Using a mixed-methods approach, the research combines a thorough literature review, survey data from Swiss consumers, and in-depth interviews with industry experts.

The findings indicate that technological challenges, such as the integration of high-quality data and the need for algorithmic transparency, are significant barriers to user trust and operational efficiency. Swiss cultural values, which place a strong emphasis on trust and personal relationships in financial decision-making, tend to favour human advisors over automated systems, particularly among older and less tech-savvy individuals. Ethical concerns about data privacy and the fairness of algorithms also hinder consumer acceptance. On the legal front, regulatory requirements under the Financial Services Act (FIDLEG) and the Financial Institutions Act (FINIG) create significant compliance costs and operational challenges, especially for smaller firms. Economically, high upfront costs and a lack of cost transparency limit the scalability and acceptability of robo-advisors to potential users. Considering these findings, the study recommends the adoption of hybrid advisory models, improved data integration and transparency through Explainable AI (XAI), streamlined regulatory processes and targeted educational initiatives to address knowledge gaps. By aligning technological innovation with cultural expectations, regulatory pragmatism and ethical standards, financial institutions can build trust and foster sustainable growth in the robo-advisory market. This comprehensive strategy is critical to increasing the acceptance and effectiveness of robo-advisory services within Switzerland's sophisticated and culturally rich financial ecosystem.