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企业人工智能漂洗与审计师风险决策——来自多模态数据的证据

Enterprise AI Washing and Auditors’ Risk Decisions——Evidence from multimodal data

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【作者】 袁春生; 郭振雄; 白玮东;

【Author】 Yuan Chunsheng;Guo Zhenxiong;Bai Weidong;

【通讯作者】 郭振雄;

【机构】 山西财经大学会计学院; 山西师范大学经济与管理学院;

【摘要】 近年来,随着资本市场对企业人工智能投资的高度关注,一些企业出现了人工智能漂洗现象。本文以2013—2023年我国沪深A股上市公司为研究样本,探究人工智能漂洗对审计师风险决策的影响。研究发现,企业人工智能漂洗会导致审计师提高审计费用。机制检验结果表明,人工智能漂洗加大了企业整体经营风险,通过强化审计师风险感知和增加审计投入,提高了审计费用。横截面检验显示,这一影响在分析师关注较低和审计师行业专长较低时更为显著。进一步研究发现,企业人工智能漂洗还会促使审计师披露更多人工智能相关以及与人工智能业务风险匹配的关键审计事项。拓展性分析表明,审计师实施的上述风险决策有助于提升审计质量。研究结论对审计师感知企业“技术光环”背后的实质性风险、优化人工智能相关风险评估模型具有借鉴意义。

【Abstract】 In recent years, as the capital market pays close attention to corporate artificial intelligence investment, some companies have resorted to AI washing. Using data from A-share listed companies in Shanghai and Shenzhen stock exchanges from 2013 to 2023 as a research sample, this paper explores the impact of AI washing on auditors’ risk decisions. Research has shown that enterprise AI washing can cause auditors to increase audit fees. The mechanism test results show that AI washing increases the overall operating risks of enterprises, and by strengthening auditors’ risk perception and increasing audit investment, it increases audit fees. Cross-sectional tests show that this effect is more pronounced where analysts pay lower attention and auditors have lower industry expertise. Further research indicates that enterprise AI washing will also urge auditors to disclose more key audit matters related to AI and matching AI business risks. Expansive analyses show that the risk decisions above implemented by auditors help improve audit quality. The research conclusions provide reference for auditors to perceive the substantive risks behind enterprises’ ‘technology halo’ and to optimize AI-related risk assessment models.

【基金】 山西省哲学社会科学规划重点课题(项目批准号:2025ZD099)的资助
  • 【分类号】F832.51;F239.4;F279.2;TP18
  • 【下载频次】467
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