Governed Agentic AI for ITSM and HRSD Automation
Keywords:
Governance-Native Agentic AI, Enterprise Automation Architecture, AI Governance Frameworks, Agentic Operating Systems (AOS), Retrieval-Augmented Generation (RAG), Knowledge-Rich Conversational Systems, IT Service Management Automation (ITSM), Human Resource Service Delivery (HRSD), Enterprise-Scale Nudging, Governance-by-Design AI, Agentic AI Deployment Frameworks, RAG Pipeline Engineering, Conversational Knowledge Orchestration, Autonomous Enterprise Agents, Decision–Action Loop Design, Responsible Agentic AI, Corporate Automation Enablement, Context-Aware AI Agents, Operationalizing Governance in AI, Enterprise Conversational Platforms.Abstract
Governance-native agentic AI provides a promising architecture paradigm for enterprise automation needs. The concept is placed into context through exploration of the role of governance in AI development, supported by a framework for designing and deploying such systems. The architecture is then exemplified through definition of requirements and an RAG pipeline development approach for IT Service Management (ITSM) and Human Resource Service Delivery (HRSD) operations, with particular focus on the practical establishment of RAG systems for knowledge-rich conversational contexts. The discussion highlights the novelty of the initiative and its support of implementation of enterprise-scale nudges.
Artificial Intelligence (AI) is now a key enabler of corporate automation initiatives. Such systems perform a myriad of tasks, particularly in the Information Technology (IT) and Human Resources (HR) functions of enterprises, and are widely presented with autonomous agent labels. However, while the AI product offerings of the major technology companies have grown in sophistication, the accompanying Agentic Operating Systems (AOS) technologies are far less developed. Hence, few AI systems are actually agentic in functioning, and even formal agents sense decisions and actions assigned within the bounds of a specific conversation context.
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