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AI Governance Checklist

AI governance checklist

An AI governance checklist is a practical list of controls for keeping AI-influenced decisions defensible. This one is organized by the four pillars of Digital Information Governance.

Use this checklist to test whether your AI-influenced decisions are defensible today. It is organized by the four pillars of DIG. To score yourself in two minutes, use the DIG maturity self-assessment.

Information Provenance

Decision Traceability

Representation Integrity

Audit Readiness

Frequently asked questions

What should an AI governance checklist cover?

The controls that make an AI-influenced decision defensible: the provenance of its inputs, a trace of who decided and why, accurate representation across AI systems, and the ability to prove all of it on demand. The DIG four pillars organize these.

How do I know where we stand?

Run the free DIG maturity self-assessment to score your organization on the five-level scale and get a recommended next step.

References

  1. NIST AI Risk Management Framework (AI RMF 1.0): Govern, Map, Measure, Manage. National Institute of Standards and Technology, 2023. View source ↗
  2. Information governance: the records and data lifecycle discipline (storage, retention, disposition), distinct from AI decision governance. ARMA International, Generally Accepted Recordkeeping Principles; AIIM. View source ↗
  3. EU AI Act, Regulation (EU) 2024/1689 (Official Journal of the European Union); ISO/IEC 42001:2023; Texas Responsible AI Governance Act (TRAIGA). View source ↗
  4. USPTO Trademark Reg. No. 99559923, Digital Information Governance / DIG, owner Matthew Bertram. View source ↗