<![CDATA[This study investigates the integration of Artificial Intelligence (AI) in forensic auditing and compares its implementation and effectiveness between developed and developing economies. It aims to highlight how AI technologies contribute to fraud detection, data analysis, and litigation support, while examining global disparities in adoption. A qualitative-comparative approach is employed, focusing on legal frameworks, technological readiness, and institutional capabilities across selected countries. The study synthesizes insights from academic literature, policy reports, and regulatory guidelines. The results indicate that developed economies benefit from advanced infrastructure and well-established regulatory frameworks that facilitate effective AI use in forensic auditing. In contrast, developing economies encounter obstacles such as technological gaps, limited resources, and legal uncertainties that hinder widespread adoption. The study provides practical implications for policymakers, regulators, and professional bodies by offering recommendations to strengthen institutional capacity, improve legal frameworks, and foster technological investment, especially in developing countries. By offering a cross-contextual analysis of AI adoption in forensic auditing, this research contributes to the limited body of comparative studies on the topic and underscores the importance of tailored strategies to bridge global disparities in AI-driven forensic practices.]]>
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