses were obtained from young investors who use AI-powered investment apps, and opinion statements were measured on a five-point Likert scale. Percentage analysis, descriptive statistics, multiple regression, Pearson correlation and chi-square tests were applied. The regression model (R² = 0.83, F(5, 59) = 57.38, p < 0.001) showed that usability (β = 0.20, p = 0.014), alerts (β = 0.22, p = 0.020) and trust (β = 0.31, p = 0.004) were significant predictors of investment decisions, with trust the strongest; relevance and personalization were not significant at the 5% level. All five features were positively and significantly correlated with perceived financial literacy, personalization being the strongest (r = 0.781, p < 0.001). Age, gender, occupation, monthly income and marital status showed no significant association with usage frequency (all p > 0.05). The study recommends transparent explanation of AI recommendations, simple interfaces, customisable alerts, clear risk disclosure and in-app investor education.



Keywords

AI-powered investment apps, investment decisions, young investors, trust, personalization, financial literacy, Chennai



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