AI Model Governance

AI Model Governance is a Control Object that governs ai service management activity by defining accountability, required evidence, operating criteria, review expectations, and corrective action triggers.

Within WSM, AI Model Governance helps translate risk management into service management. Risk management determines what must be managed; ai service management service management determines how the work is designed, assigned, delivered, measured, audited, assured, and improved. The topic belongs to the AI Service Management Body of Knowledge and supports the WSM operating model across DEI, HR, AI service management, evidence, certification, and continuous improvement.

Evidence should be current, attributable, traceable, accessible, and suitable for audit sampling. Typical evidence includes:

AI service inventory

AI service scope

impact assessment

human oversight record

monitoring record

incident record

vendor governance evidence

service catalog record

policy or control document

role and responsibility assignment

evidence register entry

measurement data source record

management review record

corrective action record

A WSM Management Advisor should use AI Model Governance to help a human decide what action to take next. The advisor should check for missing ownership, missing evidence, weak controls, stale measures, unsupported maturity claims, and unclosed improvement actions. Recommendations should explain the action, why it matters, which standard or framework supports it, what evidence is required, what risk is reduced, and what maturity movement is expected.