Artificial intelligence (AI) can support the company’s internal audit function (IAF) by delivering substantial strategic oversight, minimizing manual procedures, and making possible additional value-added auditing service. Currently, there are research gaps in the literature, such as limited studies on the topic, low AI adoption rates in the IAF across different countries and regions, and a shortage of comprehensive frameworks for effectively using AI in the IAF. Hence, this review work aims to fill the research gap by offering an outline of research avenues on the topic in the literature and suggesting a new compressive framework for the effective use of AI in the IAF. This paper undertakes a systematic literature review (SLR) approach and aspires to highlight the state of research on the use of AI in the IAF, to deliver insight for scholars and industry experts on the issue, and to reveal the implications for IAF of the new AI technology. Moreover, to quickly make artificial intelligence work in internal audit functions, the CACS framework was recommended with attributes such as commitment, access, capability, and skills development (CACS). This work provides significant contributions for guiding future research directions and the development of theoretical foundations for the IAF field. On a practical level, the work will help internal auditors to assess and understand the potential advantages and risks of implementing AI in their organization’s IAF. For regulators, this review should prove useful for updating regulations on internal auditing in the context of using advanced technology such as AI and for ensuring the compliance of internal auditing practices to the evolving technology. Organizations can also benefit from this review to decide whether AI investments in their IAF are justified. This review made an initial extensive SLR on AI use in the IAF as a basis for developing new research avenues in auditing and accounting.

人工智能 (AI) 可以通过提供实质性的战略监督、最大限度地减少手动程序并提供额外的增值审计服务来支持公司的内部审计职能 (IAF)。目前，文献中存在研究空白，例如对该主题的研究有限，不同国家和地区的IAF采用率较低，以及缺乏在IAF中有效使用AI的综合框架。因此，本综述工作旨在通过提供文献中该主题的研究途径概要并提出在 IAF 中有效使用人工智能的新压缩框架来填补研究空白​​。本文采用系统文献综述（SLR）方法，旨在强调人工智能在 IAF 中的应用研究现状，为学者和行业专家提供有关该问题的见解，并揭示新的人工智能对 IAF 的影响。人工智能技术。此外，为了快速让人工智能在内部审计职能中发挥作用，推荐了具有承诺、访问、能力和技能开发（CACS）等属性的CACS框架。这项工作为指导 IAF 领域未来的研究方向和理论基础的发展做出了重大贡献。在实践层面上，这项工作将帮助内部审计师评估和了解在其组织的 IAF 中实施人工智能的潜在优势和风险。对于监管机构而言，这种审查对于在使用人工智能等先进技术的背景下更新内部审计法规以及确保内部审计实践符合不断发展的技术很有用。组织还可以从这次审查中受益，以确定对其 IAF 的人工智能投资是否合理。本次审查对 IAF 中人工智能的使用进行了初步广泛的 SLR，作为开发审计和会计新研究途径的基础。