Platform / Risk and incidents
Keep governance alive after approval.
Classification is a point-in-time decision. Operational assurance begins earlier, when exposure findings are tested as risk hypotheses, and continues after launch as controls, indicators, incidents and material changes are reviewed.
Product demonstration · 2 minutes 14 seconds
Operational AI assurance
Connect risks, controls, indicators, incidents, FRIA readiness, recovery exercises and recurring managed reviews using hypothetical data. All organisations, people and systems shown were created for demonstration, and no client data appears.
Read the video transcript
Putting an AI system into use is where operational assurance begins. EU AI Fit brings together current risks, overdue reviews, open incidents and actions requiring an owner. Each risk records cause, possible harm, controls, indicators and escalation thresholds.
Incident records preserve facts and the rationale for internal or regulatory reporting decisions without declaring an event reportable automatically. Incident and recovery exercises preserve roles, communications, recovery objectives, lessons and corrective actions.
FRIA readiness structures Article 27 fact gathering, and the managed compliance desk brings inventory, classification, evidence, suppliers, incidents, training and regulatory updates into a recurring review. The result is an operating record, not a certificate.
Why this matters
A green status at launch says little about next quarter.
Model, data, users, suppliers and operating conditions change. Controls can exist on paper while alerts are ignored or intervention authority is unclear.
EU AI Fit keeps operational risks, controls, indicators and incidents attached to the governing system record. It prioritises transparent facts and overdue decisions instead of inventing a single compliance score.
Who it is for
The people watching live operation and authorised to respond.
- System owners monitoring live operation
- Risk and compliance teams reviewing controls
- Incident coordinators and decision makers
- Leadership teams receiving periodic assurance
How the work moves
Turn operating signals into controlled action and reassessment.
- 01
Review the hypothesis
Challenge assessment-generated suggestions, then record only credible risks with their cause, affected people, potential harm, likelihood and impact.
- 02
Define controls and indicators
Explain prevention, detection and response controls, with thresholds, data sources and review cadence.
- 03
Record events and decisions
Preserve incident chronology, severity, escalation, notification considerations and corrective action.
- 04
Decide and reassess
Approve residual-risk acceptance only after control evidence, keep accepted risks owned and dated, and reopen affected governance when material facts change.
In this scenario
Quality declines after a model update
A supplier changes a model and customer-support escalations rise beyond the agreed monitoring threshold.
The indicator breach opens a review against the affected system and links the supplier change to the operational evidence.
The owner records containment, customer impact, escalation decisions and whether classification, instructions, testing or staff briefing must be revisited.
Management can see the event, the response and the remaining decisions without a misleading red-to-green shortcut.
What is retained
A chronology of risk, control performance and response.
The managed compliance desk brings these records into a repeatable quarterly management review.
- Reviewed exposure-to-risk traceability
- Operational risk, control and residual-decision records
- Monitoring indicators and thresholds
- Incident chronology and escalation decisions
- Owned review dates, reassessment history and management approval
Source basis
The official material behind the workflow.
Source review updated 31 August 2026. Read our editorial and regulatory review policy, check the current source and obtain qualified advice for your circumstances.
- Regulation (EU) 2024/1689
The official consolidated legal text, including the 2026 amendments, and starting point for every assessment.
- Article 9 — risk management
The continuous, iterative risk-management requirements for high-risk AI systems.
- Article 26 — deployer monitoring
Official duties concerning use, human oversight, monitoring, logs and serious incidents.
Next step
Maintain the position, not just the launch file.
Put operational signals, incidents and decisions into a repeatable management cycle.
Explore the managed desk