Background: Digital transformation has increased the complexity of fraud risks in higher education institutions, requiring governance mechanisms, professional judgment, and technological capabilities to operate in combination. Objective: This research investigates the influence of Whistleblowing Systems and Professional Skepticism on Fraud Detection Effectiveness while examining the direct and moderating roles of Artificial Intelligence Readiness. Methods: A quantitative methodology was employed through a cross-sectional survey involving internal auditors, members of Internal Supervisory Units (Satuan Pengawasan Internal [SPI]), and university staff engaged in governance and fraud prevention across Indonesian higher education institutions. The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results: The findings reveal that Whistleblowing Systems, Professional Skepticism, and Artificial Intelligence Readinesseach have a positive and statistically significant effect on Fraud Detection Effectiveness. Artificial Intelligence Readinessalso significantly strengthens the relationship between Whistleblowing Systems and Fraud Detection Effectiveness but does not significantly moderate the relationship between Professional Skepticism and Fraud Detection Effectiveness. Conclusion: These results suggest that artificial intelligence supports fraud detection not by replacing auditors' professional judgment but by strengthening organizational preparedness to integrate intelligent technologies into governance frameworks. Therefore, effective fraud detection in higher education depends on the synergy among organizational governance, human expertise, and Artificial Intelligence Readiness.