Enterprise Resource Planning (ERP) systems, particularly SAP, face increasing demands for real-time operations and minimal downtime, necessitating sophisticated error management approaches. This paper examines the evolution from reactive to dynamic error management in SAP environments, analyzing theoretical frameworks and practical implementations. Through comprehensive literature review spanning 2000-2025, we explore hybrid error detection frameworks combining rule-based systems with artificial intelligence, achieving detection accuracies up to 94%. The study investigates process adaptation mechanisms, workflow management dynamics, and technical implementations leveraging SAP HANA capabilities. Key findings reveal that effective dynamic error management requires integration across technological, process, and human dimensions. The analysis demonstrates that hybrid frameworks combining traditional and AI-based approaches, coupled with real-time analytics and automated adaptation mechanisms, significantly enhance error detection and resolution capabilities. We propose recommendations for organizations implementing SAP systems, emphasizing predictive error management, ecosystem-wide integration, and democratization of error management capabilities. This research contributes to understanding dynamic error management as a strategic competence directly influencing business performance, customer satisfaction, and competitive advantage in contemporary enterprise environments.

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