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Enterprise Resource Planning (ERP) systems are critical for managing diverse business processes, including finance, human resources, supply chain management, and customer relationship management. Traditional ERP systems often struggle with workflow automation and real-time decision-making due to their reliance on manual configurations and limited automation capabilities. This paper explores the integration of Artificial Intelligence (AI) into ERP systems to enhance workflow automation. Specifically, it examines the use of Artificial Neural Networks (ANNs) to improve predictive accuracy and operational efficiency. The study includes a detailed analysis of the impact of AI-enhanced workflows on process cycle times, error rates, and resource utilization, supported by a case study involving a retail company. The results demonstrate significant improvements in operational efficiency, accuracy of predictions, and user satisfaction. The paper also discusses the challenges associated with AI integration, such as data quality, system complexity, and user acceptance, and provides recommendations for successful implementation. Future research directions are suggested, including the exploration of additional emerging technologies and the development of comprehensive integration frameworks.
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