You’ve probably talked to a chatbot on a bank or airline website at some point. You asked a simple question and got a canned response: “For flight inquiries, press 1.” Useful in basic terms, but very limited, and you needed something more complex. At times like that, you want to talk to a customer service agent: you want a human to help you!

Now imagine an assistant who not only answers, but also understands the context, remembers what you said before and can even act on your behalf. You ask it: “Book a doctor’s appointment on Tuesday after 5 o’clock” and it doesn’t just show you a link, but enters the system, searches for available options and confirms the appointment. This is no longer a chatbot: it is a conversational agent.

These agents represent a huge leap forward from traditional question-and-answer systems. They no longer just return text, but combine language comprehension with the ability to make decisions and execute actions in the real world.

Its logic is based on three pillars:

• Natural language: they understand what we say with our words, without us having to use rigid commands.
• Memory and context: they remember previous interactions to give continuity to the conversation.
• Action: they can use external tools (calendars, databases, reservation systems) to solve specific tasks.

This gives rise to what are known as tool-using agents, i.e. agents that don’t just talk the talk, but act as intelligent intermediaries between us and a wide network of services.

Examples that are already among us:

• Assistants who schedule meetings in your calendar, automatically coordinating schedules and agendas.
• Systems that help write code and simultaneously run tests to verify that it works.
• Platforms that compose music, generate images, or prepare financial reports based on real data.

Unlike first-generation chatbots, today’s conversational agents can adapt to each user’s style, interpret ambiguities and combine multiple steps to accomplish a task. Instead of simply answering questions, they become digital collaborators.

At SMS Sudamérica, we see this change as a strategic opportunity. We not only work on creating agents that answer clearly, but also on designing systems capable of integrating with the tools already used by companies and governments. Thus, we achieve assistants that do not remain in theory, but execute real actions: from registering an incident to generating management reports or interacting with human resources systems.

The challenge, of course, is not only technical. When an agent converses and acts on our behalf, we need to ensure transparency, security, and traceability. The user needs to know what decisions the system made and why.

In short, conversational agents are much more than chatbots. They are the natural evolution towards a world where talking to a machine does not feel like a cold transaction, but like interacting with a real assistant. In that near future, conversational agents will be strategic allies in digital transformation, and at SMS Sudamérica we are already building them to turn a simple query into an action of real value.

Note by: María Dovale Pérez