Regulation guide

AI Verify Third-Party AI Governance

Operationalize the AI Verify Third-Party AI Governance requirements—from regulatory obligations and evidence collection to vendor assessments, continuous monitoring, governance, and remediation workflows.

Overview

AI Verify is an AI governance testing framework and toolkit, not a standalone binding regulation.

AI Verify helps organizations assess AI systems against governance and testing themes such as transparency, explainability, robustness, fairness, safety, accountability, and human oversight. It is useful for vendor AI because buyers need evidence about models they did not build.

Rather than prescribing identical controls for every relationship, the regulation emphasizes a risk-based approach, requiring organizations to apply governance, oversight, controls, monitoring, and due diligence according to the criticality and risk of each relationship.

This implementation guide explains what the regulation requires, how those requirements translate into operational controls and evidence, and how Halbarad helps organizations operationalize compliance through assessments, continuous monitoring, governance workflows, and supply chain risk intelligence.

Official Sources

Intent of the Guide

AI Verify helps organizations assess AI systems against governance and testing themes such as transparency, explainability, robustness, fairness, safety, accountability, and human oversight. It is useful for vendor AI because buyers need evidence about models they did not build.

Operationalization Requirements

  • Inventory AI use cases and third-party AI providers.
  • Classify use cases by impact, data sensitivity, autonomy, and human oversight.
  • Collect provider evidence on governance, testing, data use, security, privacy, and monitoring.
  • Track model changes, incidents, drift, and provider terms.

Evidence Requirements

  • AI use-case and provider inventory.
  • Risk classification and human oversight records.
  • Testing and governance evidence.
  • Contracts covering data use, model changes, incidents, and subcontractors.
  • Monitoring, issues, and approvals.

Common Gaps

  • Embedded AI features are not captured in vendor reviews.
  • Provider evidence does not explain data use or model updates.
  • Human oversight is described but not assigned to an owner.

How Halbarad Helps

Halbarad helps teams track AI providers, use cases, data access, evidence, downstream providers, changes, incidents, issues, and approvals.

Disclaimer

This guide is for general information only and is not legal advice. Review the official regulation, guidance, and supervisory materials, and consult qualified counsel or compliance advisors for your organization's specific obligations.