Topic

Generative AI Deployment

Generative AI deployment refers to the process of implementing and operationalizing generative AI systems such as large language models and other foundation models into production environments and business applications. This involves critical governance decisions around model selection, infrastructure requirements, access controls, and monitoring mechanisms to ensure the systems perform safely and in compliance with organizational policies. For enterprises, managing generative AI deployment is essential because these systems present unique risks including hallucinations, data privacy concerns, potential bias, and regulatory exposure that require careful oversight before and after launch.

1 item

ResearchGlobal2026-07-08

Eight-Step ITSM Deployment Framework from GSDCouncil Puts Hallucination Detection and Data Privacy Controls at the Center of AI Governance

The GSDCouncil has published a research report outlining an eight-step framework for deploying generative AI in IT service management, with explicit governance requirements covering access controls, data privacy, hallucination detection, and regulatory compliance. The report includes named case studies and positions structured risk controls as prerequisites for AI-driven automation in ITSM. Compliance teams at organizations using AI in service desk and IT operations functions should treat the framework as a benchmark against which their existing controls can be assessed.

ITSM governance hallucination detection data privacy risk controls implementation framework IT service management generative AI deployment