Auditing Corporate Disclosures with the Assistance of Task-Specific Artificial Intelligence – Evidence on Effectiveness and Efficiency

This study examines auditors’ perceptions of how task-specific artificial intelligence (AI) im-pacts the effectiveness and efficiency of auditing corporate disclosures, particularly manage-ment reports. Based on a survey of employees of a Big 4 audit firm in Germany, we analyze experiences with an AI tool designed to assist in detecting misstatements in management re-ports, e.g., by automatically identifying and matching disclosure requirements with reported content. The results indicate that the AI tool enhances audit effectiveness and efficiency alt-hough this result is less pronounced in supporting the detection of more complex qualitative issues. Perceptions of the AI tool’s impact are shaped not only by its technological features but also by auditors’ roles, expertise, and engagement with digital transformation. Auditors’ per-ceptions of potential deskilling effects and level of trust in AI outputs also vary across these attributes, emphasizing the relevance of implementation strategies, training, and transparent communication when integrating AI into audit workflows.