# Where people should approve AI-assisted freight work

Human-in-the-loop AI means a person can inspect, approve, correct, or reject a proposed action before it changes something consequential. In trucking operations, that boundary matters when a suggestion affects a driver, customer appointment, rate, invoice, or pay amount. Routine extraction can prepare the work; accountability stays with the team.

## An approval card should answer five questions

1. **What changed?** Show the field, old value, proposed value, and affected load.
2. **Why?** Show the source document, status event, or policy that prompted the proposal.
3. **How certain is it?** Mark missing, conflicting, or stale information.
4. **Who decides?** Name the role with authority to approve it.
5. **What happens next?** List the downstream records and messages the action will change.

Suppose a truck appears likely to miss a receiver appointment. The assistant may propose moving the appointment and notifying the driver. The dispatcher should see the timestamp of the status event, the current appointment, and the proposed replacement. If the underlying location is stale, the proposal should be held for verification.

## Set different thresholds for different work

Extracting a reference number into a draft load can have a lighter review than sending a customer notification or issuing an invoice. Define actions that always require sign-off, who can override them, and how corrections are recorded. Test an incorrect recommendation during the demo; the ability to recover is as important as a successful example.

RunaboutX's [AI TMS](/ai-tms/) presents human approval as part of its intended operating model. See [exception management](/features/exception-management/) for a load-level example and the [RFP checklist](/resources/guides/tms-rfp-checklist/) for vendor questions.

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Canonical: https://www.runaboutx.com/resources/learn/human-in-the-loop-ai/
Last reviewed: 2026-10-14