Antecedents of university students’ behavioral intention to use artificial intelligence-based investment tools

Yoong, Shi Qi (2025) Antecedents of university students’ behavioral intention to use artificial intelligence-based investment tools. Final Year Project, UTAR.

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Abstract

The financial industry is experiencing a surge in AI technology usage. This technology is impacting how many individuals make decisions regarding their investments and how they invest through automation, using what are referred to as "Robo-Advisors" and Automated Trading Platforms. The question is whether younger people (university attendees) will adopt these methods of investing. Thus, the purpose of this study is to understand what influences university students' intentions toward utilizing AI investment methods by integrating the Technology Acceptance Model (TAM) and the Theory of Reasoned Action (TRA) within an empirical research framework. Specifically, this research project will be examining the influence that various variables have on students' attitudes towards investing using AI: (1) Perceived Usefulness; (2) Perceived Ease of Use; (3) Trust; (4) Perceived Risk; (5) Social Influence; (6) Awareness of the Service; (7) Confidence; (8) Smartphone Self-Efficacy; and (9) Internet Connection Quality. Using a Convenience Sampling Method, the researchers gathered Survey Data from a sample of UTAR students and conducted the data analysis using Quantitative Technique(s). This study provides an insight into the technological, psychological, and social aspects of students' Acceptability/Acceptance of using AI investment tools and contributes to the growing body of Literature around Technology Adoption, along with providing some practical applications for the Financial Technology Sector to use in their Marketing strategies when promoting AI Investment Services to young investors.

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