There is an implicit contract that Brazilian consumers have signed in recent years. Today, the 24-hour business support It has gone from being a luxury to becoming a basic market expectation. Most organizations, however, still haven't realized that they need to sign this contract as well.

Due to the expansion of artificial intelligence, 74% of consumers now expect customer service to be available 24/7. The idea of ​​waiting hours or until the next business day for a response is simply no longer acceptable to a large part of the public, whether B2C or B2B. 

This data changes the operational calculations of any company that depends on customer service to generate or maintain revenue. 

Why business hours have become a strategic problem 

Business hours as a service limit is a policy designed for the convenience of the operation, not the customer. It made sense when the entire purchasing and support chain was human and face-to-face. 

The environment has changed. The customer researches, decides, and wants to solve problems at their own pace—which often doesn't coincide with the hours when the team is available. 

In a B2B context, this has direct implications for the sales cycle. A prospect who sent an inquiry at 10 PM and receives a response the next day at 22 AM has already spent that time considering alternatives and possibly interacting with a competitor who responded more quickly. 

According to market data, responding to a lead within 5 minutes increases the chance of qualification by 21 times. After 30 minutes, this advantage practically disappears. 

What do Brazilian consumer data show about expectations of customer service?to 

Zendesk's CX Trends 2026 report presents a set of data detailing what Brazilian consumers expect today: 

• 87% prefer genuinely personalized experiences. 

• 82% get frustrated when they have to repeat information during customer service interactions. 

• 80% say that any customer service representative — human or AI — should have immediate access to the interaction history. 

Brazilian consumers aren't asking for perfection. They're asking for context and continuity. They want to be recognized, they want the problem to improve with each interaction—not to start from scratch. 

24/7 service isn't about putting people to work in shifts. 

This is the most common misconception when companies face the demand for increased availability: the first solution considered is to expand the team or create an on-call schedule. 

The problem is that this model scales costs at the same rate as it scales capacity — and it doesn't solve the quality problem, because the reduced-hours team is tired and less able to provide excellent service. 

The model that structured companies are adopting is different. It separates service types by complexity and distributes them intelligently: 

Artificial intelligence at the first level: Frequently asked questions, order status, scheduling, standard information, initial context gathering. These requests represent between 60% and 80% of the total service volume and do not require human judgment. 

Human specialized at the second level: Complex cases, sensitive situations, strategic negotiations, problem-solving that requires context and decision-making. This is where human agents deliver value that AI cannot replicate. 

Integration between the two: The history of the service provided by the AI ​​is available to the human agent when they take over. The customer doesn't need to repeat anything. The experience is seamless. 

What changes in the operation when this model is implemented? 

When AI and humans operate in an integrated way, the impact is not just on availability — it's on quality across the entire operation. 

Well-structured generative AI chatbots are capable of resolving up to 80% of requests without human intervention, with a typical 50% to 80% improvement in response time. This frees up human staff for tasks that truly require specialized attention. 

The agent who stops answering the same questions 40 times a day gains more energy and attention for the cases that matter. Team satisfaction increases. The quality of complex service improves. The NPS reflects this change. 

The trap of poorly structured AI. 

Implementing AI in customer service without careful data integration is like trading one problem for another. If the customer's history isn't centralized and accessible to the AI ​​agent, the experience will be equally frustrating—only automated. 

The key to making this work well is ensuring that all channels feed into the same repository of information: WhatsApp, email, phone, website chat, and social media need to converge on a single view of the customer. 

Without this integration, AI responds efficiently, but without context — and the customer keeps repeating themselves. 

The question that defines the next step. 

Does your company serve the customer at their pace, or at a pace that is more comfortable for the operation? 

If the answer is the second option, the cost of that choice is already showing up — in leads that didn't progress, in customers who left without complaining, and in opportunities that the competitor captured while your team was offline. 

Intelligent 24/7 customer service starts with an architectural decision, not a headcount decision.