
AI Governance & Risk
Policy, data boundaries and approvals for AI that has to be accountable.
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- Certificate of Completion
- Self-paced, online
- Professional technology education
AI in a regulated or contractually exposed business is a governance question before it is a technical one. This program is for the people who have to answer for how it is used.
It covers data boundaries, approval design, record-keeping and risk assessment — and how to write a policy people can actually follow, rather than a document nobody reads.
- Set clear boundaries for what AI may see and store
- Design approval points with named accountability
- Assess risk without either panic or denial
- Write an AI policy people follow
- Keep records that stand up to a question later
- No technical background required
- Responsibility for how AI is used in your organisation
Short final assessment plus a policy outline exercise.
AI Governance & Risk — Certificate of Completion
Credential ID format: ARV-G-YYYY-NNNN
Program outline.
Module structure is published openly. Lesson content is produced to Arvanord's engineering documentation standard.
01The governance question
- What has to be answerable, and by whom
- Regulated work and contractual exposure
- Data protection basics for AI use
- Common failures that reach management
02Boundaries
- Classifying data by sensitivity
- What leaves the organisation, and what does not
- Third-party models and data handling
- Retention and deletion
03Accountability
- Approval design with named owners
- Human decision points
- Logging and record-keeping
- Escalation paths
04Policy
- Writing a policy people follow
- Vendor assessment questions
- Incident response for AI failures
- Review cycles
05Assessment
- Short final assessment
- Policy outline exercise
- Certificate issuance
Common questions.
Is this legal advice?
No. It teaches the governance structure — boundaries, approvals, records and policy — so that the questions you take to counsel are the right ones.
Does it cover data protection?
It covers data protection as it applies to AI use: what data may be processed, where it goes, how long it is kept and what must be recorded.
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