We all know traditional QA hasn’t changed a great deal over the years. 

Most contact centres still only manually sample a small percentage of calls.  

They listen for obvious quality issues and hope the few interactions they score represent the overall customer experience.A nd it usually transpires that they rarely do. 

When you only review 2–5% of your total interactions, you end up making assumptions about the other 95%. That means your best agents can go unnoticed for the great work that they do, recurring issues can easily slip through the net, and valuable insights end up getting buried in hours of unreviewed conversations. 

Which is a huge problem, because in customer service, it’s what you don’t know that can hurt you the most. 

The problem with traditional QA 

In fairness, the idea behind QA is simple…  

You listen, evaluate, and improve based on your findings.  

When you do this at scale, you start to run into problems as manual QA can be time-consuming. Not only that, it’s also completely subjective to the person marking, which leads to inconsistencies.  

Even in productive teams, human agents can only review so much. A 15-minute call can take 3x that long to listen to and mark, and on top of that, they’ll naturally interpret tone, sentiment, or context differently. 

Therefore, your performance data tends not to be as accurate as you think. Your response to your QA becomes reactive instead of proactive, and it’s also too slow to keep up with how quickly contact centres move.  

By the time you’ve picked up on a trend in the data, it’s already potentially affected hundreds of your customers and their experience with your brand.  

How AI changes everything 

Since AI came along, it has completely transformed the possibilities of QA. 
 
Thanks to automatic QA, you can now analyse every single interaction and not just a handful of random samples. And you can reliably do this at scale, across all of your channels, from voice, to email, to chat, social media and even WhatsApp.  

Suddenly, you’re working with all of your data instead of relying on a small data set and hoping for the best.  
 
AI can go further, it can help you to identify keywords quickly, your customers’ sentiment, can flag anomalies and keywords for compliance.  

AI helps you to spot the patterns you could easily miss before they become problems. And It gives your supervisors the superpowers they need without all the manual graft.  
 

The result? 

✅ Instant visibility into both performance and quality trends 

✅ Objective scoring with human bias. 

✅ Quicker coaching loops with targeted feedback. 

✅ Consistent standards and expectations across every agent and every channel. 

From reactive to proactive coaching 

One of the main issues with traditional QA is that the feedback can often come days or, in some cases, weeks after the customer interaction. And when you’re evaluating historically, the moment has passed, and the damage is done.  
 
AI changes that, because it analyses interactions straight away and that’s another key reason for why it changes the game. If you’re the manager of a sales team, you don’t want to wait till the following day or even days to understand what’s going wrong; you want to identify the reason why and act on it. And if you’re the manager of a customer service team, you’d want to be able to spot issues before they get out of control and cost your business money.  

QA gives you the ability to coach in the moment and not in the days afterwards.  

Ultimately, it’s the difference between reacting to mistakes and preventing them. 

Every interaction, fully evaluated 

One of the biggest values of automatic AI-driven QA is what you do with the data.  

Because when you analyse every call, message and chat, you can finally:  

• Understand what makes a high performer and use their approach for training.  

• Identify your customers’ pain points in real time and fix them.  

• Track compliance whilst reducing the risk of further errors.  

• Automate your QA so that your team can focus on the good stuff, coaching and improvement.  

Say no to guesswork and no to more bias.  
 
And what you get in return is a clear and consistent overview of performance across every department in your contact centre.  

At QContact, we call that peace of mind… every interaction, fully evaluated, which allows you to focus on making more meaningful improvements.   

AI isn’t replacing your QA team, it’s here to empower them 

There’s a lot of noise when it comes to AI and automation in contact centres; it brings a collective fear that good people will be replaced by machines, but in reality, the opposite is true, AI amplifies it.  
 
Take away all the repetitive, mind-numbing, time-consuming tasks and you free up time for your QA agents to get stuck into the good stuff. They can analyse trends, coach with more conviction and drive performance in the right direction.  
 
You don’t lose the human touch; you end up letting the humans do the stuff they are naturally better at. 

The future of QA is here 

Right now, customer expectations have never been higher, and with that, so has the pressure on contact centres to deliver consistently great customer service at scale! 

If your contact centre still relies on random checks, you won’t be getting the bigger picture.  
 
Automatic AI-powered QA gives you that visibility; it’s a bird’s-eye view of your entire business, and it’s also faster and fairer.  

Every call, chat and interaction, FULLY evaluated for complete piece of mind.  

Ready to see it in action? 

 
With QContact’s Automatic QA, you get to analyse every interaction across voice, chat, and messaging.  

So you can instantly identify trends, coach missed opportunities, and fix any compliance issues. 

If you’re ready to move from random checks to real insight? 

Book a demo today.