How are companies using AI to improve call center performance and quality?

I’ve been looking into how companies are using AI to improve call center performance, and I’m curious how this is actually working in practice.

Traditional call center QA often depends on managers manually reviewing a limited number of calls. That can make it difficult to get a consistent view of overall agent performance, especially when a team is handling thousands of conversations.

AI seems to be changing this by making it possible to analyze a much larger number of calls and identify patterns that might otherwise be missed.

Some of the areas I’m particularly interested in are:

• How accurately AI can evaluate calls against quality criteria
• Whether companies can realistically move beyond small call samples
• How AI identifies recurring issues in agent performance
• Whether QA data is actually being used for agent coaching
• How companies measure the ROI of AI-based quality monitoring

I’ve also been looking at TrackAgent, which focuses on AI-powered call quality assurance and agent performance analysis. What I find interesting is the idea of combining automated call evaluation with coaching insights rather than using AI simply as a reporting tool.

For those working in customer service, sales, or BPO operations, I’d be interested to hear your experience:

Are you already using AI for call quality assurance, or do you still rely mainly on manual QA?

And if you’ve implemented an AI-based system, has it actually improved agent performance or reduced the workload for your QA team?