Jianhua Tan , Samuel Chang , Ying Zheng , Kam C. Chan
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Effects of artificial intelligence in the modern business: Client artificial intelligence application and audit quality
Audit clients in various industries are investing significant funds in research and development for artificial intelligence (AI), machine learning, and related technological innovations relevant to their firm operations. In this study, we examine the impact of client AI applications on the quality of financial statement audits. Using 25,408 firm-year observations from a sample of Chinese firms, we document that firms developing and implementing AI technology exhibit, on average, a higher audit quality on their annual audits. This effect is transmitted by increased internal control quality and increased corporate transparency. Additional analysis suggests that this effect is moderated by the auditor's IT background, auditor-client distance, the client's corporate governance quality, and whether the firm belongs to a high-technology industry. Furthermore, we find that applications of AI also decrease audit lags and audit fees for the client. Given that the implementation of AI improves audit quality and reduces fees, we suggest that a firm's AI application improves operational efficiency and provides additional unforeseen benefits of improved audit quality for the firm.
期刊介绍:
The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.