Challenges of Forensic Accounting in the Era of Artificial Intelligence: A Multi-Criteria Approach from an Expert Perspective (Fuzzy MCDM)

Abstract

This study aimed to assessing the key challenges facing forensic accounting in the era of artificial intelligence, as highlighted in recent local and international literature, by applying the Fuzzy Multi-Criteria Decision-Making (Fuzzy MCDM) approach. The research relied on the opinions of fifteen experts in accounting and auditing, represented by faculty members from the Accounting Department at Al-Zaytouna University. Their judgments were analyzed using the Fuzzy Analytic Hierarchy Process (FAHP) implemented through MATLAB, with results validated using Expert Choice software. The findings revealed that legislative and regulatory challenges constitute the most significant obstacle to forensic accounting under digital transformation, followed by educational and academic challenges, and human and professional challenges, while technical and data-related challenges ranked last. Furthermore, the study evaluated a set of proposed strategies to address these challenges, showing that legislative and technological updates ranked first, followed by academic development and professional empowerment. The study recommends strengthening legislative and regulatory frameworks, updating educational programs, and enhancing professional competencies to support the effective adoption of artificial intelligence in forensic accounting and improve the efficiency of financial fraud detection.