Empirircal investigation into y-the integration of cloud-based artificial intelligence in auditing

Yazan Abdelmajid Abu Huson, Laura Sierra‐García, M. García-Benau, N. Aljawarneh
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Abstract

Purpose- The increasing prevalence of cloud computing and the rapid proliferation of artificial intelligence technologies have opened up novel prospects for enhancing auditing methodologies. This research aims to scrutinize the consequences of incorporating cloud-based artificial intelligence (CBAI) in auditing, focusing on its implications for audit clients, auditors, and the overall audit process. Methodology- A method of quantitative research was utilized in this study, where 322 questionnaires were distributed to external auditors in Jordan. The objective was to collect information on the potential enhancements brought about by cloud-based artificial intelligence in the auditing field. The study employed convenience random sampling, a technique involving the collection of data from readily available members of the population, which, in this context, refers to external audit offices in Jordan. Jordan has a total of 454 audit offices with a diverse range of auditors, including partner-owner auditors, assistant auditors, and certified auditors. The analysis of the gathered data was conducted using SmartPLS software, which employs structural equation modeling (SEM). Findings- The study's outcomes reveal the potential for cost savings associated with the adoption of CBAI, as well as the streamlining of audit procedures and the enhancement of overall efficiency. Moreover, the research observes the transformation of auditors' roles, with a shift towards a greater focus on analytical and advisory responsibilities, departing from traditional manual tasks. These findings underscore the potential advantages for audit clients, auditors, and the audit process, underscoring the significance of embracing these technologies to advance the auditing profession in the digital age. Conclusion- The study investigates how CBAI influences audit quality and efficiency through a thorough examination of data sourced from a sample of external auditors operating within the context of Jordan. Additionally, it delves into the significant advancements that CBAI can introduce to the auditing field, encompassing its potential for data storage and analysis, the improvement of communication between auditors and clients, the adoption of innovative audit techniques, and the shift from manual to digital auditing methodologies. Keywords: Cloud-based artificial intelligence, Auditing, Auditors, Cloud computing, Artificial Intelligence, Audit quality. JEL Codes: O30, O33, O35
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基于云的人工智能在审计中的应用经验调查
目的--云计算的日益普及和人工智能技术的迅速发展为改进审计方法开辟了新的前景。本研究旨在探讨将基于云的人工智能(CBAI)纳入审计的后果,重点关注其对审计客户、审计师和整个审计流程的影响。方法--本研究采用定量研究方法,向约旦的外部审计师发放了 322 份调查问卷。目的是收集有关云端人工智能在审计领域带来的潜在改进的信息。本研究采用了方便随机抽样技术,即从人口中随时可获得的成员那里收集数据,在本研究中,人口指的是约旦的外部审计机构。约旦共有 454 家审计机构,审计人员来自不同领域,包括合伙人审计师、助理审计师和注册审计师。研究结果表明,采用 CBAI 有可能节约成本、简化审计程序并提高整体效率。此外,研究还观察到审计师角色的转变,从传统的手工任务转变为更加注重分析和咨询职责。这些发现强调了审计客户、审计师和审计流程的潜在优势,突出了在数字时代采用这些技术推动审计行业发展的重要意义。此外,研究还深入探讨了云端人工智能在审计领域所能带来的重大进步,包括其在数据存储和分析方面的潜力、审计师与客户之间沟通的改善、创新审计技术的采用以及从人工审计到数字审计方法的转变:基于云的人工智能 审计 审计师 云计算 人工智能 审计质量JEL Codes:O30, O33, O35
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