Penggunaan Data Analytics dan AI dalam Audit: Persepsi Auditor terhadap Skeptisisme Profesional
DOI:
https://doi.org/10.61722/jiem.v4i10.12961Keywords:
artificial intelligence, audit data analytics, auditor perception, overreliance, professional skepticismAbstract
This study synthesizes how auditors perceive the effect of data analytics and artificial intelligence (AI) on professional skepticism. Audit firms increasingly rely on analytics and AI, yet evidence on how these tools shape the auditor's questioning mind remains fragmented across contexts. Using a qualitative systematic-style literature review, we analyzed 20 peer-reviewed publications and scholarly chapters from 2022 to 2026 that examine auditors' views, adoption experiences, and judgment outcomes in technology-enabled audits. Sources were screened for relevance to auditors, AI or data analytics, and professional skepticism, then coded using thematic synthesis. Four themes emerge: AI is perceived as an enhancer of efficiency and audit quality; overreliance and opacity threaten the questioning mind; the effect of AI on skepticism is conditional on auditors' knowledge, cognitive disposition, and continuous learning; and governance and training operate as safeguards. Evidence from Indonesia suggests that AI can weaken the link between a questioning mind and audit judgment while strengthening the effect of suspension of judgment. The findings imply that audit firms and regulators should pair technology deployment with explainability requirements, verification routines, and continuous skepticism training. Because the study is a literature-based synthesis, its conclusions are not statistically generalizable and call for primary perception surveys of auditors.
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