Responsible AI & Governance Corner
Retrospective edition3 min read

Rehearse the AI incident before the real one

Prepare to contain incorrect actions, not only unavailable systems.

Office of Responsible AI & Governance, GENELLIPSE

Business context. Practical action. Shared accountability.

UNDERSTAND THE CHALLENGE

The business issue

An AI service can remain available while producing harmful or misleading output. Incident preparation should therefore include erroneous recommendations, unauthorized actions and information exposure as well as technical outages.

PUT IT INTO PRACTICE

01

Define an operational trigger

Agree which events require investigation, restriction or suspension. Include user reports and business anomalies, not only infrastructure alerts. Make it easy for people to raise concerns without needing to diagnose the technical cause first.

02

Map containment to business effects

Identify how to disable a tool, restrict an audience or return to a manual process. Determine how affected work will be located and reviewed. Preserve evidence appropriately and avoid assuming that a corrected model response reverses actions already taken.

03

Practice the handoffs

Run a tabletop exercise with business, security, technology and communications participants. Introduce uncertainty and require explicit decisions. Record improvements and test them before closing the findings. The objective is a workable response, not an exercise designed to confirm that every existing procedure is perfect.

FROM DISCUSSION TO ACTION

A sequence your team can use

Select each stage to explore the proposed action. Adapt the sequence and controls to your business context.

AN ILLUSTRATIVE OPERATING SEQUENCE

Recognize

Detect and report a consequential AI failure.

↻ Review the evidence. Learn from exceptions. Refine the next decision.

Recognize. Detect and report a consequential AI failure.

Contain. Restrict the workflow and locate affected work.

Correct. Review consequences and verify improvements.

MEASURE WHAT MATTERS

Look for evidence of improvement

Establish a baseline and agree appropriate targets. These are proposed measures, not claims of customer results.

01

Time to containment

Elapsed time before unsafe activity is restricted.

02

Affected-work visibility

Cases identifiable for review and correction.

03

Verified improvements

Exercise findings retested successfully.

How Genellipse can help

Genellipse can design response paths across Cortex AI workflows, GeneSecure security processes and GeneComply evidence reviews. The exercise should involve the business owners who can authorize containment and correction, not only the platform team.

Cortex AI can support governed agent workflows and review coordination; GeneComply can organize control evidence; GeneSecure can support the agreed security processes. Genellipse helps design responsibilities, access and escalation around the business use case. Neither an AI platform nor a framework mapping automatically establishes legal compliance or transfers executive accountability.

Discuss your business challenge

Office of Responsible AI & Governance, GENELLIPSE

Sources & professional context

NIST — AI Risk Management Framework

The NIST AI RMF is a voluntary risk-management reference, not a certification or a substitute for applicable law. The workflow and examples in this article are Genellipse recommendations.

Original Genellipse editorial analysis, prepared October 10, 2026. References provide context and do not endorse Genellipse. Product scope, integrations and responsibilities are agreed for each engagement.