Conversational AI vs. Traditional Rule-Based Chatbots

What is the difference between traditional rule-based chatbots and conversational AI chatbots?

There is a popular belief that chatbots are all equal; however, this is not the case. While some chatbots are simple programs, some are powered by conversational AI (artificial intelligence) – making them highly intelligent programs. Before we dive in on the differences, let us first introduce what chatbots are.

Chatbots

According to Wikipedia, a chatbot or chatterbot is a software application used to conduct an on-line chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human agent. Most chatbots on the internet operate through a chat or messaging interface through a website or inside of an application.

With this basic understanding of what a chatbot is, we can start to differentiate between traditional chatbots and more intelligent conversational AI chatbots.

Traditional Rule-Based Chatbots

Traditional chatbots follow simple pre-defined rules without a true understanding of intent and context. These are referred to as rule or flow-based bots. Although some may claim to have conversational abilities, these chatbots are typically text based and are trained to respond to certain keywords for every foreseeable scenario. As a result, if questions are off script, they may be ineffective at answering them. An easy way to understand flow-based bots is thinking of flow charts. Since each answer is pre-programmed, the chatbot will follow the path down the flow chart based on your response.

Conversational AI Chatbots

Conversational AI combines data, machine learning (ML), and natural language processing (NLP) to create technologies that understands intent, analyzes different languages and contexts, and imitates human conversation. This empowers technologies like chatbots or virtual agents to learn and become more intelligent over time, and quickly and efficiently communicate in a human-like manner via text and speech. There are two main components of Conversational AI:
  1. Machine Learning (ML): based on the idea that systems can continually learn and identify patterns through repeated use and automatically improve themselves with minimal human interaction.

  2. Natural Language Processing (NLP): technologies that enable computers to understand language in speech or text including intent and sentiment.

Conversational AI chatbots, conversational AI assistants or AI chatbots are built upon layers of complex systems that enable continuous self-improvement – becoming more intelligent and mature as they learn with conversation data and supervised machine learning. In addition, using natural language processing (NLP), AI chatbots emulate human conversations by analyzing and understanding sentiment and context in different languages. They can even understand if you misspell something.
conversational ai workflow

A Comparison: Conversational AI Chatbot ands Traditional Rule-Based Chatbots

For a comparison of the features between conversational AI chatbots and traditional rule-based chatbots, visit our Conversational AI page. Here is a simple example of how a conversational AI chatbot would behave and how a rule-based chatbot would behave:

rule-based chatbot and ai chatbot

Use Cases for Conversational AI and Traditional Rule-Based Chatbots?

If traditional chatbots are basic and rule-specific, why would you want to use it instead of AI chatbots? Conversational AI chatbots are very powerful and can useful; however, they can require significant resources to develop. In addition, they may require time and effort to configure, supervise the learning, as well as seed data for it to learn how to respond to questions.

Moreover, chatbots help augment human agents, and free up time for them to do more complex tasks. Traditional chatbots can be useful for limited scope topics, such as frequently asked questions (FAQs).

In addition, we are seeing a significant adoption of conversational AI chatbots in various industries to help augment humans and increase communication channels. Neurosoph, using its Specto AI platform, built two conversational AI chatbots for the Government of Massachusetts: COVID-19 chatbot and MyVax Records chatbot. Combined, these chatbots have over 1.7 million chatbot interactions, over 92% of interactions that meet the needs of the visitor, and over 90 topics (or intents) available to respond to visitors – thus, helping to alleviate the volume of calls to the state call center.

NeuroSoph builds conversational AI chatbots

NeuroSoph is an end-to-end AI software and services company that has over 30 years of combined experience in the public sector. We are highly skilled and knowledgeable experts in AI, data science, strategy, and software. Using NeuroSoph’s proprietary, secure and cutting-edge Specto AI platform, we empower organizations with enterprise-level conversational AI chatbot solutions, enabling more efficient and meaningful engagements.

For more information about our product and services, please contact us today – lets extend intelligence in your organization.

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