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    AI Governance

    Application & enablementControl of AI systems
    Editorially reviewed on: 2 sources
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    The short answer · 15 words

    In short

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

    Flow-alerta.cab (2026): AI Governance. https://flow-alerta.cab/en/glossar/ai-governance. Editorially reviewed on: 10 October 2026.

    How much detail would you like?

    Practical

    AI governance makes responsibilities and risk management traceable. Their effectiveness depends on whether rules are actually implemented and reviewed.

    Hypothetical example: A company introduces AI inventory, risk classes, owners, approvals, and incident pathways.

    Start with an AI inventory, clear responsibilities and controls that fit your risk and resources.

    At a glance

    Core
    It includes inventory, responsibilities, risk decisions, data, vendors, evaluation, documentation, approvals, monitoring and incidents. Governance is more than compliance.
    Use
    AI governance makes responsibilities and risk management traceable. Their effectiveness depends on whether rules are actually implemented and reviewed.
    Example
    Hypothetical example: A company introduces AI inventory, risk classes, owners, approvals, and incident pathways.
    Limits
    Only write guidelines; ignore Shadow AI; delegate responsibility to tools; no resources or effectiveness testing.

    In context

    AI Risk Management

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

    EU AI Act

    The EU AI Act regulates AI systems risk-based and distributes duties among different actor roles.

    Accountability

    Accountability in the AI context means that responsibilities, decisions and control paths are defined in such a way that actions and effects of an AI system can be understood and assigned.

    Questions about this term

    Is governance only for high-risk AI?

    No.

    Is it equal to compliance?

    No, it also controls value and quality.

    All details and background

    It includes inventory, responsibilities, risk decisions, data, vendors, evaluation, documentation, approvals, monitoring and incidents. Governance is more than compliance.

    ELI5 – Explained simply

    It clarifies who has to decide, check and take responsibility for what in AI.

    Why it matters in practice

    AI governance makes responsibilities and risk management traceable. Their effectiveness depends on whether rules are actually implemented and reviewed.

    Example

    Hypothetical example: A company introduces AI inventory, risk classes, owners, approvals, and incident pathways.

    Pitfalls and limits

    • Only write guidelines; ignore Shadow AI; delegate responsibility to tools; no resources or effectiveness testing.

    Origin & history

    NIST published the voluntary AI Risk Management Framework 1.0 in January 2023; GOVERN is an overarching function in it.

    Use in mid-sized companies

    • Start with an AI inventory, clear responsibilities and controls that fit your risk and resources.

    Related terms

    Matching Flow-alerta service

    AI adoption & supportAI implementation & support: clarify usage guidelines, limits, responsibilities and escalation paths.

    Matching tool / use case

    View use casesNIST AI RMF and Playbook; AI inventory, role matrix and documented risk controls.

    Sources

    Quellenprüfung: 10.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.

    Editorially reviewed on:

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