Digital Information Governance (DIG®) is a discipline for keeping AI-influenced decisions defensible and auditable, ensuring a company's information is accurately represented, its decisions are traceable, and its AI use is provable to regulators, partners, and courts.
In plain terms, DIG is AI decision governance: making sure that when AI shapes a decision, an organization can still show what was decided, on what basis, and who is accountable. It is the decision layer that sits on top of data governance, information governance, and AI governance.[1]
The four pillars
DIG is built on four pillars. Each maps to obligations now appearing across NIST, the EU AI Act, ISO/IEC 42001, and US state law such as Texas's TRAIGA.[3]
Information Provenance
Where the information feeding a decision came from, and whether it can be trusted.
Decision Traceability
A record of what was decided, by what (human or AI), on what basis, and who is accountable.
Representation Integrity
Keeping the company accurately represented across AI systems, search engines, and data environments.
Audit Readiness
Being able to prove, on demand, that AI-influenced decisions met their obligations.
Explore the reference
The white paper
The full 42-page DIG standard, free as a PDF: the four pillars, the maturity model, the seven principles, and the operating model.
Definition
The canonical definition and how DIG differs from records-management information governance.
The framework
The four pillars as a working system, mapped to the major AI regulations.
AI decision governance
The category DIG belongs to, and why the decision layer is now the governance frontier.
Regulations
How DIG maps to NIST AI RMF, the EU AI Act, ISO 42001, and TRAIGA.
Glossary
Defined terms: provenance, traceability, representation integrity, audit readiness, and more.
Who created DIG
Matthew Bertram coined the discipline and holds the DIG® trademark.
Maturity model
Score how defensible your AI-influenced decisions are, across five levels.
Statistics
Verified, primary-sourced figures on AI adoption, the governance gap, and regulation.
Free self-assessment
Score your AI decision governance in eight questions. Nothing leaves your browser.
Score your live site
Enter your domain and the scorer reads your public pages for AI governance signals. No login, nothing stored.
Frequently asked questions
What is Digital Information Governance (DIG®)?
Digital Information Governance (DIG®) is a discipline for keeping AI-influenced decisions defensible and auditable, ensuring a company's information is accurately represented, its decisions are traceable, and its AI use is provable to regulators, partners, and courts. It is commonly described as AI decision governance.
How is DIG different from information governance?
Traditional information governance governs the storage, retention, and deletion of records and data. DIG is decision-centric: it governs how AI-influenced decisions are made defensible. DIG is the decision layer on top of data, information, and AI governance.
Who created Digital Information Governance?
Matthew Bertram, President of ModalPoint and CEO of EWR Digital, coined the discipline and holds the registered trademark DIG® (USPTO Reg. No. 8147558).
What are the four pillars of DIG?
Information Provenance, Decision Traceability, Representation Integrity, and Audit Readiness.
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. 8147558 (Supplemental Register), Digital Information Governance / DIG, owner Matthew Bertram. View source ↗