Level of Acceptance and Behavioral Intention on the Use of Artificial Intelligence in Internal Audit Procedure

Abstract

The integration of Artificial Intelligence (AI) into internal auditing is reshaping conventional audit methodologies by enhancing precision, efficiency, and analytical capacity. Despite its growing relevance, the degree to which internal auditors accept and intend to adopt AI technologies remains insufficiently examined. This study investigated the level of acceptance and behavioral intention among accounting professionals toward AI adoption in auditing, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Utilizing a descriptive-correlational research design, data were gathered from 431 accounting professionals selected through stratified random sampling. The research instrument assessed acceptance across four UTAUT constructs—Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions—and evaluated respondents’ behavioral intention to adopt AI tools. Results indicated generally high acceptance levels, with Performance Expectancy and Effort Expectancy emerging as key drivers. Significant differences in acceptance and intention were observed based on demographic variables such as age, job position, and AI familiarity. Furthermore, strong positive correlations were found between all acceptance constructs and behavioral intention. The study recommends targeted capacity-building initiatives and improved organizational infrastructure to facilitate successful AI integration. These findings provide valuable insights into the human and organizational dynamics influencing AI adoption in internal audit contexts and inform strategic planning for technology-driven transformation in the profession.