Topic

Risk Controls

Risk controls are the specific safeguards, policies, and technical measures that organizations implement to mitigate identified AI governance risks and ensure compliance with regulatory requirements. These controls span preventive measures (such as data quality checks and model validation), detective measures (like monitoring for bias or performance degradation), and corrective actions taken when issues arise. Effective risk controls are central to enterprise AI governance because they translate risk assessments and regulatory obligations into concrete operational practices that reduce the likelihood and impact of AI-related failures, security breaches, or compliance violations.

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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