Generative AI (GenAI), particularly large language models (LLMs), is increasingly embedded in decision-making processes, making it essential to understand the drivers of its actual use. Despite their accessibility, LLMs are prone to hallucinations and bias, which contribute to user skepticism. This study examines the factors shaping perceptions of LLMs in personal and professional decision-making contexts, focusing on perceived usefulness, user trust, and personal values. An anonymous survey of 215 professionals was analysed using descriptive statistics, hierarchical cluster analysis, and regression analysis. Findings reveal that, contrary to expectations, trust and perceived usefulness alone do not sufficiently explain LLM adoption. Instead, personal values emerge as a significant yet underexplored determinant influencing usage decisions. These results extend current GenAI adoption research by incorporating the role of individual values. The study highlights the importance of context-sensitive, stakeholder-aware strategies and underscores the need for further research on value alignment across diverse cultural and regulatory environments.
