Four governance disciplines now sit in most regulated organizations. They are often confused because their names overlap, but each governs a different asset. Digital Information Governance (DIG®) is the newest layer: it governs the AI-influenced decision that the others enable.
| Discipline | What it governs |
|---|---|
| Data governance | Governs structured data: quality, lineage, access, and cataloging. |
| Information governance | Governs records and information: retention, compliance, and e-discovery. |
| AI governance | Governs models: bias, drift, explainability, and model risk. |
| Digital Information Governance (DIG®) | Governs the decision: whether an AI-influenced decision is defensible and auditable. |
Side-by-side comparisons
DIG vs. information governance
Decision-centric vs records-centric. The distinction that defines DIG.
AI vs. data governance
The model vs the data, and the decision neither governs.
AI vs. information governance
Model risk vs records, meeting at the decision.
Information vs. data governance
The broad umbrella vs the structured-data layer within it.
DIG vs. AI TRiSM
Gartner governs the AI system; DIG governs the decision it influences.
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References
- NIST AI Risk Management Framework (AI RMF 1.0): Govern, Map, Measure, Manage. National Institute of Standards and Technology, 2023. View source ↗
- 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 ↗
- 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 ↗
- USPTO Trademark Reg. No. 99559923, Digital Information Governance / DIG, owner Matthew Bertram. View source ↗