By Katia Dultra, Head of Customer Onboarding at 2clix
At the panel I took part in at CONAREC 2026, a conversation that started backstage ended up on stage: how has AI changed the way companies look at customer service quality?
My routine at 2clix is to listen, every day, to companies talking about the pain points of their quality teams. And one of those pain points comes up almost every time. In many companies, quality is still seen as a supporting area, not as a protagonist of the business.
I believe this is changing. And the change comes down to four points.
1. From sample to scale
Until recently, doing quality meant listening to 4 to 10 interactions per agent per month. One evaluation a week, focused on the individual.
The problem is everything that stays hidden behind such a small sample.
With AI, analysis gains scale. Instead of looking only at the person being evaluated, the company starts to see patterns, behaviors and recommendations that cut across the entire operation. And it can even decide which of these findings deserve attention first.
2. Customer service as a sensor of the future
Customer service is no longer just a record of what happened. It is a sensor of what is going to happen.
Imagine a beverage brand. Some customers start complaining to customer service about a bitter taste in the product. Each contact is handled in isolation, and no one notices that the volume is growing. Behind the complaints was a specific batch, from one region of the country, close to its expiration date. Had it kept circulating, the problem would have turned into an image crisis.
With visibility over every interaction, that pattern shows up sooner. The company gets ahead of the loss. And avoiding losses is revenue too.
Another example: a university with a Business Administration program starts hearing frequent questions about AI. Could the program be losing enrollments? Maybe it makes sense to adjust the curriculum or create a graduate program. The demand was already there, in customer service. Someone just needed to listen.
3. Service that makes sense for each audience
Structured data also helps design the experience. With Dasa, for example, the question was how to personalize service for each brand in the portfolio, each with its own audience and expectations.
In education, the challenge is similar. Someone coming in through Enem (Brazil’s national high school exam) has different questions from someone starting from scratch with the university entrance exam. Treating everyone the same way wastes the conversation.
In practice, understanding behaviors at scale is what makes it possible to build service that makes sense for each profile. AI doesn’t replace that perspective. It gives it volume and speed.
4. From insight to revenue
The shift we have been trying to bring to the market is this: turning CX and quality into areas that generate revenue. And reaching the board with something concrete. An insight that was prioritized, became action and moved a number.
NPS and CSAT remain essential. They are top-of-the-pyramid indicators. But the area can go further and position itself as a source of change, not only in technology, but in process, in behavior and in ways of thinking.
If I had to sum it all up in one word, it would be connection. Every interaction is a connection. Even when it isn’t human, there is a human behind it handling it. That connection is where knowledge comes from. And it is through it that revenue comes.
My take is that generating ideas, insights and recommendations will no longer be the problem. The challenge now is to prioritize, choose what to do first and have the discipline to execute, until all of it turns into results.
CX can no longer be left on the periphery of the business. It is the center.
To watch the panel video on LinkedIn, click here!
2clix helps companies manage quality and business with AI, turning what happens in customer service into data and decisions. In 2026, it won the Prêmio CONAREC in the Sistema de Monitoria de Qualidade category.
