Model & Program Governance
Operational controls for model & program governance, with maturity levels, evidence requirements, and implementation guidance.
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7 controls matching filters
AI Model Preview and Staged Release Policy
Distinguish preview and experimental access from approved production use. Require documented governance approval at each release stage before wider deployment.
AI System Intake and Approval Workflow
Use a standard intake process before new AI systems enter the organization. Record use case, data classification, risk tier, and ownership. Route approvals across relevant functions and retain governance, risk, and compliance (GRC) records.
AI Governance Program Milestone Framework
Set governance milestones throughout deployment. Require completion before a system advances to its next lifecycle stage.
Continuous AI Assurance Function Design
Operate an ongoing assurance function that produces regular evidence of control effectiveness. Give boards, regulators, and enterprise customers current records of the governance program’s performance.
Generative AI Input Data Classification
Classify data entering generative AI through prompts, background material, retrieved documents, results from connected tools, and conversation history. Address privacy, confidentiality, and regulatory risks absent from general data classification rules.
RAI Benchmark-Aligned Evaluation Framework
Map AI system evaluations to published benchmarks such as HELM Safety, AIR-Bench, and FACTS. Produce evidence regulators, auditors, and enterprise customers can compare against independent standards.
Emerging AI Modality Classification and Governance Extension
Detect new AI capabilities entering the organization, including ambient AI, agents that handle images and audio, brain-computer interfaces, and always-on assistants. Extend governance coverage before widespread deployment.