Topic

Operational AI Governance

Operational AI governance encompasses the processes, policies, and controls that manage AI systems during their day-to-day deployment and use across an organization. It addresses how teams monitor model performance, manage data quality, handle incidents, and ensure compliance with established standards throughout an AI system's lifecycle. This layer of governance is critical because it bridges the gap between strategic AI policies and technical implementation, ensuring that deployed models remain safe, effective, and aligned with organizational risk tolerance and regulatory requirements.

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ResearchGlobal2026-06-16

GenAI in ITSM Deployments Require Formal Hallucination Controls and Access Governance, GSDC Guide Finds

The GSDC Council has published a practitioner guide on deploying generative AI within IT service management functions, covering governance and risk controls including access management, data privacy, hallucination detection, and compliance checks. The guide also recommends ongoing performance measurement to link AI governance to service outcomes. It is aimed at organizations operationalizing GenAI in ITSM contexts globally.

ITSM generative AI hallucination controls data privacy operational AI governance