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5 AI tools for quality assurance to upgrade your workflows

AI tools for quality assurance

Artificial intelligence has many roles for customer support teams.

When it comes to quality assurance though, AI serves as a powerful way of automating and augmenting QA processes, ensuring consistent and high-quality customer interactions.

But let’s be clear: Not every QA tool out there has mastered providing AI where you most need it.

Unfortunately, a tool that will just automatically transcribe calls won’t cut it. Most customer support teams will need a solution to help speed up ticket analysis, automatically rating all of your tickets and offering feedback to agents.

So where exactly do AI tools come in?

Why do you need AI for quality assurance?

Let’s start with one of the most pressing QA challenges: Reviewing every single ticket.

With the high volume of customer tickets received daily, manually reviewing all tickets is impractical and resource-intensive. AI enables you to assess 100% of tickets efficiently and accurately, ensuring that no customer query goes unreviewed and maintaining a high level of quality assurance across the board.

And you don’t have to skimp on quality. You can train your AI algorithm to ensure that quality standards are consistently met across all customer interactions. By employing predefined criteria and algorithms, AI will then evaluate tickets against these standards objectively, reducing subjectivity and ensuring adherence to established quality benchmarks.

Go one step further and bridge the gap between QA and performance. AI tools can provide automated feedback to agents based on their performance evaluations. By analyzing interactions in real-time, AI identifies areas of strength and areas needing improvement, delivering timely feedback to agents to help them enhance their skills and performance. 

Simply put, AI tools are faster when it comes to improving future QA processes as they can instantly look at the insights into agent performance across multiple dimensions, including response times, resolution rates, customer satisfaction scores, and adherence to quality standards. This 360-degree view enables managers to identify trends, patterns, and areas for development, empowering them to make informed decisions to optimize team performance and deliver exceptional customer service.

But every tool does all of this. So next we’re taking a look at some of the best AI tools for quality assurance customer support teams should consider.


best ai tool for quality assurance - kaizo

Using Kaizo’s state-of-the-art Samurai AI capabilities alongside Auto QA, you can optimize automated quality assurance processes by swiftly rating all your tickets and identifying the root cause of negative feedback. 

The system also analyzes sentiment and empathy cues to automatically flag tickets needing special attention, with customizable filters tailored to your criteria. Kaizo also provides rapid access to summarized data from calls, transcriptions, and dialogues through GPT Summaries.

Additionally, you can go beyond QA as Kaizo offers features to boost team engagement and motivation, including AI-generated Missions and customizable goals powered by Kaizo’s innovative gamified technology.

Notable features:

  • Automated Quality Assurance
  • AI-driven Agent Empathy Score
  • Customer Sentiment Analysis
  • AI conversation summary
  • Phone call transcriptions
  • Performance coaching
  • Gamified workforce engagement

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ai tool for quality assurance - maestroqa

MaestroQA harnesses artificial intelligence for sentiment analysis, tone classification, and translation. This allows agents to better understand customer intentions and craft helpful responses to their inquiries. Moreover, it offers comprehensive insights to enable customer support teams to proactively tackle potential concerns.

Notable features:

  • Scorecard builder
  • QA reporting
  • Auto QA
  • Workflow automation
  • Root cause analysis
  • Calibration workflows


ai tool for quality assurance - balto

Balto has recently launched its QA Copilot that allows users to autonomously evaluate calls based on natural language criteria, without pre-set templates or constraints. BaltoGPT also leverages generative AI to instantly analyze calls and provide insights about your call center and provide agents with real-time guidance. 

Notable features:

  • Generative AI
  • QA Copilot
  • Customizable scorecards
  • QA dashboard and reporting


ai tool for quality assurance - scorebuddy

Scorebuddy’s AI capabilities were initially limited to its reporting module. Its smart analytics reviews feature allows you to review more conversations and automate sentiment analysis and topic detection. Right now, you can also use AI scorecards and leverage GPT to automatically score specific questions, eliminating hours of manual effort.

Notable features:

  • Flexible AI scorecards
  • Smart analytics and QA reporting
  • Root cause analysis
  • Calibration module
  • Business intelligence
  • Auto QA (i.e. sentiment analysis, automated scoring, topic discovery)


ai tool for quality assurance - evaluagent

EvaluAgent is one of the latest tools to start introducing AI into their stack. With this platform, you can leverage AI and automation to identify crucial interactions for monitoring, preventing human oversight and maintaining HR rigor. AI is also part of their conversational intelligence module as you can use it to automatically analyze issues against logic and AI Insight Topics. As a last step, its AI-driven insights can automate the delivery of relevant improvement actions.

Notable features:

  • Auto QA (just for assessing and flagging high-risk conversations)
  • QA reporting
  • Calibration
  • Scorecards

Other key factors to take into account

For starters, assess the depth and complexity of the AI capabilities offered by the tool you want to pick. Look for features such as natural language processing, sentiment analysis, machine learning algorithms, and predictive analytics to ensure the tool can effectively analyze and interpret a wide range of customer interactions.

You’ll also want to go beyond QA use cases. The right tool will scale with your team so keep an eye on features that support performance management, such as goal setting, feedback sharing, and coaching tools, to empower agents and enhance their engagement and development.

Not sure where to start?

Think of what AI capability is most likely to speed up QA efforts for you. Relying on artificial intelligence to score tickets faster, analyze sentiment and empathy, as well as get GPT summaries of calls and conversations should be a top priority.

Kaizo lets you leverage all of these and automation to make sure you’re rating 100% of your tickets accurately. Get a free demo to see how it can impact your own team’s performance!

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