This study explores the factors influencing public sector employees’ comfort with using artificial intelligence (AI) tools for financial decision-making. Leveraging an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework, the research analyzes survey data from 1,994 respondents to identify key predictors of AI comfort. The study examines four core constructs—perceived usefulness, effort expectancy, financial planning behavior, and organizational support—alongside demographic and socioeconomic controls. Using ordinal logistic regression, the findings reveal that comfort with AI is more strongly associated with confidence in AI-generated outputs, frequency of AI interaction, and perceived organizational readiness than with traditional demographic factors. Surprisingly, perceived utility of AI in retirement planning was negatively associated with comfort, suggesting a disconnect between expected benefits and user trust. The study highlights the importance of trust-building, exposure, and institutional support in fostering AI adoption. Implications include the need for user-centered design, targeted training, and policy initiatives that promote digital financial literacy. These insights contribute to the growing body of research on technology acceptance and offer practical guidance for organizations seeking to integrate AI into consumer financial services.