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Governance & Compliance

AI Products must operate under clear governance and adhere to applicable legal, regulatory, and ethical requirements.
Governance ensures AI Products remain accountable, compliant, and aligned with declared organizational principles.

Why Governance & Compliance Matter​

  • Regulatory Pressure → AI-specific laws (e.g., EU AI Act, NIST AI Risk Framework) require demonstrable governance.
  • Risk Management → Misuse, bias, or uncontrolled drift can expose organizations to legal and reputational harm.
  • Trust → Consumers, regulators, and society expect transparent accountability.
  • Alignment → Ensures consistency with enterprise-wide data, AI, and risk policies.

Governance Requirements​

1. Policy Alignment​

  • Must comply with enterprise governance frameworks.
  • Must declare compliance with AI-specific regulations (regional, industry-specific).
  • Must integrate with Data Product policies if the AI Product consumes or produces data products.

2. Roles & Responsibilities​

  • Declare AI Product Owner, responsible for lifecycle governance.
  • Define accountability across roles (developer, owner, compliance officer).
  • Identify escalation paths for risk incidents.

3. Risk Classification​

  • Each AI Product must declare a risk category:
    • Minimal Risk
    • Limited Risk
    • High Risk
    • Unacceptable Risk (prohibited)
  • Risk category determines required safeguards, monitoring, and reporting.

4. Compliance Controls​

  • Document applicable standards: ISO/IEC 42001, SOC 2, HIPAA, GDPR, etc.
  • Define testing and validation requirements before deployment.
  • Provide evidence artifacts: audit logs, performance reports, bias testing results.

5. Ethical Safeguards​

  • Explicitly declare prohibited uses (see Prohibited Uses).
  • Define mitigation strategies for fairness, transparency, and explainability.

Governance Mechanisms​

AI Products must include mechanisms to:

  • Audit → generate logs and evidence for compliance validation.
  • Review → undergo periodic governance reviews.
  • Enforce → enforce access restrictions and prohibited uses via policies.
  • Report → provide dashboards, APIs, or reports for oversight bodies.

Example​

Credit Scoring AI Product

  • Owner: AI Governance Lead.
  • Risk Category: High Risk.
  • Compliance Controls: EU AI Act Article 10 (data quality), GDPR Art. 22 (automated decisions).
  • Evidence Artifacts: fairness audit logs, retraining approval records.
  • Governance Mechanisms: Quarterly review with risk committee, prohibited uses enforced via PBAC.

Summary​

  • AI Products must be governed as first-class entities — not as uncontrolled assets.
  • Governance includes roles, risk classification, compliance controls, and ethical safeguards.
  • Products must support auditability, enforcement, and reporting mechanisms.

Principle: Without governance and compliance, an AI Product cannot be considered safe, ethical, or trustworthy.