We have automated our initial client proposal drafting using AI, but we are seeing wild swings in proposal quality. How do we construct a weekly Scorecard metric that measures the human verification of these AI outputs before they reach the client?

Question

Tyler Smith · Accepted Answer

Using AI to draft client facing materials can dramatically cut production times, but it introduces a major quality risk. If your team relies too heavily on automated drafts without proper human review, you will eventually send a flawed deliverable that damages a client relationship.

To manage this operational risk, you must measure human accountability on your weekly Scorecard. Do not just track the volume of outputs generated by the AI. You must track a metric that measures human verification, such as the weekly percentage of AI drafts audited and signed off by a manager.

This metric ensures that your team does not view AI as a replacement for their critical thinking. Every piece of content, quote, or report must have a clear human owner who takes full responsibility for its accuracy before it goes out the door.

If your Scorecard shows that proposal volume is up but the audit rate is dropping, you have a warning sign. You can immediately address this during your weekly Level 10 Meeting™ before a bad draft reaches a client.

By holding your team accountable for the validation of AI outputs, you protect your brand quality while still capturing the massive operational efficiency gains that AI provides.