Empowering Internal Control: A Case Study in Leveraging Data and Technologies
DOI:
https://doi.org/10.60154/jaepp.2024.v25n2p26Keywords:
Social Construction of Technology, Technologies Institutionalization, Data Analytics and Technologies, Internal Control AutomationAbstract
This essay responds to the PCAOB's call for insights into data analytics and emerging technologies in auditing by developing a Social Construction of Technology (SCOT) framework to embed data analytics and technologies to improve internal control performance. SCOT outlines four phases of institutionalization: problem definition, interpretative flexibility management, stabilization, and social construction. This paradigm is validated through a documented procedure of institutionalizing a data-driven analytic project optimizing the purchase-to-payment process at a state university. The study used a value-focused thinking approach to observe and identify the values at stake in the decisions about how communication among IT, auditors, and management impacts the adoption of technologies. The collected evidence highlights the importance of identifying suitable algorithms and qualified data as the starting point for technology’s institutionalization. Additionally, the case study demonstrates mechanisms for preparing an integrated and transparent data platform, emphasizing the role of integrating relevant social groups and technology in circulating emerging technology. This study offers a practical roadmap about how to fit AI and technologies into an institutional social management ecosystem. It contributes to the literature by addressing the emerging technology usage trap and improving analytics performance, offering practical value through a social construct roadmap for institutionalizing emerging technologies.
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