Artificial Intelligence and Retail Investment: A Quantitative Investigation of Adoption Drivers and Perceived Effectiveness

Abstract

This study explores how retail investors perceive and use artificial intelligence (AI) tools in their financial activities. As digital systems play a growing role in private investing, questions arise about their assessed benefits, emotional influence, and trustworthiness. While AI use in institutional finance has been well studied, much less is known about the behavior of individual investors. A structured online survey was conducted with participants across Europe, North America, and Asia. The questionnaire was designed to reflect both user and non-user perspectives, drawing on established constructs from behavioral finance and Technology Acceptance Model. Quantitative analysis included reliability checks, composite scoring, and appropriate statistical methods to test eight hypotheses.
Results show that age and cultural background strongly influence perceptions of AI usefulness and trust. Younger participants and respondents from Asian countries were more open to using AI tools. In contrast, concerns about complexity, low trust, and avoidance behavior were key barriers for non-users. Notably, frequent use of AI was linked to reduced emotional decision-making, indicating that algorithmic support can encourage a more balanced and rational investment behavior. The study demonstrates that AI adoption is shaped by more than technical access. Trust dynamics, demographic factors, and cultural framing all contribute to how AI tools are evaluated and used.
These insights carry practical implications for developers, educators, and policymakers seeking to foster wider and more inclusive adoption. A focus on user-centered design, targeted financial literacy, and emotionally accessible onboarding may be critical for success. By combining behavioral and technological perspectives, this research provides a nuanced framework for understanding retail investors’ interaction with intelligent financial technologies.

Keywords: artificial intelligence, retail investment, behavioral finance, retail investor psychology, Technology Acceptance Model, adoption intention, cultural and generational variation

6717192033 David Martin Gerhard Koeglmeier, 2568 (2025). Advisor: รศ. ดร.จอมพงศ์ มงคลวนิช – Assoc. Prof. Dr. Jomphong Mongkhonvanit, สารนิพนธ์ (Independent Study), Artificial Intelligence and Retail Investment: A Quantitative Investigation of Adoption Drivers and Perceived Effectiveness, นำเสนอในที่ประชุมวิชาการ (Conference), The 18th National and International Academic Conference 2025, ปริญญาโท (Master’s Degree), บัณฑิตวิทยาลัย (Graduate School), Master of Business Administration, Finance and Accounting, Siam University, Bangkok, Thailand – มหาวิทยาลัยสยาม กรุงเทพมหานคร ประเทศไทย