AIGR · Institutional AI governance

Standards

EvidenceReviewDecision

Control alignment

Connect enterprise evidence to the obligations that govern the system.

AIGR organizes external obligations and internal control expectations into a traceable evidence model. Alignment supports coverage and review discipline without implying certification, endorsement or legal compliance.

Organize external obligations without turning the framework into a checklist.

Management

Governance systems

Accountability, decision rights, policies, operating controls and continual improvement.

Risk

Risk management

Classification, impact analysis, treatment, escalation and lifecycle review.

Security

Information protection

Access, system security, incident response and evidence of control operation.

Privacy

Data governance

Purpose, minimization, access, retention, deletion and accountable handling.

Regulation

Applicable obligations

Requirements are mapped according to sector, jurisdiction, system role and intended use.

Assurance

Evidence discipline

Controls are credited only when relevant, current, traceable and sufficient evidence is present.

Alignment principle

One artifact can support more than one obligation—but the mapping must remain explicit.

AIGR is designed to reduce duplicate evidence work by connecting a validated artifact to the controls and obligations it actually supports.

Enterprise assessment

Establish governance readiness for a defined AI system.

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