title: “AI Change Management” description: “Managing material changes to AI systems, governance conditions, controls, and lifecycle decisions.”
AI Change Management
Change management ensures that material changes to an AI system, its operating environment, or its governance conditions are identified, assessed, approved, implemented, and traceable. Within AIGO, change management connects lifecycle activity with risk management, controls, evidence, assessment, approval, monitoring, assurance, and continual improvement.Purpose
Changes can alter: * system behavior * intended use * deployment context * risk exposure * control effectiveness * accountable roles * stakeholders * regulatory applicability * evidence requirements * monitoring requirements * assurance conclusions Change management therefore helps determine whether existing governance decisions remain valid after a material change.Material changes
A change should be evaluated for materiality rather than assumed to be material or immaterial solely because of its technical scope. Examples of potentially material changes include: * changes to intended use * changes to system capabilities or behavior * changes to deployment context * changes affecting risk exposure * changes to classification * changes to applicable governance requirements * changes to implemented controls * changes to accountable ownership * significant model or component changes * changes affecting monitoring or assurance requirements * changes that introduce new stakeholders or affected populationsChange assessment
A governed change may require reassessment of: * AI system classification * risks and risk treatment * controls * approvals * monitoring * assurance * evidence * intended use * affected stakeholders * lifecycle status * applicable requirements The outcome of the assessment should determine which existing governance records remain valid and which require revision or re-approval.Traceability
Significant changes should be traceable to: * the affected AI system * the change record * the rationale for the change * the impact assessment * relevant risks * affected controls * supporting evidence * required approvals * implementation actions * resulting monitoring or assurance activities This traceability helps maintain a coherent governance history throughout the AI system lifecycle.Machine-readable representation
AIGO provides a machine-readable Change Schema for representing governed changes and their associated information. The Change Schema is part of the AIGO machine-readable governance layer and can be related to other governed records such as AI systems, risks, controls, assessments, approvals, monitoring, assurance, and evidence.Relationship to evaluation
Changes may trigger governance reassessment or evaluation activities. Where machine-readable governance rules and evaluations are used, a material change can become an input to determining whether relevant governance conditions, controls, or decisions continue to satisfy defined requirements.Source
The canonical procedure is maintained in:guidance/02-procedures/07-AIGO-AI-Change-Management-Procedure-v0.1.md
The corresponding machine-readable structure is:
schemas/08-change/08-AIGO-Change-Schema-v0.1.json