AI Incident Response

When an AI system fails, misbehaves, or is questioned by regulators — a practitioner’s playbook for detection, response, disclosure, and post-incident learning.

Who this is for

• Incident response and crisis management leads
• Compliance and legal functions
• Product and engineering leads for critical AI systems
• Communications and regulatory affairs

What you will be able to do

• Define what counts as an AI incident, at appropriate severity thresholds
• Detect incidents through monitoring, complaint, and audit signals
• Contain, investigate, and remediate an incident with the right cross-functional team
• Manage regulatory notification obligations (including the Article 73 serious-incident regime)
• Communicate an incident to affected users and the public without making things worse
• Run a post-incident review that produces actual learning

Syllabus

Each module comprises a mix of structured reading, worked examples, and applied exercises. Every programme concludes with an integrated written assessment marked against the published rubric.

Module 1. What is an AI incident

Definitions across regimes (EU AI Act, sector frameworks, ISO). Severity classification. Distinguishing incidents from ordinary performance issues.

Module 2. Detection

Monitoring architectures. Complaint channels. External sources. When automated detection is enough and when it is not.

Module 3. The response operating model

Roles: incident commander, technical lead, legal, communications. Playbook design. Runbooks.

Module 4. Investigation and containment

Preserving evidence. Root cause analysis for AI failures. When to pause the system.

Module 5. Notification and disclosure

Regulatory notification obligations across regimes. Article 73 in practice. Customer and public communications.

Module 6. Remediation and reinstatement

Fixing the immediate cause. Fixing the systemic cause. Getting the system back into production safely.

Module 7. Learning

Post-incident review that changes behaviour. Feeding lessons back into the AIMS.

Assessment

Sample question

Your credit-scoring model has produced a scoring pattern that appears to disadvantage a protected group. A journalist is asking questions. Walk through the next 24 hours.

Assessments are marked by a named human examiner against the four-dimension rubric: regulatory accuracy (30%), applied judgement (30%), artefact quality (25%), communication (15%). Pass at 60, distinction at 75.

Prerequisites

Working knowledge of enterprise incident management. EU AI Act Foundations is helpful for the regulatory context.

Certification

On successful completion (pass mark 60), you receive a SAAII Certified Practitioner (CP) — AI Incident Response credential. The credential is CPD-accredited, verifiable at thesaaii.com/verify, and forms one component toward higher-tier credentials. See the certification ladder for how it stacks.

Cohort licensing available from £395/seat (10+). Public sector, education, and registered charity: 20% discount. Instalment plans available for programmes at £495 and above. See For organisations and the FAQ for detail.