An Agentic ERP Governance Framework for Autonomous AI Agent Deployment in Cloud-Based Industrial Management Systems

Abstract

Cloud ERP platforms have passed through three distinct automation eras. Scripted batch jobs gave way to robotic process automation, and RPA is now giving way to autonomous agentic AI — systems that reason over enterprise data, select tools dynamically, and execute multi-step business workflows without human direction at every step. The shift is not merely a capability upgrade. Agentic systems behave non-deterministically, invoke tools whose scope may exceed what static governance models anticipate, and can produce cascading process consequences in live financial environments. Governance frameworks built for predictive models and rule-based bots were not designed for this. This paper proposes the Agentic ERP Governance Framework (AEGF), a five-dimension instrument designed to guide the responsible deployment of autonomous AI agents in cloud-based industrial management systems. Drawing on Sociotechnical Systems Theory, the Technology-Organisation-Environment framework, and the NIST AI Risk Management Framework, the AEGF addresses Process Suitability, Autonomy Tiering, Governance and Auditability, Organisational Readiness, and Risk and Continuity Management as an integrated governance architecture. An application to accounts payable automation on Oracle ERP Cloud illustrates how the framework operates in a representative industrial management context.