Impact of Artificial Intelligence on Auditing - An Exploratory Study

审计 计算机科学 探索性研究 人工智能 业务 会计 社会学 人类学
作者
Ravi Seethamraju,Angela Hecimovic
出处
期刊:Journal of the Association for Information Systems [Association for Information Systems]
被引量:17
摘要

Artificial Intelligence (AI) assisted by the massive processing power and big data is poised to significantly influence the auditing profession. Though selective initiatives deploying AI technology for specific auditing tasks are in place in the big four firms, empirical evidence is sketchy. This exploratory qualitative study, using the Technology-Organization-Environment (TOE) framework as its broad theoretical lens, and semi-structured interviews as the data collection strategy, investigates the adoption of Artificial Intelligence (AI) in auditing in Australia and identifies the factors influencing the adoption. Adoption of AI by auditing firms, our study found, would not only result in improvement in audit quality and decision making but also helps them build capabilities to deliver value-adding AI consultancy services that are more profitable than traditional auditing. External entities such as auditing standard-setting bodies and regulatory bodies in Australia are lagging behind due to their conservative approach and constraining the adoption. Some of the challenges include use of poor quality data in the development of AI solutions, inability to document the use of technology for verification by regulators, potential human bias that could be built in the AI programs, 'black-box' nature of AI solutions that do not inspire trust, perceived legal and reputational risk of financial auditing work that limits the potential use of AI. The study found a significant influence of AI on various stages of the audit process and observes the potential disappearnce of some of the traditionally known audit stages or their merger with others with the adoption of AI.
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