Human–AI Collaboration in Financial Auditing: Examining Ethical Risks and Professional Responsibility in Generative AI Adoption

Abstract

This study aims to examine the influence of Ethical Risk Perception and AI Transparency on Responsible Gen AI Adoption, with Human–AI Collaboration Quality as a mediating construct in the context of financial auditing professionals. A quantitative approach was employed using a cross-sectional survey design, with data collected from 189 auditors, including internal auditors, external auditors, public accountants, and audit consultants selected through purposive sampling based on their experience and exposure to AI technologies. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The findings reveal that all hypothesized relationships are statistically significant, indicating that Ethical Risk Perception and AI Transparency positively influence both Human–AI Collaboration Quality and Responsible Gen AI Adoption. Furthermore, Human–AI Collaboration Quality significantly mediates these relationships, reinforcing its critical role in effective AI integration. The study highlights the importance of ethical awareness and system transparency in promoting responsible AI use in auditing and provides implications for developing governance frameworks for ethical and accountable Gen AI adoption in professional auditing practices.