Reasonably foreseeable misuse
The standard used in Article 73 causality assessments (per the draft guidance, 2025-09-26) to limit the scope of reportable incidents to those where the AI system was used within its intended purpose or in ways that the provider could reasonably foresee as misuse, excluding purely unexpected or wild out-of-scope use. This concept connects directly to the risk management system under Article 9, which requires providers to identify and mitigate risks arising from reasonably foreseeable misuse.
Defined in 2 GAGE programs, which carry 2 distinct definitions of it. The wording above is taught in EU AI Act Implementation Expert.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
The standard used in Article 73 causality assessments (per the draft guidance, 2025-09-26) to limit the scope of reportable incidents to those where the AI system was used within its intended purpose or in ways that the provider could reasonably foresee as misuse, excluding purely unexpected or wild out-of-scope use. This concept connects directly to the risk management system under Article 9, which requires providers to identify and mitigate risks arising from reasonably foreseeable misuse.
Use of a system in a way not intended but predictable given how real people will operate it (for example a manager treating an advisory flag as an automatic ban). Article 9 requires the risk-management system to address it, not only the intended use.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The conformity file: assembling the evidence for the system you shipped in Module 3 · The EU AI Act: The Executive Map, Certified AI Governance Professional (CAIGP)
- Serious Incident Reporting (Article 73) · Post-Market Monitoring and Enforcement, EU AI Act Implementation Expert
Where it shows up at work
A definition is where Reasonably foreseeable misuse starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Classifies AI incidents by severity, runs containment, preserves evidence, manages notification, and closes the loop with lessons learned.
One lesson on this page teach it as a primary outcome.
Collects, labels and preserves the evidence that a control operated, a decision was made, and a claim can be defended to an auditor or regulator.
One lesson on this page teach it as a primary outcome.
Reads and applies content provenance infrastructure: C2PA content credentials, watermarking, machine readable AI labels, and the transparency duties that now require them.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Incident Response Leadneeds it at depth · 1 open posting this week
- Chief Information Security Officer, AI security focusneeds it at depth
- AI Auditorneeds it at depth · 9 open postings this week
- Physical AI Safety Engineer, autonomous systems editionneeds working knowledge
- Chief Audit Executive, AI audit editionneeds it at depth
- Chief Privacy Officer, AI privacy editionneeds working knowledge
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: EU AI Act Article 73; ISO/IEC 42001 Annex A incident controls; NIST AI RMF MANAGE 4; EU AI Act Articles 11 and 12.
One interview question about it
An AI system has just caused harm to a customer. Walk me through the first 48 hours.
Asked of candidates for ai incident response and recovery. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Cybersecurity and IT carries it as work you can show: Incident playbooks and post-incident reviews are your artifacts.
- A cybersecurity or information assurance degree carries it as a claim to back up: Incident response is a course; AI incidents add model failure to the playbook.
- Compliance and regulatory affairs carries it as work you can show: Audit-ready documentation is what you produce.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.