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Can AI grade support conversations?
Reviewing conversations for accuracy, tone and policy compliance. Historically a 2% sample.
Moves you from the 2% a manager samples to 100% coverage. Your scorecard decides whether that is useful.
Most support teams review about 2% of conversations, chosen by whichever manager had an hour spare. Automated QA scores all of them. That change is real, and it is worth less than it sounds unless one other thing is right.
From 2% to 100%
Full coverage removes sampling bias, which is the main reason traditional QA misleads. A manager who reviews ten conversations is reviewing ten conversations, not the queue.
The scorecard is the whole product
This is the part every vendor underplays. The tool grades whatever you tell it to grade. A long, vague rubric produces confident, meaningless numbers at industrial scale — worse than no QA, because now the numbers look official.
- Few criteria, not many. Five observable things beat twenty subjective ones.
- Observable, not inferred. Did the agent state the resolution time is a criterion; was the agent empathetic is not.
- Calibrate before you trust it. Have a manager score fifty conversations by hand and compare. Systematic disagreement means the rubric is wrong, not the AI.
- Decide what you will act on before you generate it.
Scoring your AI agent, not just your humans
The part that matters more each year. If an AI agent resolves 40% of your tickets, nobody is reviewing those conversations at all unless a QA tool does. You have automated a large share of your customer contact and removed it from oversight at the same time.
Zendesk QA, Observe.AI and MaestroQA all score AI conversations alongside human ones. Ask specifically about this — it is a newer capability than the vendors imply.
What it costs
| Tool | Price | Note |
|---|---|---|
| Zendesk QA | Quoted | Formerly Klaus. Published a seat rate until 2026; now an add-on with no standalone figure |
| EvaluAgent | From $35/user/mo | Rare transparency in this category, though the page calls its figures ballpark |
| MaestroQA | Not published | Deepest rubric configurability |
| Observe.AI | Not published | QA plus live agent assist |
Where it fails
- Dashboards nobody opens. QA that does not feed a weekly coaching conversation changes nothing.
- Gaming. Agents optimise for the rubric, so a bad rubric actively degrades service.
- Uncalibrated scores. Without calibration you are measuring reviewer disagreement, not agent quality.
Spend your effort on the scorecard, not the vendor choice. The difference between a good and bad rubric is larger than the difference between any two tools here.
Tools That Actually Do This
Purpose-built for scoring, and all three now grade AI agents alongside humans.
Zendesk QA
ZendeskFormerly Klaus. Auto-scores every conversation and now grades AI agents alongside humans.
MaestroQA
Custom scorecards and screen capture, for teams that want QA defined their own way.
EvaluAgent
One of the few QA vendors publishing per-seat pricing, plus per-conversation QA for AI agents.
Frequently Asked
Can AI grade support conversations?
Yes, across 100% of them rather than the 2% a manager samples. Whether that is useful depends entirely on how well your scorecard is designed.
How much does AI QA software cost?
EvaluAgent publishes indicative rates, from $35 per user per month and from $0.05 per AI conversation. Zendesk QA used to publish a seat rate and no longer does. MaestroQA, Kaizo and Observe.AI all quote on request.
What makes a good QA scorecard?
Few, specific, observable criteria. Five things you can point at in a transcript beat twenty subjective ones.
Can QA tools score AI agents too?
Zendesk QA, Observe.AI and MaestroQA do. It matters increasingly — if AI handles 40% of your tickets, nobody reviews those conversations unless a QA tool does.
What is calibration and why does it matter?
Having humans score the same conversations and comparing. Without it you are measuring reviewer disagreement rather than agent quality.
Is automated QA better than manual review?
On coverage, decisively. On judgement, no. Most teams use automated scoring for coverage and human review for the conversations it flags.
Which QA tool should I pick?
Zendesk QA if you run Zendesk and want published pricing, EvaluAgent if you do not, MaestroQA if your rubrics are genuinely complex.
Related Questions
What is customer service, and what does it actually cost?
YesThe function that answers customers after the sale. Simple to define, and the second-largest operating cost in a lot of businesses.
What are the different types of customer service?
YesEight delivery channels, each with a different cost per contact and a different answer to whether automation helps.
How does AI actually augment a support team?
YesFour levels of automation, from suggesting text to acting on your systems, each with a different cost and a different failure mode.