IS Implementation & Adoption
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Paper Number
1362
Paper Type
short
Description
This paper explores and explains key factors affecting the adoption of Artificial Intelligence (AI) by auditing firms through the lens of the Technology-Organisation-Environment (TOE) framework. Using the multiple-case study method, the primary data collection was through semi-structured interviews with decision-makers of auditing firms, complemented by secondary data. The preliminary data analysis identified anomalies to existing theories, revealing the specificity of the AI adoption compared to other technology adoption processes. The findings show that firms’ adoption process is affected by the affordance of AI, barriers to adoption, communication process, staff’s AI-expertise, auditing regulation and client’s acceptance. This study contributes to the literature by providing a better understanding of AI adoption at the firm level, thus filling the gaps in the extant research. The findings strengthen the theories that underpin our understanding of the technology adoption by firms, revising, extending, and elaborating the TOE framework with more empirical evidence.
Recommended Citation
Yang, Jiaqi; Blount, Yvette; and Amrollahi, Ali, "Factors that Influence the Adoption of Artificial Intelligence by Auditing Firms" (2021). ICIS 2021 Proceedings. 5.
https://aisel.aisnet.org/icis2021/is_implement/is_implement/5
Factors that Influence the Adoption of Artificial Intelligence by Auditing Firms
This paper explores and explains key factors affecting the adoption of Artificial Intelligence (AI) by auditing firms through the lens of the Technology-Organisation-Environment (TOE) framework. Using the multiple-case study method, the primary data collection was through semi-structured interviews with decision-makers of auditing firms, complemented by secondary data. The preliminary data analysis identified anomalies to existing theories, revealing the specificity of the AI adoption compared to other technology adoption processes. The findings show that firms’ adoption process is affected by the affordance of AI, barriers to adoption, communication process, staff’s AI-expertise, auditing regulation and client’s acceptance. This study contributes to the literature by providing a better understanding of AI adoption at the firm level, thus filling the gaps in the extant research. The findings strengthen the theories that underpin our understanding of the technology adoption by firms, revising, extending, and elaborating the TOE framework with more empirical evidence.
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