Trust in AI-Driven Investment Tools:How Perceived Trust affects Young Investors’ Willingness to Adopt Robo-advisors for Investment Management

Sammanfattning

This qualitative study examines how perceived trust shapes young investors’ willingness to adopt Robo-advisors for investment decisions. As artificial intelligence becomes increasingly integrated into financial services, understanding the factors that influence technology acceptance is essential. Using an integrated framework based on Uncertainty Reduction Theory (URT) and the Technology Acceptance Model (TAM), the study explores how young investors manage uncertainty, perceive usefulness, and creates trust towards automated financial tools. The study is based on twelve semi-structured interviews with young investors aged 18–35. Through thematic analysis, three central themes emerged: the advisory role of AI, trust and transparency, and learning engagement.The findings show that while participants acknowledge the efficiency and convenience of Robo-advisors, concerns about transparency, data security, and loss of control interfere with adoption. Trust, shaped by clarity, brand reputation, and perceived system reliability, was identified as the key mediator between uncertainty reduction and acceptance. Overall, the results suggest that increased transparency and opportunities for user control are crucial for enhancing young investors’ trust and adoption of Robo-advisors.