This study investigated the association between organizational culture and the effectiveness of artificial intelligence (AI) tools in detecting financial statement fraud in the public sector, with a focus on the moderating role of organizational culture. The increasing complexity of the public sector financial system and the growing use of AI-based fraud detection tools necessitate an understanding of contextual factors that influence their effectiveness. The study is grounded in institutional theory and adopts a quantitative research design complemented by explanatory correlational analysis. A population of 820 participants from the Bayelsa State Ministry of Finance were involved in accounting and auditing functions across public sector institutions, while a sample of 380 participants was drawn using a stratified random sampling technique. Primary and secondary data were employed with a questionnaire as the major source of data collection based on a 5-point Likert scale. The questionnaire was tested using content and face validity, while reliability was determined by the Cronbach’s Alpha coefficient. The responses from the administered questionnaire were tested using univariate, bivariate and multivariate analysis. The SEM analysis revealed a positive and significant association between MAL, NLP, DTA, DIM, and EXS on the detection of financial statement fraud in the public sector. The results further revealed that organizational culture positively and significantly moderates the relationship between AI adoption and the detection of financial statement fraud in the public sector. The study concludes that AI tools alone are insufficient for optimal fraud detection performance in the public sector. Instead, their effectiveness is maximized when supported by a strong and ethical organizational culture. The study recommends that public sector institutions should integrate cultural development strategies with AI adoption policies to strengthen fraud detection systems and improve financial accountability.
Keywords: Artificial Intelligence, Fraud Detection, Organisational Culture, Public Sector, financial statement fraud detection
