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Immediacy and personalization make the difference in customer experience. Contact centers have become the heart of the relationship between businesses and people. However, the technological revolution we are living through, driven by artificial intelligence, has brought with it a new challenge: the overabundance of solutions, terms, and promises that often create confusion. Every day, customer experience leaders face the difficult task of distinguishing between software that promises to automate, converse, or even think like a human.
Amid that confusion, one question arises: how can you tell which solution your company truly needs in order to offer an excellent customer experience? In this article, we delve into these new concepts and clarify the differences between the types of AI agents, bots, and other technologies. Discover how each one can help you.
What is the difference between an AI agent and a chatbot or voicebot?
Before exploring the different levels of automation, it is essential to understand the difference between a chatbot and an AI agent.
- A chatbot or voicebot is an automated system that interacts with users by following predefined rules or flows. The chatbot uses written text, while the voicebot communicates using voice conversation. Its goal is to solve simple and repetitive tasks, such as answering predefined frequently asked questions or guiding users through basic processes. This type of bot is simple, predictable, and works well for meeting specific needs.
- In contrast, an AI agent is a much more advanced solution: it uses generative AI and autonomous reasoning capabilities to understand, decide, and act based on context, even solving complex queries without human intervention. While the bot follows a script, the AI agent acts like another member of the team, capable of learning, adapting, and making decisions on its own. For example, while a chatbot may answer the most common questions, an AI agent is equipped to offer personalized customer service with recommendations and even sentiment analysis.
What levels of automation coexist in a contact center?
Choosing between different levels of automation is not a matter of all or nothing, but rather a matter of strategy. A contact center can benefit from a combination of traditional bots, conversational bots, and AI agents. You just need to define the role of each one.
1. Traditional bot: ITR and IVR
At the first step of automation, we find the veterans: traditional bots, such as ITR (Interactive Text Response) and IVR (Interactive Voice Response) systems that have been the foundation of contact center automation for years.
How do they work? With fixed rules and predefined menus, like a catalog of voice or text options. An ITR operates by selecting preconfigured commands following a sequential logic. They simulate conversation, but do not interpret the user’s responses: they provide alternatives and open new ones based on the selected option. They operate similarly to an IVR over the phone, but in a chat environment.
These bots identify keywords through automatic speech recognition (ASR), convert text to speech (TTS) and vice versa, but they do not understand subtleties or improvise. They excel at the simple: transferring calls, providing balances, scheduling appointments, repetitive tasks that do not require a high level of understanding.
Their main advantage is efficiency in basic processes and their ease of implementation. However, the user experience is usually rigid, as the options are closed and cannot adapt to variations in natural language. If your goal is to automate simple tasks and reduce operational costs, traditional bots remain a valid option. Platforms like Inconnect include IVR natively.
2. Conversational bot powered by GenAI
The next level consists of conversational bots powered by generative AI (GenAI). These bots represent a significant evolution compared to traditional ones, as they incorporate advanced natural language understanding (NLU) and machine learning capabilities.
Thanks to AI and configurable conversational flows (no code), these bots can engage in much more natural conversations that are adapted to the user’s context. Their technical characteristics determine what they are capable of doing:
- Proprietary AI intent detection engine: they understand the user’s query in any language or regional variation, adapting the response to the context.
- Omnichannel support: they automate service across multiple channels such as calls, social media, webchats, or WhatsApp.
- Dialogue Router: they are designed with dialogue flows visually and without programming.
- Knowledge Base Fusion: they generate responses based on advanced knowledge bases.
- Ask for help: if the bot does not know the answer, it can request assistance, learn in real time, or seamlessly transfer the query to a human agent.
These bots are ideal for resolving frequent queries, guiding self-service processes, and improving the customer experience, as they offer a more fluid and personalized interaction. Insmartbot, from Inconcert, the previous generation of chatbots and voicebots before Inagent, is an example of this technology.
3. AI Agents: the new generation of conversational intelligence
The most advanced level is represented by AI agents. Unlike conversational bots, AI agents are 100% trained with generative AI and are capable of reasoning, querying data, and making decisions autonomously, without relying on predefined flows.
Among the main characteristics that define AI agents, their proprietary AI engine, specifically trained in CX operations, stands out. This engine allows them to interpret the context of the interaction and make decisions autonomously, connecting with databases and leading AI models such as OpenAI, Anthropic, Meta, and Google.
Additionally, AI agents offer empathetic and personalized communication, providing responses tailored to each customer, in any language and across any channel. This capacity is complemented by their ability to autonomously access systems such as CRM, ERP, or knowledge bases, which allows them to offer precise and complete answers.
Advanced quality management is another key feature, helping supervisors monitor performance in real time and improve the quality of interactions. Finally, AI agents stand out for their ability to generate insights, analyzing performance, sentiment, and conversation trends to continuously optimize the customer experience.
All this potential is not just a technological promise, but a reality supported by the latest industry studies. In fact, according to the recent Boston Consulting Group (BCG) report AI Agents, and the Model Context Protocol (April 2025), AI agents are revolutionizing automation in the contact center and are already delivering improvements of 30 to 90 percent in speed and productivity.
When should you use bots or AI agents to enhance your customer experience?
Depending on the CX operation you need to automate, you can implement one or another solution:
Inagent: the most advanced solution from Inconcert with Agentic AI
Contact center automation has come a long way, from traditional bots to different types of AI agents, each with its own strengths. At Inconcert, we understand that there is no one-size-fits-all solution. That is why we offer a wide range of options, from classic bots to advanced AI agents like Inagent, designed to take CX to a new level of autonomy, personalization, and efficiency.
If you are looking to transform your customer experience, we invite you to explore how Inagent and our bot solutions can be adapted to the specific needs of your business. Request a demo.
