The Impact of Artificial Intelligence on Auditing: Navigating Ethical challenges

Sammanfattning

Purpose – The aim of this study is to establish and discuss the present and potential ethical implications stemming from the use of AI in the auditing process, as told by auditors. Additionally, this study explores the steps that, both the auditor and their respective firms, are taking to navigate the complexities that AI can impose on the five fundamental principles of ethics by IESBA. Methodology – Data was collected using semi-structured interviews with auditors from two Big Four audit firms. Findings – Auditors perceive AI differently; sometimes as a decision-support tool or a potential replacement of the auditor, but currently AI serves mainly administrative functions. While optimistic about the potential of AI to enhance efficiency, auditors are aware of the ethical challenges AI can pose. The findings indicated that AI integration is transforming auditing roles, and will continue to do so, necessitating new skills, and posing risks of overreliance that may undermine foundational auditing competencies mainly among inexperienced auditors. The “black-box” nature of AI and biases in algorithms require auditors to maintain professional skepticism and judgment. Moreover, verifying clients’ AI-generated data showed to pose challenges due to inconsistencies and errors, which emphasized the need for updated ethical guidelines and regulatory oversight to ensure AI support, rather than replaces, human expertise in auditing. A consensus among the interviewed auditors was that adhering to the five ethical principles is crucial. We could show that audit firms are implementing training programs and guidelines to ensure ethical AI use, focusing on utilizing AI for administrative tasks rather than judgment-based work and promoting human verification of AI outputs. Analysis – The findings were analyzed through the lens of Rest’s Four-Component Model to bring a comprehensive framework for understanding the ethical implications of AI in auditing. This is because Rest’s model systematically captures the progression from the initial recognition of an ethical challenge to the practical application of ethical principles in auditing practices. Appropriately, it featured the interplay between AI advancements and ethical practices in the audit profession, which necessitate adaptive steps to uphold the five fundamental principles of ethics in a technologically advanced auditing environment. Practical implications – The thesis provides an understanding into the ethical implications of AI integration in auditing and supplies guidance for auditors and audit firms on navigating these challenges. It also notes the importance of policymakers balancing auditing ethics with technological advancements to prevent auditors from falling behind technologically advanced clients.