# Which contact center quality assurance platforms use AI scoring without replacing human calibration entirely?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I've been researching which contact center quality assurance platforms use AI scoring without replacing human calibration entirely for a QA team worried that going all-in on automated scoring means losing the calibration process that keeps scoring consistent across reviewers. The better platforms treat AI as the first pass, not the final word. Here's what stood out in the <a class="a a--md" elv="true" href="https://www.g2.com/categories/contact-center-quality-assurance">Contact Center Quality Assurance category on G2</a>.</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/nice-cxone/reviews"><strong>NICE CXone</strong></a>. AI scoring flags calls for review, but human calibration sessions remain part of the standard workflow rather than being phased out. Best for teams wanting AI triage with human calibration retained.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/playvox-quality-management/reviews"><strong>Playvox Quality Management</strong></a>. Scorecards support both automated and manual scoring on the same call, so calibration between AI and human reviewers stays visible. Best for teams wanting side-by-side AI and human scoring.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/genesys-cloud-cx/reviews"><strong>Genesys Cloud CX</strong></a>. AI-assisted scoring integrated into the broader platform, with human review workflows still configurable per team. Best for teams already on Genesys wanting QA in the same platform.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/calabrio-one/reviews"><strong>Calabrio ONE</strong></a>. Workforce engagement suite where QA scoring sits alongside analytics, keeping human review as an explicit step rather than an afterthought. Best for teams wanting QA tied to broader workforce engagement data.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/five9-intelligent-cloud-contact-center-platform/reviews"><strong>Five9 Intelligent Cloud Contact Center Platform</strong></a>. AI scoring built into the platform's QA module, with calibration workflows for supervisors to weigh in on flagged calls. Best for supervisors wanting a direct role in the AI scoring loop.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">The thing worth checking before rolling this out broadly: whether reviewers actually trust the AI scores enough to calibrate against them, or whether they quietly re-score everything anyway. That trust gap is usually the real adoption blocker, not the technology.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For QA teams running AI-assisted scoring, has calibration between AI and human scores actually held steady over time, or does the AI drift and need frequent retraining?</p>

##### Post Metadata
- Posted at: 14 days ago
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;Ours has stayed steady so far with Playvox, though we&#39;re still fairly early in. Genuinely curious if anyone running this longer term has seen the AI side start drifting once call patterns or scripts change and needed retraining.&lt;/p&gt;

##### Comment Metadata
- Posted at: 13 days ago
- Author title: Marketing Executive





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