The Pitch Avatar team helps you identify the tasks for which each solution is most effective.
While conversational AI continues to grow in popularity, rule-based chatbots (also known as decision tree chatbots) remain widely used. However, AI enthusiasts often view such chatbots as undeniably outdated, perceiving their use as a mark of rigid conservatism that has no place in the IT world. Let’s explore whether this perception holds true.
To begin with, it’s important to recall how each solution functions:
A rule-based chatbot, as the name suggests, strictly adheres to the rules it is programmed with. All its response options are predefined. A typical use case involves asking the user to select a question from a set of given options, which the chatbot then answers. Upon receiving a user query, the chatbot scans its database and, based on the rules, selects the only possible response. It lacks self-learning capabilities and requires manual updates for new configurations and responses. Crucially, it can only respond to text-based queries.
Conversational AI provides a versatile solution capable of searching for and generating answers to virtually any user query, while supporting active, free-form intelligent dialog when needed. It can be customized to perform a wide range of tasks—for example, serving as a personal secretary-assistant, an online consultant or salesperson, or even an online presentation host. However, like most base neural networks, LLM-based dialog AI is prone to errors and hallucinations. This is the primary reason why customizing agents based on conversational AI tends to be more complex, expensive, and often requires expert intervention.
As you can see, rule-based chatbots still hold a niche in the current landscape. Of course, sooner or later, they will disappear as a standalone type of IT product, fully replaced by universal AI-based solutions that become more advanced, user-friendly, and cost-effective. For now, though, wherever a simple reference tool or navigator is needed to provide clear, structured answers, rule-based chatbots remain a technically and economically viable option. However—and this cannot be ignored—the problem of “obsolescence” persists. Many AI enthusiasts dismiss rule-based chatbots simply because they are considered “old,” not because they fail to perform their intended tasks.
To summarize, there’s nothing stopping us from developing hybrid solutions. For instance, our Pitch Avatar presenter’s assistant combines an AI foundation with elements of a decision tree, allowing presentation authors and their audiences to save valuable time. In our view, these kinds of hybrids represent the near future.
Wishing you all the best – success, and high revenues!
