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    AI Risk Management

    Application & enablementManagement of AI risks
    Editorially reviewed on: 1 source
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    The short answer · 10 words

    In short

    Identify, evaluate and adequately address risks of an AI system.

    Flow-alerta.cab (2026): AI Risk Management. https://flow-alerta.cab/en/glossar/ai-risk-management. Editorially reviewed on: 09 October 2026.

    How much detail would you like?

    Practical

    Connects technical decisions with responsibilities and operational limits.

    Example scenario: A company evaluates false information from a service bot and defines escalation and quality controls.

    Capture risks per application, assign actions and review for changes.

    At a glance

    Core
    The process looks at the specific system, its use and possible impacts. Measures and remaining risks are documented and re-examined in the event of changes.
    Use
    Connects technical decisions with responsibilities and operational limits.
    Example
    Example scenario: A company evaluates false information from a service bot and defines escalation and quality controls.
    Limits
    Treat one-off assessment as permanently valid; consider only technical errors; conceal residual risks.

    In context

    AI Safety

    Design and deploy AI systems to prevent or limit damage.

    AI Audit

    A documented verification of an AI system against specified requirements.

    AI Governance

    AI governance sets out rules, roles and controls for the life cycle of AI systems.

    Questions about this term

    Is the NIST framework a law?

    No. It is a voluntary framework; existing legal requirements must be examined in addition.

    All details and background

    The process looks at the specific system, its use and possible impacts. Measures and remaining risks are documented and re-examined in the event of changes.

    ELI5 – Explained simply

    You think about what can go wrong, how severe the consequences would be and what helps against it.

    Why it matters in practice

    Connects technical decisions with responsibilities and operational limits.

    Example

    Example scenario: A company evaluates false information from a service bot and defines escalation and quality controls.

    Pitfalls and limits

    • Treat one-off assessment as permanently valid; consider only technical errors; conceal residual risks.

    Origin & history

    NIST published the AI Risk Management Framework 1.0 for voluntary use in 2023.

    Use in mid-sized companies

    • Capture risks per application, assign actions and review for changes.

    Related terms

    Matching Flow-alerta service

    AI opportunity analysis & roadmapAI consulting: AI potential analysis & roadmap on tasks, data and prerequisites of a possible first AI use case.

    Matching tool / use case

    View use casesNIST AI RMF; Use Case: Risk Assessment for an AI Pilot

    Sources

    Quellenprüfung: 09.10.2026. Die Quellen belegen Definition und dokumentierte Einordnung; Anwendungsbeispiele sind mögliche Szenarien.

    Editorially reviewed on:

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