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Chatbots vs Conversational AI: Is There Any Difference?

by Kazimierz Rajnerowicz·Updated
Have you ever wondered if chatbots and conversational AI interfaces are the same? Read our guide to understand the similarities and differences between both technologies and how they can be used by companies cover photo

Conversational interfaces can improve customer satisfaction and boost customer engagement. They can handle online customer service, real-time social sales, marketing automation—you name it!

No wonder businesses adopt AI chatbot solutions so eagerly. 

But—

There are so many different buzzwords! Let’s take chatbots vs conversational AI for example. Is there any difference between them? Or are they the same thing?

It can make your head spin just trying to evaluate your options, let alone actually build something.

Don’t worry. We are here to help you figure it all out.

In this article:

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Conversational AI vs chatbots: comparison

It’s difficult to draw a clear line between chatbots and conversational AI. In fact, the two terms are often used interchangeably.

Typically, by a chatbot, we usually understand a specific type of conversational AI that uses a chat widget as its primary interface.

Conversational AI, on the other hand, is a broader term that covers all AI technologies that enable computers to simulate conversations.

Conversational AI is used in software such as bots, voice assistants, and other apps with conversational user interfaces.

So—

What is the difference between a chatbot and conversational AI?

Well, it’s a little bit like asking what is the difference between a pickup truck and automotive engineering. Pickup trucks are a specific type of vehicle while automotive engineering refers to the study and application of all types of vehicles.

In a similar fashion, you could say that customer service chatbots are an example of the practical application of conversational AI.

ChatbotConversational AI
A piece of software that simulates human-like conversations and interactions. It can be powered by AI or not.A general expression that can mean technologies, solutions, or specific engines that use artificial intelligence to simulate conversations.
Example:
– Tidio is a chatbot platform for creating AI bots without coding
Example:
Dialogflow by Google Cloud is a conversational AI used for designing virtual agents
✅ A chatbot is great for automating tasks and customer service✅ Conversational AI can help you create more natural and lifelike conversations

As you can see, there is a big overlap. Essentially, chatbots are conversational AI put into action.

However, some people may refer to simple text-based virtual agents as chatbots and enterprise-level natural language processing assistants as conversational AI.

At the end of the day, it doesn’t really matter what you call them. The terminology varies from case to case. The important thing is that these technologies are becoming more and more advanced and beneficial. In fact, about one in four companies is planning to implement their own AI agent in the foreseeable future.

According to a report by Accenture, as many as 77% of businesses believe after-sales and customer service are the most important areas that will be affected by artificial intelligence assistants. These new virtual agents make connecting with clients cheaper and less resource intensive. As result, conversational AI solutions are revolutionizing the way that companies interact with their customers.

Let’s take a closer look at both technologies to understand what exactly we are talking about.

What is a conversational chatbot?

A conversational chatbot is a computer program that is designed to simulate a conversation with a user. Bots are meant to engage in conversations with people in order to answer their questions or perform certain tasks. 

From real estate chatbots to healthcare bots, these apps are getting implemented in a variety of industries. Conversational bots can provide information about a product or service, schedule appointments, or book reservations. While virtual agents cannot fully replace human agents, they can help businesses maintain a good overall customer experience at scale. In fact, by 2028, the global digital chatbot market is expected to reach over 100 billion U.S. dollars.

real estate chatbot example

Now—

Do all chatbots use conversational AI?

This question is difficult to answer because there is no clear definition of artificial intelligence itself.

In general, the term AI is used to describe any computer system that can perform tasks that would normally require human intelligence. Nevertheless, some developers would hesitate to call chatbots conversational AI, since they may not be using any cutting-edge machine learning algorithms or natural language processing.

So, the use of AI is frequently the key differentiator. That’s why our two main types of chatbots are rule-based bots and AI bots.

Rule-based chatbots follow a set of rules in order to respond to a user’s input. Under the hood, a rule-based chatbot uses a simple decision tree. This means that specific questions have fixed answers and the messages will often be looped.

AI chatbots, on the other hand, use artificial intelligence and natural language understanding (NLU) algorithms to interpret the user’s input and generate a response. They can recognize the meaning of human utterances and generate new messages dynamically. This makes chatbots powered by conversational AI much more flexible than rule-based chatbots.

Here is an example of two AIs having a conversation.

Caption: Chatbot vs chatbot

Read more: How to Recreate In-Store Customer Experience with the help of AI

What are the different types of conversation bots?

Setting the “AI or not AI” question aside, there are many other ways to categorize chatbots. It’s a good idea to focus on your chatbot’s purpose before deciding on the right path. Each type requires a unique approach when it comes to its design and development.

  • Live chat chatbots. Customer service bots and virtual assistants that help customers with frequently asked questions or basic requests through website live chat widgets
  • Social media bots. They interact with users on social media platforms such as Instagram or Facebook
  • Instant messaging bots. These bots work within messaging apps such as WhatsApp or Messenger to provide omnichannel support
  • Chatbot apps. Android and iPhone apps with chatbot interfaces, for example, Replika
  • Online chatbots. Interactive personalities that are embedded on dedicated websites or landing pages, for instance, Kuki AI

The most common type of chatbot is the support chatbot that customers can access via chat widgets or messaging apps. These bots can answer questions from customers and provide information about products or services, such as prices or availability. They do it much faster than human agents. And, in the context of good customer experience, faster does mean better.

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Read more: Popular Chatbot Use Cases

What is conversational AI?

The majority of chatbots are text-based, meaning they rely on typed input from users to generate responses. Historically speaking, a “chat bot” is not a “bot that you can have an informal conversation with,” but rather a “bot for online chat rooms.” While some people refer to virtual AI assistants like Amazon’s Alexa as voice-based chatbots, others would be hesitant to call them chatbots at all.

So, what should we call these devices?

“Conversational AI” is a good catch-all term. As we mentioned before, it’s synonymous with AI engines, systems, and technologies used in chatbots, voice assistants, and conversational apps.

At their core, these systems are powered by natural language processing (NLP), which is the ability of a computer to understand human language. NLP is a field of AI that is growing rapidly, and chatbots and voice assistants are two of its most visible applications.

How does conversational AI work?

In order to understand how conversational AI works, it’s helpful to think about the ways in which humans communicate. When we have a conversation with someone, we take turns speaking and listening. We use verbal and nonverbal cues to signal when it’s our turn to speak, and we adjust what we say based on the responses we receive.

Computers, on the other hand, are not very good at understanding human communication. They can’t pick up on verbal cues like tone of voice, and they don’t have the ability to interpret nonverbal cues like body language. Truth be told, some bots are not very smart.

This is where NLP comes in.

NLP is a field of AI that deals with teaching computers how to understand human language. This involves teaching them to recognize patterns in speech and text, and to interpret the meaning of those patterns.

There are many different techniques that can be used for NLP, but machine learning is among the most important ones right now. It’s a method of teaching computers to learn from data, without being explicitly programmed to cover all possible cases.

This means that a conversational AI can understand new utterances even if it has never heard them before.

Read more: How to Set up an NLP Chatbot in Tidio

What is the key differentiator of conversational AI?

On the surface level, basic chatbots and advanced conversational AIs may seem very similar. Both are capable of engaging in conversations with people. Sometimes you can even get the same result from either one.

However, many business executives are concerned about implementing bots. About 47% of them are worried that bots cannot yet adequately understand human input.

Now—

While a traditional chatbot is just parroting back pre-determined responses, a conversational AI can actually understand the context of the conversation and respond in a more natural way. The natural language processing functionalities of conversational AI engines allow them to understand human emotions and intents better, giving them the ability to hold more complex conversations.

For example, conversational AI understands if it’s dealing with customers who are excited about a product or angry customers who expect an apology.

AI can also use intent analysis is similar to determine the purpose or goal of messages. For example, if someone writes “I’m looking for a new laptop,” they probably have the intent of buying a laptop. But if someone writes “I just bought a new laptop, and it doesn’t work” they probably have the user intent of seeking customer support.

This solution is becoming more and more sophisticated which means that, in the future, AI will be able to fully take over customer service conversations. Implementing AI technology in call centers or customer support departments can be very beneficial. This would free up business owners to deal with more complicated issues while the AI handles customer and user interactions. 

Read more: AI Taking Over Jobs: Statistics & Trends

How to build a conversational AI chatbot

From the perspective of business owners and developers, the most important difference between bots and advanced conversational AI is that the latter is much harder and more costly to develop.

Building a conversational AI requires significant investment of time and resources. You need a team of experienced developers with knowledge of chatbot frameworks and machine learning to train the AI engine. The development process of AI applications is also much longer.

On the other hand, you can find many online services that allow you to quickly create a chatbot without any coding experience.

In fact, let’s do it right now.

You are going to be surprised at how easy building your own AI agent is.

Step 1: Create your free account

step 1 install the code

To get started, go to Tidio’s register page and create a free account. There are many signup options available. You can sign up with your email address, your Facebook, Wix, or Shopify profile. Follow the steps in the registration tour to set up your website widget or connect social media accounts.

Step 2: Prepare the AI bot conversation flows

AI bot conversation flows preparation

Try to identify the key areas where your visitors need help. It may be helpful to extract popular phrases from prior human-to-human interactions. If you don’t have any chat transcripts or data, you can use Tidio’s ready-made chatbot templates. There is one for almost every use case and conversation scenario. Then, adjust conversation scripts to your company’s needs by changing selected messages and bot behavior.

Step 3: Train the AI bot

AI bot training example

After you’ve prepared the conversation flows, it’s time to train your NLP bot agent. You can do this by adding training data based on real customer queries. Go to the Visitor Says node that triggers each of the chatbot flows. Choose one of the intents based on our pre-trained deep learning models or create your new custom intent. To do this, just copy and paste several variants of a similar customer request.

Read more: Best Practices for Training a Chatbot

Step 4: Monitor and improve

monitoring panel

Now that your AI virtual agent is up and running, it’s time to monitor its performance. Check the bot analytics regularly to see how many conversations it handled, what kind of requests it couldn’t answer, and what were the customer satisfaction ratings. You can also use this data to further fine-tune your chatbot by changing its messages or adding new intents.

That’s it! You’ve now created and deployed your first chatbot using Tidio. Remember to keep improving it over time to ensure the best customer experience on your website.

Read more: How to Create a Chatbot: Complete Guide for Beginners

Key takeaway

The difference between a chatbot and conversational AI can sometimes be very subtle. Generally, a chatbot focuses on automating specific tasks. Conversational AI is a broader term and usually, it focuses on simulating human conversation in a more advanced way.

However, both chatbots and conversational AI can use NLP and find their application in customer support, lead generation, ecommerce, and many other fields.

You can create bots powered by conversational AI and NLP with chatbot providers such as Tidio. Our platform makes it easy to set up and train your chatbot. You can even use our visual flow builder to design complex conversation scenarios.

Do you think you are ready to start building your own conversational AI agent? You can give it a go with our free trial—no credit card required!

FAQ

Here are some additional questions and resources you may find helpful:

What is an example of conversational AI?

Some common examples of conversational AI include chatbots, virtual assistants, and customer service robots. The goal of most conversational AI systems is to mimic human conversation as closely as possible, often through the use of machine learning (ML) algorithms. For instance, virtual assistants, such as Amazon’s Alexa or Apple’s Siri, are designed to answer users’ questions in a conversational manner.

What is a conversational AI platform?

Commercial conversational AI solutions allow you to deliver conversational experiences to your users and customer. You can also use conversational AI platforms to automate customer service or sales tasks, reducing the need for human employees. It can be integrated with a bot or a physical device to provide a more natural way for customers to interact with companies.

How much does conversational AI cost?

There are too many factors to name a single number. Some conversational AI engines come with open-source community editions that are completely free.  Other companies charge per API call, while still others offer subscription-based models. The cost of building a chatbot and maintaining a custom conversational AI solution will depend on the size and complexity of the project. However, it’s safe to say that the costs can range from very little to hundreds of thousands of dollars.

Resources:

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Kazimierz Rajnerowicz
Kazimierz Rajnerowicz

Tidio's Content Editor and Copywriter. Casimir writes about live chat and chatbots and watches over the technicalities of the publication process.

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