# How are you handling AI-generated QA comments and auditor anonymity in ScorebuddyCX?

ScorebuddyCX has helped us keep support QA more consistent and accountable, with reliable performance and useful reporting for coaching opportunities and trend tracking. The main friction points are AI-generated comments that can be inaccurate or need manual editing, plus a desire for auditors to appear as anonymous or generic users to reduce perceived bias. Onboarding and clearer guidance around advanced settings and AI features would also help adoption. How are others improving AI comment quality and managing auditor visibility in your QA process?

##### Post Metadata
- Posted at: about 1 month ago
- Author title: Support Operations Analyst | Enhancing Efficiency & Customer Satisfaction through Data-Driven Insights.
- Net upvotes: 1



## Related Product
[ScorebuddyCX](https://www.g2.com/products/scorebuddycx/reviews)

## Related Category
[Contact Center Quality Assurance](https://www.g2.com/categories/contact-center-quality-assurance)

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