Analysis of External Auditor Intentions in Adopting Artificial Intelligence as Fraud Detection with the Unified Theory of Acceptance and Use of Technology (UTAUT) Approach

Abstract

The industrial revolution is a process of rapid change in industrial activities previously carried out by humans, replaced by machines. Artificial Intelligence is expected to be able to detect fraud, especially in financial reports, because Artificial Intelligence can analyze complex data in real time and recognize signs of fraud that auditors may have missed. The purpose of this study is to analyze the external auditor acceptance model to adopt Artificial Intelligence as fraud detection. This research uses quantitative research methods. Sources of data are obtained from primary data and secondary data. The primary data is obtaining from questionnaire. Distributing questionnaires in this study was carried out using Google Form. The secondary data obtained from journals, articles, online books. The result of this research, it can be concluded that Performance Expectancy, Facilitating Conditions have a significant positive effect on external auditors' Behavioral Intention in adopting Artificial Intelligence as a fraud detection. The variable Effort Expectancy has a positive but not significant effect on external auditors' Behavioral Intention in adopting Artificial Intelligence as a fraud detection. The variable Social Influence has a negative but not significant effect on external auditors' Behavioral Intention in adopting Artificial Intelligence as a fraud detection.