The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems

Journal article

This study examines the role of Artificial Intelligence (AI) in financial auditing by exploring its opportunities, implementation challenges, and strategic implications for the accounting profession in Indonesia. Using a mixed-methods approach with qualitative dominance, the research integrates interviews, surveys, case studies, and FGDs supported by NVivo and SPSS analysis. The findings indicate that AI adoption in auditing is still limited and shaped by professional readiness, regulatory alignment, and institutional capacity. Rather than emphasizing numerical adoption rates, the study highlights emerging patterns of digital adaptation, the perceived need for competency development, and the widening gap in technological preparedness. Theoretically, this research strengthens the discourse on digital transformation in auditing by positioning AI adoption within the frameworks of innovation diffusion and professional readiness. It offers a conceptual perspective on how technological disruption reshapes audit practices, ethical considerations, and regulatory expectations. The study provides insights relevant to academia, practitioners, and policymakers in advancing AI-based audit transformation

Authors: Mökander, J; Sheth, M; Watson, DS; Floridi, L

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: Minds and Machines
• Volume: 33
• Issue: 1
• Pages: 221-248
• Publication date: 2023-01-04
• DOI: 10.1007/s11023-022-09620-y
• EISSN: 1572-8641
• ISSN: 0924-6495
• Language: English
• Keywords: Artificial intelligence; Scope (computer science); Management science; Data science; Engineering; Context (archaeology); Computer science; Commit; Set (abstract data type); Knowledge management