Human Approval Controls for AI Automation

AI governance / human control

Human approval should be
designed into the workflow.

“Human in the loop” is not enough unless the system knows exactly when to stop, who owns the decision, what evidence that person sees, and what happens if nobody responds.

Where Bridge Road keeps explicit approval gates.

Commercial commitments

Price exceptions, margin exceptions, nonstandard terms, large quotes, credits, refunds, purchases, and promises that create financial exposure.

Uncertain source data

Unknown SKUs, conflicting customer records, ambiguous quantities, incomplete documents, low-confidence extraction, or inconsistent system values.

Sensitive access

Customer information, employee records, credentials, financial data, regulated information, or actions that cross business-unit or role boundaries.

Irreversible actions

Deletes, cancellations, production changes, outbound messages with material commitments, and transactions that cannot be safely replayed.

Approval packet

The reviewer should get a decision, not another research project.

A useful approval request includes the proposed action, source records, validation results, exception reason, confidence signal when relevant, financial or customer impact, and clear approve/reject/edit choices. Every decision is recorded with the resulting system action.

Example: RFQ → Quote

An AI workflow extracts an emailed RFQ, matches the customer and products, retrieves approved pricing sources, and checks availability. A standard request that passes every rule can become a prepared quote. A price override, unknown SKU, missing requirement, or margin exception stops and routes to the responsible person before anything is sent.