Impact of AI-Based Financial Advice on Investment Preferences and Risk Perception among Salaried Investors

Abstract

Artificial Intelligence (AI) is increasingly used to deliver financial information, investment recommendations and portfolio decision support. This study examines the proposed impact of AI-based financial advice on investment preferences and risk perception among salaried investors. The framework treats perceived usefulness, perceived accuracy, trust, personalisation and transparency as dimensions of AI-based financial advice and tests their proposed relationships with investment preference and risk perception. A quantitative cross-sectional design using a structured five-point Likert questionnaire is proposed. For demonstration of the intended empirical reporting format, a synthetic dataset of 450 hypothetical salaried investors was generated and analysed using internal-consistency assessment and regression-style structural estimates. The simulated results indicate positive associations between the five AI-advice attributes and investment preference and negative associations with risk perception. These numerical findings are illustrative only and must not be represented as observations from real respondents. The study contributes a focused framework for future primary research on AI-assisted investment decision-making among salaried investors.