AI risk register
Scenarios, impact, likelihood, owner, mitigation and status
02 / RISK
AI risk management.
Identify foreseeable harms, prioritise material exposures and make mitigation decisions traceable.
Explore the processHOW IT WORKS
How risk moves to a decision
A useful AI risk process considers intended use, affected people, data, model behaviour, security and operational dependencies — not only model accuracy.
STAGE01
CONTROL FOCUS
Identify
Map the system and affected parties
EVIDENCE TO CAPTURE
Use-case context, data flows, affected groups and threats
Select any stage to see its control focus and expected evidence.
QUESTIONS TO ANSWER
Make it operational.
Use these questions to turn governance principles into decisions that your organisation can evidence.
- What could go wrong for users, customers or third parties?
- Which risks remain after controls, and who can accept them?
- What change or incident triggers a fresh assessment?
TANGIBLE OUTPUTS
What good looks like.
Risk treatment plan
Actions linked to control owners and measurable completion
Residual risk decision
Recorded approval, rejection or escalation with rationale
MEASUREMENT
Signals worth tracking
Illustrative measures to adapt to your organisation's risk profile and delivery model.
High risks without treatmentOverdue mitigation actionsResidual risks awaiting sign-off