Chatbots vs Conversational AI: A Complete Guide

Chatbots vs Conversational AI: What's the difference? This guide explains what each means and how they differ.
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Chatbots vs. Conversational AI: What's the difference?

Chatbots have become commonplace in the business world. You can find them on almost every website these days, which can be backed by the fact that 80% of customers have interacted with a chatbot previously.

They're popular due to their ability to provide 24x7 customer service and ensure that customers can access support whenever they need it. As chatbots offer conversational experiences, they're often confused with the terms "Conversational AI," and "Conversational AI chatbots."

While they may seem to solve the same problem, i.e., creating a conversational experience without the presence of a human agent, there are several distinct differences between them.

In this article, we'll explain the features of each technology, how they work and how they can be used together to give your business a competitive edge over other companies.

Conversational AI is a Technology

Simply put, chatbots are computer programs that mimic human conversations, whereas conversational AI is the technology that powers it and makes it more "human." The key difference is in the level of complexity involved. Chatbots use basic rules and pre-existing scripts to respond to questions and commands. At the same time, conversational AI relies on more advanced natural language processing methods to interpret user requests more accurately.

With the chatbot market expected to grow to up to $9.4 billion by 2024, it’s clear that businesses are investing heavily in this technology—and that won’t change in the near future.

However, with the many different conversational technologies available in the market, they must understand how each of them works and their impact in reality.

What is a Chatbot?

A chatbot is a computer program that emulates human conversations with users through artificial intelligence (AI).

The most common type of chatbot is one that answers questions and performs simple tasks by understanding the conversation's words, phrases, and context. These basic chatbots are often limited to specific tasks such as booking flights, ordering food, or shopping online.

There are two types of chatbots: rule-based chatbots and AI-based chatbots.

  • Rule-based chatbots: Rely on predetermined answers to questions and don't learn from their conversations with humans. They can reply with canned responses triggered by specific keywords or phrases. Rule-based chatbots don't know how to respond to new questions or if the user says something different than expected.
  • AI-based chatbots: Use AI to learn from interactions with humans so they can better understand the needs of their users over time and respond intelligently based on those needs. AI chatbots can learn from past conversations and adapt based on what they learned during previous interactions with humans.
An image depicting the differences between rule-based chatbots and AI-based chatbots

What is Conversational AI?

Conversational AI allows your chatbot to understand human language and respond accordingly. In other words, conversational AI enables the chatbot to talk back to you naturally.

It uses speech recognition and machine learning to understand what people are saying, how they're feeling, what the conversation’s context is and how they can respond appropriately. Also, it supports many communication channels (including voice, text, and video) and is context-aware—allowing it to understand complex requests involving multiple inputs/outputs.

The critical difference between chatbots and conversational AI is that the former is a computer program, whereas the latter is a type of technology. A few examples of conversational AI chatbots include Siri, Cortana, Alexa, etc. Depending on the sophistication level, a chatbot can leverage or not leverage conversational AI technology. 

If your chatbot is trained using Natural Language Processing (NLP), is context-aware, and can understand multiple intents, it’s a conversational AI chatbot. Chatbots are often leveraged by businesses to help meet certain marketing, sales, or support goals and their success is tracked by metrics such as goal completion rate

There are three kinds of conversational AI applications, and they are:

  • Chatbots: Chatbots use conversational AI to simulate a conversation flow with a human. Not all chatbots use conversational AI—but the ones that do, tend to provide a more natural and relevant output as it's trained using natural language processing (NLP) models.
  • Voice assistants: They're software programs that carry out tasks based on voice commands. It uses voice recognition, voice synthesis, and language processing algorithms to understand the command and provide the necessary outputs. A few examples include Amazon's Alexa, Apple's Siri, Microsoft's Cortana, etc.
  • Virtual assistants: They're powered by AI and are context-aware chatbots that help you perform specific tasks. They're powered by NLP and natural language understanding (NLU) models—making their output more personalized, accurate, and engaging.

Chatbot vs. Conversational AI: Examples

Examples of rule-based chatbots

  1. SendinBlue

SendinBlue’s Conversations is a flow-based bot that uses the if/then logic to converse with the end user. You can set it up to answer specific logical questions based on the input given by the user. While it's easy to set up, it can't understand true user intent and might fail for more complex issues.

An image showing how SendinBlue Conversations bot works
SendinBlue Conversations app Source
  1. Sprinklr

In this example by Sprinklr, you can see the exact conversational flow of a rule-based chatbot. Each response has multiple options (positive and negative)—and clicking any of them, in turn, returns an automatic response. This is more intuitive as it can recognize serial numbers stored within their system—requiring it to be connected to their internal inventory system.

An image of the conversation flow found on Acme chat support's bot
Sprinklr chat support Source

Examples of conversational AI

  1. IBM Watson

This conversational AI chatbot (Watson Assistant) acts as a virtual agent, helping customers solve issues immediately. It uses AI to learn from conversations with customers regularly, improving the containment rate over time. The chatbot is enterprise-ready, too, offering enhanced security, scalability, and flexibility.

The image shows a conversation flow found on a banking chatbot powered using IBM Watson
IBM Watson in Banking Source
  1. Babylon Health

Babylon Health's symptom checker uses conversational AI to understand the user's symptoms and offer related solutions. It can identify potential risk factors and correlates that information with medical issues commonly observed in primary care. Based on that, it provides an explanation and additional support if needed.

An image showing how Babylon Health's symptom checker chatbot works
Babylon Health's Symptom Checker Source

Conversational AI is the future

Chatbots and conversational AI are two very similar concepts, but they aren't the same and aren't interchangeable. Chatbots are tools for automated, text-based communication and customer service; conversational AI is technology that creates a genuine human-like customer interaction.

For this reason, many companies are moving towards a conversational AI approach as it offers the benefit of creating an interactive, human-like customer experience. A recent PwC study found that due to COVID-19, 52% of companies increased their adoption of automation and conversational interfaces—indicating that the demand for such technologies is rising.

Additionally, these new conversational interfaces generate a new type of conversational data that can be analyzed to gain better understanding of customer desires. Those who are quick to adopt and adapt to this technology will pioneer a new way of engaging with their customers.

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