Learning hub
AI Governance
Practical AI governance starts by knowing where AI is being used, establishing accountability, and applying governance proportionate to context and risk.
It is the system by which an organization makes its use of AI visible, accountable, appropriately controlled and continuously governed so that AI can be used responsibly and deliver intended business value.
A practical governance flow
Govern the business use of AI alongside the systems, agents, models, platforms, and vendors that enable it.
- 01DiscoverWhere is AI being used?
- 02UnderstandPurpose • Owner • Context
- 03TriageWhat governance is needed?
- 04GovernRequirements • Risk • Controls • Decisions
- 05MonitorEvidence • Change • Performance • Risk
- 06Realize valueIs AI delivering what it was intended to?
Explore AI Governance
Start with the foundations, then move into decisioning, lifecycle governance, organizational accountability, and agent-specific concerns.
Foundations
What Is AI Governance?
Understand the purpose, scope, and practical operating model of AI governance.
Read guideAI Governance Framework
Turn principles into a repeatable operating model from discovery through value.
Read guideAI Inventory & Ownership
Connect technical AI objects to their business uses, context, and accountable owners.
Read guideDecide & assess
Operate & oversee
AI Governance Lifecycle
Carry governance from intake through operation, material change, value, and retirement.
Read guideRoles & Responsibilities
Separate business accountability, technical responsibility, specialist review, and oversight.
Read guideAI Governance Committee
Use central governance for material decisions, exceptions, policy, and portfolio oversight.
Read guideGovernance should be proportionate
Not every use of AI needs the same process. A low-impact use operating under approved rules should not automatically receive the same governance depth as AI affecting employees, customers, regulated processes, sensitive information, or consequential decisions. Triage determines what is recorded, reviewed, controlled, monitored, or escalated.
Topics we're developing
Future educational coverage will include:
- AI risk and controls
- EU AI Act
- NIST AI RMF
- ISO/IEC 42001
- Microsoft Agent 365
Building AI governance in your organization?
DigitalCore is exploring a practical governance layer for organizations that need more than spreadsheets without the complexity of enterprise GRC.
Join early access