AI monitoring plan
Signals, thresholds, frequency and accountable owners
05 / OPERATIONS
Monitoring & incidents.
Keep deployed AI observable, support safe intervention and reassess when the operating environment changes.
Explore the processHOW IT WORKS
The operational response loop
Production AI requires more than uptime checks. Monitor quality, safety, drift, user feedback, security events and changes in how the system is used.
STAGE01
CONTROL FOCUS
Observe
Capture live signals
EVIDENCE TO CAPTURE
Quality, drift, latency, cost, complaints and security indicators
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 thresholds trigger an alert or stop condition?
- Who is on call and empowered to disable the system?
- How are incidents fed back into risk and model reviews?
TANGIBLE OUTPUTS
What good looks like.
Incident response runbook
Severity levels, containment, rollback and escalation
Change & reassessment log
Changes in data, models, vendors or intended use and review outcomes
MEASUREMENT
Signals worth tracking
Illustrative measures to adapt to your organisation's risk profile and delivery model.
Time to detect and containUnresolved high-severity alertsReassessments completed on time