Chatbot vs Conversational AI: What's the Difference?

Global spending on conversational commerce is expected to reach 290 billion in 2025, according to Juniper Research. That’s a staggering seven-fold increase from the year 2021. It is high time that you should know about conversational AI technology to improve your customer experience (CX)—or risk falling behind in this growing trend.

In this article, I’ll explain what chatbots and conversational AI are, their differences, and which one you should use in your business.

I’ll also explain how you can eliminate the incorrect, fabricated, and hallucinated responses of chatbots that affect the customer experience.

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Chatbot vs Conversational AI: The Difference

Many people use the terms chatbot and conversational AI interchangeably. But, it is not the case.

Chatbots are computer-programmed interfaces that mimic human conversations to assist users in real-time. These chatbots can be either powered with simple pre-built conditional flows or artificial intelligence (AI).

Conversational AI is a technological advancement of artificial intelligence. It is the conversational AI that gives contextual understanding to the chatbots.

The difference between chatbots and conversational AI is that conversational AI is an advancement in artificial intelligence that can be used to power chatbots to elevate the customer experience (CX).

Almost everything in the digital world is a wrapper of something. I.e., Applications > Frameworks > Infrastructure > Hardware.

Every application is built using a kind of framework and based on some infrastructure and hardware–exactly like layers wrap around each other.

Likewise, chatbots are the wrappers of conversational AI.

Conversational AI is the technology that took chatbots to the next level and gave birth to advanced conversational chatbots like GoZen DeepAgent.

Instead of comparing chatbot technology with chatbots, it’s more logical to compare traditional chatbots with conversational AI chatbots.

What is Conversational AI?

Conversational AI is a type of artificial intelligence (AI) that uses NLP, foundation gen-AI models, and machine learning (ML) to decipher the user input and simulate human conversation.

The conversational AI is the novel advancement that powers the new-age chatbots and voice assistants.

Key components of conversational AI:

1. Natural language processing (NLP):

2. Machine learning (ML):

3. Dialogue management:

4. Speech recognition and synthesis:

Applications of conversational AI

AI chatbots, virtual assistants, interactive voice response (IVR), and real-time language translation services.

What is a Chatbot?

A chatbot is a text or voice-based digital software program that can be used in multiple industries to automate customer support, sales, and marketing.

Chatbots simulate conversations with their users. These programs are designed to interpret human input, whether it be text or voice, and respond in a way that mimics human interaction.

So, does this mean chatbots are conversational AI?

Well, that depends on which type of chatbot you are referring to.

There are three types of chatbots:

Rule-based chatbots

Rule-based chatbots typically operate on a set of predefined rules. They can be classified as basic chatbots.

Rule-based chatbots use decision trees and sometimes regular expressions (regex) to match the user input (i.e., pattern matching) and produce human-like responses.

The decision tree is nothing more than if-then-else decision rules.

A rule-based chatbot interprets user input using the pattern-matching technique and compares it with the pre-defined set of conditions to deliver the possible output.

If asked anything outside of its pre-defined rules, the rule-based chatbots typically throw a fallback error message.

Examples of rule-based chatbots include ELIZA, PARRY, Jabberwacky, and even older versions of Intercom.

AI chatbots

AI chatbots use natural language understanding (NLU), a subset of natural language processing (NLP), to interpret user queries and mimic human-like responses.

Since AI chatbots leverage large language models (LLMs), they have the ability of contextual understanding, which enables them to grasp the nuances of human conversation by recognizing the context in which a dialogue occurs.

This capability allows them to interpret user intent more accurately, maintain the flow of conversation, and provide relevant responses based on prior interactions.

Contextual understanding is the ability that separates rule-based chatbots from AI chatbots.

Hence, AI chatbots are highly sophisticated and more accurate than rule-based chatbots. Examples of AI chatbots include GoZen DeepAgent, Drift, Tidio, and Intercom.

Hybrid chatbots

As the name suggests, hybrid chatbots use a combination of a pre-defined set of rules and artificial intelligence (AI) features, like NLU, to understand and process human queries. Hybrid chatbots can deliver contextual responses as well as they can simply deliver responses in accordance with the pre-defined set of rules.

GoZen DeepAgent, Drift, and Intercom are a few examples of hybrid chatbots.

Now you understand that AI chatbots and hybrid chatbots can be a type of conversational AI. However, it is notable that not all chatbots are conversational AI.

The importance of conversational AI technology in businesses

Conversational AI adoption is nothing but the process of integrating and utilizing conversational AI technologies within various applications and systems to enhance user interactions, streamline operations, and improve overall efficiency.

This adoption involves implementing tools like chatbots, virtual assistants, and voice-activated systems to facilitate more natural, human-like communication between machines and users.

Here’s the benefits of implementing conversational AI via chatbots on your website:

Since they categorize users by buying intent, their AI-based product recommendations are remarkably accurate. Businesses that use AI chatbots have reported 30-50% more inbound leads captured than traditional web forms.

What’s a RAG-powered chatbot?

Retrieval augmented generation (RAG) is an AI framework that combines retrieval-based and generative AI techniques to improve the accuracy and relevance of AI-generated responses.

RAG-powered chatbots are key to delivering highly accurate, context-aware, and up-to-date responses by retrieving real-time information from external knowledge bases before generating answers.

Chatbots that are solely powered by generative AI models, such as ChatGPT, Gemini, and Claude, are prone to make fabricated and hallucinated responses.

If you choose those kinds of AI chatbots for your business, you will risk the customer experience (CX), as the poor response to user queries leads to poor customer satisfaction score (CSAT).

RAG-powered AI chatbots like DeepAgent increase the intent coverage of a chatbot. Hence, the RAG-powered chatbot can handle a broader range of user queries with greater accuracy and relevance by dynamically retrieving and integrating external knowledge into its responses.

RAG-powered chatbot (as well as agent) to automate customer support, marketing, and inbound sales

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How to create a conversational chatbot for FREE?

AI chatbots are a game-changer for businesses looking to automate interactions, qualify leads, and enhance customer experience. There’s no doubt about this.

However, many business owners and decision-makers think that implementing an AI chatbot is costly and complex, requiring significant technical expertise and high upfront investment. That is not true if you find the right vendor.

Implementing a conversational AI chatbot on your website is completely free. Here’s how you can implement it:

FAQs

1. What’s the difference between DeepAgent and other AI chatbots?

The difference between DeepAgent and other AI chatbots is that AI native automation. DeepAgent is not just a chatbot with typical automation workflows, rather, it comes with AI native automation.

Unlike rule-based automation workflows, AI native automation is suitable for unstructured processes where rules can’t be predefined.

An example of AI-native workflow automation is:

2. Can I use ChatGPT as a chatbot for my business?

No, you can’t use ChatGPT as a chatbot on your website. Here are a few reasons why you can’t:

3. Chatbot vs Live Chat: What’s the Difference?

Live chat is software that allows real human agents to assist customer support, whereas a chatbot is software that is powered by conversational intelligence, a type of artificial intelligence (AI).

Chatbots may include live chat features, but live chat interfaces don’t always have conversational intelligence.