Artificial Intelligence Adoption and Perceived Audit Engagement Performance: An Empirical Study of Moroccan Auditors

Abstract

Artificial intelligence (AI) is progressively transforming audit practices, yet its effects are mainly documented in advanced economies. In Morocco, a market characterized by intermediate digital maturity and a fragmented audit landscape, empirical studies mostly address the intention or readiness to adopt AI rather than its effective use in audit engagements. This study examines the relationship between the effective use of AI tools, perceived benefits and change in practices, on the one hand, and perceived audit engagement performance, on the other. Drawing on the Technology Acceptance Model, the study relies on a questionnaire survey of a non-probability sample of 40 auditors working in Morocco; data were analyzed using multiple linear regression. The model shows high explanatory power (R² = 0.888; p < 0.001), and only the effective use of AI tools is significantly associated with perceived performance (β = 0.937; p < 0.001). The study shifts the focus from adoption intention to effective use and suggests that, in an emerging context, the concrete implementation of AI tools matters more than perceptions of their benefits. The non-probability nature and small size of the sample limit the generalizability of the findings; the perceptual measure of performance, collected from the same respondents, raises common method bias concerns, and the observed associations do not allow causal conclusions.