Governed RAG-Agent Architecture for Autonomous Enterprise Decisions
Keywords:
Generative Artificial Intelligence, Decision Automation, Enterprise Governance, Autonomous Agents, Compliance Risk Mitigation, Governance-Embedded Architecture, Action-Policy Decision Intelligence, ServiceNow Workflows, Embedded Policy Enforcement, Audit And Traceability, Intelligent Business Processes, Decision Intelligent Pipelines, Business-Process Auto-Detection, Process Classification Systems, Enterprise System Integration, Knowledge Repository Connectivity, Data Quality Monitoring, Situational Awareness Analytics, Reflex Decision Workflows, Scalable Enterprise AI.Abstract
Enterprises seek to harness emerging technologies such as generative AI to enable decision automation in business operations while maintaining governance, risk, and oversight. Existing architectures for building Autonomous Agents in Information Systems work well for narrow-band decision problems but fall short when adapting generative AI methods to solve problems requiring high governance and compliance risk mitigation. Existing ServiceNow implementations operate at ChatOps levels of automation but lack the otherwise available major platform functionality. Governance-Embedded Action-Policy Decision Intelligent architecture provides an end-to-end pipeline, embedded policy enforcement, built-in audit/traceability, and governance oversight of decoupled/parameterized ServiceNow Decision Intelligent Workflows.
The concept is being explored and tested in a large enterprise with the necessary conditions for success. The initial focus is business-process auto-detection and classification, with connector integration into enterprise systems such as global knowledge repositories, tracking systems, and data quality monitoring. These endpoints provide situational updates for Business-Process Decision Intelligence reflex workflows.
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