Artificial Intelligence Readiness and Adoption in Auditing

With the rapid advancement of artificial intelligence (AI), professional auditors are increasingly integrating AI into their auditing processes. This study delves into the factors that influence the intention to adopt AI within the auditing profession, focusing on how auditors incorporate this technology into their practices. Utilizing a quantitative research approach, 130 usable responses were gathered from auditors in the Maluku region of Indonesia through a purposive sampling technique. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that perceived usefulness (PU), AI readiness (AIR), and competitive pressure (CP) significantly influence auditors' intention to adopt AI. However, perceived ease of use (PEOU) and top management support (TMS) were found to have no significant impact on AI adoption intentions. These findings provide critical insights for stakeholders involved in the development and implementation of AI in auditing, offering guidance on how to increase auditors' engagement with AI technologies. Furthermore, this research contributes to the growing body of literature on AI in auditing, offering fresh perspectives and deepening the understanding of auditors' behavioral intentions toward AI adoption.