The Mediating Role of Control Risk in the Relationship between Technological Factors and AI-Based Predictive Analytics Adoption: Evidence from Audit Firms in the US

The purpose of this study was to investigate the factors that influence the adoption of AI-based predictive analysis in professional audits and to highlight the role of control risk in the decision-making process. The research methodology used was an online survey that targeted accountants and auditors working in audit firms and was distributed using Facebook ads. The findings indicated that control risk mediates the relationship between technological variables and the adoption of AI-based predictive analysis. The study also identified preparedness for IT challenges as the primary driver for adoption, but other factors played a significant role as well. The originality of this study lies in its integration of audit quality, preparedness for IT challenges, and control risk into the TOE model within the technological context. Furthermore, the study proposes control risk as a mediating variable in the study model in the context of the audit profession. The research limitations of this study include the non-random distribution of data among respondents due to the targeting tools used in the survey. The implications of this limitation are that the study's findings may not be generalizable to a wider population of accountants and auditors. Additionally, the study does not consider the impact of cultural and institutional factors that may affect the adoption of AI-based predictive analysis in professional audits. Future research is recommended, considering these factors, to provide a more comprehensive understanding of the adoption of AI-based predictive analysis in professional audits.