Conversational Enterprise Management Through Agentic AI: A Five-Pillar Framework for LLM-Driven ERP Systems

Traditional Enterprise Resource Planning systems impose complex menu-driven workflows requiring extensive training, limiting accessibility for non-technical users. This paper presents a five-pillar framework for agentic AI-driven ERP systems that transforms enterprise management from complexity to conversation. Integrating Large Language Models, Multi-Agent Systems, Natural Language Processing, Intelligent Process Automation, and Security Architecture, the framework enables natural language interfaces for intuitive enterprise interaction. Preliminary validation across three enterprise scenarios (finance, HR, supply chain) achieves 28 of 31 criteria passed (preliminary proof-of-concept, n = 3 scenarios). System dynamics analysis identifies four feedback loops governing adoption dynamics. Comprehensive empirical validation through enterprise deployments remains essential future work.