Governed Agentic AI for Enterprise Automation
DOI:
https://doi.org/10.5281/z84bac03Keywords:
Governed Agentic AI,Enterprise Service Automation,Secure Knowledge Management,Knowledge-Centric Decision Intelligence,AI Agents,Retrieval-Augmented Generation (RAG),Enterprise Knowledge Graphs,Intelligent Workflow Orchestration,AI Governance and Compliance,Context-Aware Decision Support.Abstract
In rapidly changing environments, enterprises must adapt at sufficient speed to survive. A popular experimental approach is to automate part of an organization by delegating the fulfilment of business functions to intelligence agents—software agents capable of performing work autonomously. An architecture is described where such agents are centered around an execution orchestrator and decision workflows. However, a key limitation of agentic systems is that speed of decision-making, required for throughput and reliability, is not always sufficiently fast, leading to delays. The principal driver is a gap in the architecture. In enterprise environments, it is essential that the internal process of the agent decision-makers is harmonized by an orchestrator and that any decision pipeline supporting its reasoning must operate with sufficient speed. This gateway constitutes the core of secure knowledge-centric decision-making: the production of decisions, recommendations, and predictions with the quality and assurance properties required by the task domain. Secure knowledge-centric reasoning is thus a counterpart to the agentic foundation being automated, enabling speed, reliability, and trust in the choices that affect the execution of business functions.
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