Embracing intelligent insights: Unveiling investor adoption of AI advice and risk appetite

Abstract

This paper aims to reveal the factors influencing investors' intention to accept AI advice in financial decision-making. By integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), it proposes a comprehensive model that elucidates the intricate relationships between social norms, attitude, perceived behavioral control, and the intention to accept AI advice, with a particular focus on examining risk tolerance as a moderating factor. A questionnaire survey was conducted with 569 Vietnamese investors to collect data in three different times. Partial least squares structural equation modeling (PLS-SEM) was utilized to analyze the measurement model and test the hypotheses. Results indicate that perceived usefulness, perceived ease of use, attitude, subjective norms, and perceived behavioral control positively influence the intention to accept AI advice. Furthermore, risk tolerance significantly moderates the link between attitude, subjective norms, perceived behavioral control, and intention to accept AI advice. This pioneering study introduces a comprehensive model unveiling the dynamics of AI advice acceptance in finance. It explores the novel concept of risk tolerance as a moderator, marking an important step in understanding human-AI interaction for financial decisions. Findings provide valuable insights into evolving AI adoption, especially in high-risk contexts.