Workshop’s Topic: We explore the potential value of generative artificial intelligence (AI) in identifying critical audit matter (CAM) topics and assess the informativeness of CAMs identified by AI and human auditors. We compare AI-generated CAMs with those reported by human auditors to evaluate their effectiveness in signaling financial reporting risks to investors. We further discern the information between AI-generated CAMs and overlapping and non-overlapping auditor-reported CAMs to investigate the (dis)advantages of AI relative to human auditors. While AI has superior information-processing capabilities and is less affected by human biases, it may be less informative than human auditors due to the lack of professional judgment and access to private client information. Our findings indicate that AI can predict approximately 37% of CAMs reported by auditors. Auditor-reported CAMs or AI-generated CAMs alone are generally not significantly associated with financial reporting risk or abnormal stock returns. However, the overlapping CAMs identified by auditors and generated by AI are significantly associated with financial reporting risk and abnormal stock returns, whereas CAMs identified exclusively by auditors or AI are not, suggesting a complementary role of generative AI and human auditors in identifying CAMs. Overall, our findings indicate that combining AI and auditor reports can help investors identify significant financial reporting risks and also highlight the information value of CAMs reported by human auditors.

Time and Location: 10:00 AM (GMT+8), Room A423 (School of Management)

Language: Bilingual (Chinese and English)