Linking intention, readiness, and AI adoption: a configurational and capability-based perspective from accounting professionals in Syria

This study examines artificial intelligence (AI) adoption among accounting professionals in Syria by integrating the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with AI readiness. Using survey data from 408 accounting professionals, the study applies partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The results show that performance expectancy, facilitating conditions, hedonic motivation, and habit significantly influence behavioral intention, whereas effort expectancy and social influence do not. Behavioral intention is positively associated with AI readiness and AI adoption behavior. AI readiness also positively influences adoption behavior and demonstrates a significant indirect effect in the intention–adoption relationship. The fsQCA results reveal multiple sufficient configurations, highlighting equifinality and configurational asymmetry and indicating that AI adoption depends on combinations of motivational and capability-related conditions rather than individual predictors. The findings suggest that accounting firms and policymakers should strengthen AI literacy, professional training, digital infrastructure, data governance, and organizational support. The study extends UTAUT2 by incorporating AI readiness as a capability-related mechanism and provides context-sensitive evidence from Syria’s underexplored institutional environment.