AI-driven ERP systems are transforming finance by enabling automation, predictive forecasting, fraud detection, and real-time reporting—but they also introduce significant new risks across data, algorithms, operations, cybersecurity, and compliance. Poor data quality or biased models can lead to flawed decisions, while opaque “black-box” AI creates audit and regulatory challenges. Operational risks include over-reliance on automation and integration failures, while expanded attack surfaces increase cybersecurity threats. Regulatory pressures demand explainability, auditability, and strict data governance. To mitigate these risks, organizations must implement strong AI governance frameworks, human oversight, model validation, technical controls, and vendor risk management. Ultimately, success depends on balancing AI-driven innovation with disciplined risk management, ensuring transparency, compliance, and resilience in financial operations.

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