Generative AI in Financial Reporting

• 成果类型: Article
• 署名作者: Blankespoor, Elizabeth; Dehaan, Ed; Li, Qianqian
• 署名单位: University of Washington; University of Washington Seattle; Stanford University
• 刊物名称: JOURNAL OF ACCOUNTING RESEARCH
• ISSN/ISSBN: 0021-8456; 1475-679X
• DOI: 10.1111/1475-679x.70050
• 发表日期: 2026-06
• 页码: 1189-1232
• 关键词: generative AI; Financial reporting; Large language models; GPT; Textual analysis; complexity

摘要

Generative artificial intelligence (GAI) will likely alter many aspects of the financial reporting process and spawn a deep stream of academic research. We take an early step by examining the extent to which firms have begun using GAI in one important part of the reporting process: writing disclosures. We begin by evaluating a commercial tool's ability to detect GAI writing in disclosures, and we find that it reliably identifies even very small amounts of GAI usage in realistic samples. We then examine firms' actual earnings press releases, conference call prepared remarks, risk factors, MD&As, and IPO filings through 2024 and find statistically significant GAI usage in all five disclosure types, with up to 4.5% of new text written by GAI in 2024. Usage is predictably higher in the cross-section, and filings with higher GAI have systematically different linguistic properties. Our study provides early insights into the use and effects of GAI in financial reporting, and it motivates future research in this evolving area.