Pillar Guide

AI Privacy Compliance

AI privacy compliance requires continuous governance across consent inputs, model outputs, data minimization, and explainable control decisions.

Governance principles

  • • Consent-aware processing gates for analytics and marketing pipelines
  • • Human-in-the-loop review for high-impact AI recommendations
  • • Prompt and output logging for internal and external audits
  • • Confidence scoring and policy guardrails for actionable responses

Regulation mapping

AI governance controls should map directly to GDPR accountability requirements, CPRA consumer rights, and India DPDP consent obligations. For US state laws, include universal opt-out and GPC-aware enforcement.

Execution layer

Use AI Compliance Copilot for control interpretation, then enforce decisions using consent management, scanner policies, and immutable audit evidence exports.