Practical AI Governance
From policy to operational controls
Outcome: Operationalize AI governance into ownership, controls, and auditable workflows.
Control design, documentation standards, and governance operating model components.
Implementation Outcome
This course establishes how AI principles and policies become real governance mechanisms. Participants learn ownership models, control design, documentation practices, and workflows that withstand audit and regulatory scrutiny.
- Governance operating model (roles, ownership, decision rights)
- Control register starter set for AI use
- Documentation and review cadence workbook
Controls & Evidence
- Designed for records retention, version control, and documented review cadence
- Supports internal control alignment and defensible oversight practices
- Produces an audit-reviewable evidence set suitable for internal audit request workflows
Data handling: No submission of sensitive or proprietary data is required to complete the program.
Risk Exposure
Lack of defensible policies or controls can result in significant, unmitigated enterprise risk exposure. This program addresses the risk areas most relevant to this capability.
- Policy exists without enforceable controls
- Unclear ownership and accountability for AI decisions
- Insufficient documentation for audit or regulator inquiry
- Inconsistent governance workflows across functions
Deliverables
Governance Operating Model
Ownership, RACI, decision rights, and escalation structure.
AI Control Register Starter
Control objectives, testability notes, and evidence expectations.
Workflow & Intake Patterns
How AI initiatives enter governance review and move through approvals.
Audit-Ready Documentation Guide
Versioning, record retention, and defensible rationale templates.
Governance Lifecycle Integration
- Baseline: Establish policy-aligned use patterns and minimum control expectations across affected teams.
- Oversight: Assign accountable owners, decision rights, and escalation paths for AI-assisted activities.
- Monitoring: Define review cadence, metrics, and control checks aligned to operational reality.
- Documentation: Maintain version-controlled artifacts and evidence suitable for records retention and review.
- Audit Review: Enable internal audit and leadership review with traceable controls, decisions, and evidence.
Buyer Questions
Does this require sharing confidential data with the provider?
No. The program is designed for policy, controls, and safe-use practices. Participants can complete the program without submitting sensitive or proprietary data.
Who should attend?
Governance, risk, compliance, legal
What evidence is produced for audit review?
Version-controlled artifacts (policy templates, oversight workbook outputs, and control-aligned documentation) suitable for internal audit requests and governance reviews.
How is it deployed?
On-demand delivery with enterprise licensing options. LMS and SSO integration can be included in rollout scoping.
How are artifacts maintained over time?
Artifacts are designed for version control and periodic review. Organizations can align updates to internal change management and records retention requirements.
Request Enterprise Pricing
For rollout scoping (seat counts, deployment model, LMS/SSO integration, and licensing options), request enterprise pricing and deployment scope.