Mapping User Perceptions of AI in Accounting and Auditing with the TAM—A Network Analysis Approach

This study examines the acceptance of artificial intelligence (AI) among professionals in accounting and auditing by applying the Technology Acceptance Model (TAM). The research addresses the broader question of how AI technologies are integrated into professional decision-making in financial services, with a focus on the determinants that shape user acceptance. A standardized survey, consisting of 21 items designed to measure TAM components, was distributed to accounting and auditing professionals. Data were analyzed through confirmatory factor analysis to validate the construct structure, and Pearson’s correlation and network analyses were used to identify relationships among variables. The results confirmed a robust seven-factor model with significant interrelations, highlighting AI knowledge as a central variable influencing perceived usefulness (PU), self-efficacy, and intention to use AI. These findings demonstrate that professional familiarity and confidence in AI tools are key drivers of technology acceptance. The study concludes that enhancing AI literacy can strengthen organizational readiness for digital transformation. Additionally, the research underscores the contribution of women-led scholarship in promoting responsible and inclusive approaches to AI adoption within the accounting and auditing sectors.