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    Best Practices Guide

    Approval Authority for Exceptions to AI Risk Appetite

    Approval authority for AI risk appetite exceptions should rest with the accountable risk owner whose scope matches the potential impact, and it should escalate as the risk tier rises.

    Treat exception approval as a decision right, not a sign-off

    Security, privacy, legal, and risk functions advise. Assurance functions verify. The decision itself belongs to the accountable risk owner.

    Exception lifecycle with defined decision rights

    1. RequestThe requester submits justification, scope, and proposed compensating controls.
    2. AssessAdvisory functions evaluate impact and recommend a risk tier.
    3. ApproveThe accountable risk owner for that tier accepts or declines the risk.
    4. EnforceApproved scope becomes time-bound runtime policy with audit logging.

    An illustrative approval tier model

    Approval authority escalates as the risk tier rises. At each tier, the accountable risk owner whose scope matches the potential impact accepts or declines the risk.

    Tier by impact factors and prevent self-approval

    Advisory functions evaluate impact and recommend a risk tier, and the accountable risk owner for that tier makes the decision. Advisors recommend and assurance functions verify, so neither role substitutes for the approver.

    What an exception record must contain before approval

    Each approval needs a recorded justification, compensating controls, an expiry date, and review conditions. The record should include the following.

    • The specific risk appetite statement or policy requirement being exceeded
    • Business justification and the cost of not granting the exception
    • Scope: which agents, models, data, tools, and environments are covered
    • Compensating controls, each with a named owner and a way to verify it
    • Expiry date and the conditions that trigger early review or revocation
    • Approver, advisors consulted, tier assigned, and decision date

    Translate approved exceptions into runtime policy

    An approved exception should be enforced as scoped, time-bound runtime policy. The approved scope becomes the boundary of what is permitted, and audit logging records activity against it.

    Operating the model over time

    • Review the exception register on a schedule: Report active, expiring, and renewed exceptions to the governance body, and look for repeated exceptions to the same requirement.
    • Treat renewal as a new decision: Require current evidence that compensating controls worked, and re-tier the exception if scope or impact has changed.
    • Use repeated exceptions as policy feedback: If the same exception keeps being approved, revisit the risk appetite statement or the standard control instead of renewing indefinitely.
    • Keep decision rights documented and current: Update delegations when roles change, so the approver named in the record held authority at the time of the decision.

    Make approved exceptions enforceable

    Discuss how runtime policy, agent permissions, and audit logging can support your exception approval model.

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