Manual vs AI call QA
Manual review is how most teams start: a manager listens to a few calls and fills in a scorecard. AI call scoring checks every call against the same scorecard. Here’s what actually changes, and what still needs a person.
| Manual review | AI call scoring | |
|---|---|---|
| Calls reviewed | Usually a few percent, picked by whoever has time | Every call you upload |
| Consistency | Varies by reviewer, mood and time of day | The same checks applied the same way to every call |
| Time to feedback | Days or weeks after the call | Minutes after upload |
| Finding problems | Only in the calls someone happened to hear | Alerts across all calls, such as promises outside policy or card numbers read aloud |
| Proof behind a score | The reviewer’s notes | A link to the exact line in the recording |
| Judgment calls | Strong: a person understands context | Good on observable behavior; a manager should review and override edge cases |
Where a person still matters
AI scoring is best at checks you can hear: did the rep read the order back, offer the add-on, explain the return policy. It’s weaker on tone and intent in unusual calls. The best setup lets the AI score everything, points a manager at the calls worth hearing, and lets that manager change any score with a note.
Getting started
Write down the five to ten things a great call on your line always includes. That list is your scorecard, whether you score by hand or not. Our free scorecard templates are a starting point.