Facial Recognition Systems are increasingly adopted in the field of public surveillance. However, there is a lack of research on the factors influencing individuals’ trust in these systems, especially in underexplored regions. This study addresses this gap by investigating the factors affecting Mongolians’ trust and proposing recommendations for developing AI frameworks that are aligned with human-centered values and sensitive to the local context. For that, it adopts a mixed-methods approach comprising a survey and interviews. The quantitative data reveals key demographic and social factors influencing trust levels. The findings highlight significant concerns regarding data misuse and transparency, shaping recommendations to address these issues. At the same time, key concerns are related to potential misuse of the technology and data breaches. The research proposes actionable recommendations for fostering trust in facial recognition systems that align with global ethical principles while addressing local sociocultural contexts.