Abstract Enterprise resource planning (ERP) systems form the digital backbone of modern organizations by integrating business processes and data across functional domains. Recent advances in artificial intelligence (AI) offer significant opportunities to enhance ERP systems through intelligent automation and data-driven decision support. However, existing research primarily examines isolated AI applications and does not provide structured approaches for systematically incorporating AI capabilities into ERP-supported business processes. This study proposes a framework for integrating artificial intelligence into ERP systems by combining insights from automation theory, enterprise process modelling, and AI technology categorization. The framework decomposes ERP-supported business processes into four automation dimensions—data acquisition, information analysis, decision making, and action execution—and introduces a measurable method for assessing automation maturity through a geometric aggregation model. A systematic literature review and conceptual modelling approach are used to develop the framework and map AI technology categories, including narrow AI, generative AI, conversational AI, and agentic AI, to ERP process automation capabilities. The proposed framework contributes to the literature by extending automation theory to the context of ERP systems and by providing a structured method for analysing and guiding AI-driven ERP transformation. From a practical perspective, the framework offers ERP vendors and organizations a diagnostic tool for assessing current automation levels and identifying targeted opportunities for incorporating artificial intelligence into enterprise business processes.
Siar Sarferaz (2026) studied this question.