Understanding AI readiness and ethical challenges in auditing: Evidence from Jordan’s private sector

While the adoption of artificial intelligence (AI) in auditing is revolutionizing the practice, its use is restricted in emerging economies. This study investigates the factors influencing private-sector auditors in Jordan’s readiness for AI, combining the concepts of the “Technology Acceptance Model (TAM)” and the “Unified Theory of Acceptance and Use of Technology (UTAUT)”. It examines the relationship between awareness, use, challenges, ethical issues, preparedness, and training requirements in the context of AI. The data obtained were from 112 auditors and analyzed using “Partial Least Squares Structural Equation Modeling (PLS-SEM)”. The findings showed that awareness about AI has a significant impact on both the utilization of AI and its preparedness, with hands-on experience boosting preparedness. However, structural problems and ethical issues negatively affect readiness. Furthermore, AI readiness is found to positively affect training needs, suggesting that greater readiness leads to greater need for training. The study adds to the literature by offering an integrated explanation of the phenomenon of the adoption of AI in auditing and underscores the need for creating enabling conditions and ethical governance. The findings offer insights into the practical steps that can be taken to promote the adoption of AI in investment, including investing in infrastructure, training, and the regulatory framework.