A Model for Incorporating AI into ERP Software

This paper presents a model for systematically incorporating artificial intelligence (AI) capabilities into Enterprise Resource Planning (ERP) systems. We begin by synthesizing definitions of ERP and AI from scholarly literature, establishing a foundation for understanding their integration. The paper then traces the evolution of ERP systems from simple inventory management tools to intelligent, cloud-based platforms, highlighting how each evolutionary stage has created opportunities for AI enhancement. We propose a methodology that dissects ERP business processes into four fundamental dimensions - data acquisition, information analysis, decision making, and action execution - each operating on a continuum from manual operation to full automation. Thus, we create a framework for assessing and enhancing AI capabilities into ERP business processes. The methodology enables ERP vendors and customers to systematically evaluate their current automation levels, define target states, and implement appropriate AI technologies to bridge identified gaps. We analyze four categories of AI technologies in context of ERP software - narrow AI, generative AI, conversational AI, and agentic AI - discussing their applications, implementation challenges, and potential for advancing automation across the four dimensions. This systematic approach transforms AI incorporation from an ad hoc initiative to a structured, measurable process that aligns technological capabilities with business objectives, ultimately enhancing operational efficiency and creating competitive advantages through superior insights and responsiveness.