Agent approvals: what must be approval-gated vs safe to auto-execute

    A practical control model for agentic AI: categorize actions by risk, define approval gates, enforce evidence prerequisites, and keep audit trails for every decision.

    Approval design is not a UI detail - it is the safety boundary that determines whether automation scales or becomes a liability.

    Use these references as you implement:

    The three buckets (keep them explicit)

    1) Auto-execute (low risk, reversible)

    Criteria:

    • Reversible without money movement or contractual commitment
    • Can be retried safely (idempotent or checkpointed)
    • Has clear success/failure states and operator visibility

    Examples:

    • Draft generation (summaries, suggested fields)
    • Queue routing (assignment and escalation)
    • Non-committing notifications (with rate limits)

    2) Approval-gated (money + commitments)

    Criteria:

    • Moves money, commits the company, or changes records that drive money
    • Produces irreversible external side effects
    • Changes permissions, vendors, or ledger-impacting structures

    Examples:

    • PO issuance and awards
    • Payment runs and vendor payments
    • Posting or finalizing accounting entries

    3) Fail-closed (high uncertainty or missing prerequisites)

    Criteria:

    • Evidence is missing
    • Confidence is low or the model flags an exception
    • Preconditions are not met (permissions, required documents, parent record checks)

    Behavior:

    • Deny the action
    • Log the reason
    • Route to a review queue with evidence requirements

    Evidence prerequisites: the real approval accelerator

    The fastest approval workflow is not “approve faster.” It is “approve with the right evidence attached.”

    Evidence-first design:

    • Link documents to the action chain (invoice, PO, GRN, quote PDFs)
    • Require prerequisites before approval is even requested
    • Make exceptions explicit with reason codes and ownership

    Make retries safe, or don’t automate

    If you cannot rerun safely, approvals will not save you from duplicates.

    Design principles:

    • Use deterministic checkpoints
    • Preserve audit history across reruns
    • Never “fix by manual cleanup” as the primary recovery plan

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