Chatbot vs conversational AI: Comprehensive guide

Conversational interfaces have been around for quite some time, but with the rising popularity of AI and its many use cases, they couldn't stay immune to the changes.

And conversational interfaces are popular - there is no denying it. In 2022 alone, over88% of users engaged in at least one conversation with an AI chatbot.

But, chatbots aren't the only conversation interfaces present on the market. There are many different other examples and it can be hard to distinguish what are the differences between them and in which situations they can be used.

Probably the most common confusion is about chatbots vs conversational AI. What is a chatbot? What is conversational AI and what is the difference between the two?

Simply put, in its essence a chatbot is a decision tree that is manually set up and provides different responses based on the input it is given. Usually, the replies it gives are predetermined.

Conversational AI is a generative AI that can mimic human conversation more naturally. It understands human speech, emotions and tone of voice. It’s a component of many new conversational solutions such as AI chatbots, AI and voice assistants. 

But this only touches the surface between the differences of the two. Let’s dig a bit deeper to understand it better.

What is a chatbot?

A conversational chatbot is a programmed solution that is designed to have a conversation with a user. Depending on the input they are given, chatbots provide meaningful answers. Simply put, they have a decision tree in the background that determines the answer to each specific input.

More advanced chatbots can use the power of generative AI to process the input in a “smarter” way and provide responses that are not predefined. These bots analyze the input they receive and respond accordingly.

Such bots can utilize natural language processing and machine learning. Thanks to all of this, they can have meaningful conversations with users even when the subject deviates and can understand human language.

They can resolve customer requests efficiently, propose solutions and perform certain tasks. We could go into even more detail about how chatbots workon the backend, but let's leave that for another read.

Types of chatbots

There are different types of chatbots, depending on the logic that they have: rule-based chatbots and AI chatbots.

Rule-based chatbots 

Rule-based chatbots (in some cases also known as "basic" chatbots) have rules that they follow to respond to the user's input. At their core, rule-based chatbots are just decision trees that generate answers depending on the input that they receive.

They are called "basic" chatbots because they can't deviate from the decision tree setup that they have under the hood, but they are ideal for streamlining customer interactions. They are mostly used as virtual assistants and as part of initial and basic customer service requests.

Key benefits that rule-based chatbots bring to your business are:

• FAQ answering

• Streamlining responses that customers get based on your needs

• Save the need for a live agent to interfere 

For example, if you are looking for achatbot for a small business, the rule-based chatbot would be a great pick.

king for achatbot for a small business, the rule-based chatbot would be a great pick.

Source:Quora

AI chatbots 

AI chatbots use the power of artificial intelligence and they work differently at their core compared to rule-based chatbots. 

In addition to AI (a field of science that researches and develops methods for machines to understand input/output like humans), they also use a natural language understanding process (usage of algorithms and AI, backed by large libraries of information, to understand human language) which essentially analyzes the users' input and provides a meaningful response.

There isn't any decision tree and all responses that AI chatbots generate come from AI technology and human language understanding. AI chatbots are more complex and flexible than rule-based chatbots.

Source: Chatfuel

Key benefits that AI chatbots bring to your business are:

• Real-time interaction

• Natural language processing and understanding

• Ability to solve more complex customer issues

• Personalized responses

For example, AI chatbots are perfect asenterprise chatbots, in bigger companies that require a more complex approach for their clients. AI chatbots are also common in sales and are often part of some of thebest AI sales assistant softwares.

Rule-based chatbots and AI chatbots: What are the use cases?

Both rule-based chatbots and AI chatbots have their use cases. Depending on what your business is and what you need the chatbot for, both of them have their pros and cons.

For example, if you want to streamline the buying process in your store and help users with frequently asked questions, a rule-based chatbot would be a good pick. Answers that users seek need to be straight to the point and simple and adding more complexity to them can do more harm than good.

But, if you are an owner of a real estate business, AI chatbots can be much more useful. Users can ask various questions that usually require a more "personal" answer, so the flexibility that AI chatbots offer is more than welcome.

If you are wondering how much a chatbot costs, it's worth putting into perspective that an AI chatbot is usually more expensive than a rule-based chatbot.

All of these use cases show how a chatbot can benefit your business, regardless if it's rule-based or an AI one. 

What is conversational AI?

Now that we know what chatbots are, we are only missing one more puzzle piece to understand the differences between chatbots and conversational AI. 

Conversational AI is an all-around term that combines different ways of conversation between a machine and a human. Conversational AI can be used in various systems - such as chatbots, voice assistants (such as Siri), or any other communication application.

Chatbots and conversational AI go hand in hand and we can say that there wouldn't be any AI chatbots if conversation AI didn't exist. You can look at conversational AI as the powering tool, the engine, or the core of any communication platform, not only chatbots.

The thing with conversational AI is that it's relatively new and thanks to all the research and development, it's becoming more and more complex as time goes by. Every conversational AI model remembers the responses it gets and ensures that it becomes even better next time. So in a nutshell - it's learning and adapting. This means that it can get only better as the time goes by.

But what builds the conversational AI? Let's dig a bit deeper. Key components of conversational AI are:

• Machine learning

• Natural language processing (NLP)

• Data mining

• Automatic speech recognition (ASR)

Machine learning

Machine learning is a subfield of AI used to understand massive collections of data and drive conclusions from them. Thanks to complex algorithms and statistical models, machine learning identifies patterns in the data and creates logical predictions.

Since it's powered by an AI engine, it's constantly learning and adapting. It also has a human language component and analyzes data so that it's understandable to humans and it's used in almost all conversational AI solutions.

Natural language processing (NLP)

Natural Language Processing (NLP) is a subfield of AI focused on the interaction between computers and human language. It involves the development of algorithms and models that allow computers to understand, interpret, generate, and respond to human language in a way that is both meaningful and useful.

NLP is essential for conversational AI chatbots. We can say that it's the main power source of any intelligent solution and thanks to NLP, conversational AI is capable of transforming data, analyzing it and providing meaningful responses.

Without NLP, chatbots and conversational AI wouldn't be what they are today and we would still deal with very basic solutions that can't think "out of the box" and be flexible.

Data mining

Data mining is the process of discovering patterns, correlations, and insights from large collections of data using statistical, mathematical, and computational techniques. It involves extracting useful information from raw data to make informed decisions, predict future trends, or gain a deeper understanding of a given domain.

Thanks to data mining, conversational AI models provide more up-to-date input and generate predictions based on fresh and recent data.

Conversational data has patterns that data mining recognizes and utilizes to enhance the performance of the conversational AI engine. It's a neat feature that conversational AI chatbots benefit from and thanks to data mining, developers can enrich each new version and make it better for the users.

Automatic speech recognition (ASR)

AI conversational models can also be vocable and understand human voice to analyze input and provide a meaningful response in real time. ASR is the key component conversational AI relies on for solutions such as Siri and Alexa that use human voice for interaction.

ASR is also used in text-to-speech queries that are often used for translation and natural language conversations between a machine and a human.

Chatbot vs conversational AI: key differences

So what is the difference between chatbots and conversational AI? Sure, everything sounds clear in theory but if we put it into practice, how can one differentiate between the two?

If we look at the traditional chatbots, we can see that they respond in a predefined way, usually following a set logic that lies in the background. If we add conversational AI to the equation, now the chatbot can understand the context of the conversation and go beyond the predefined logic. 

It can give more complex answers, understand human language better, put human emotions into the context of the answer and adjust it accordingly to make it more human-like.

Also, it can analyze the conversation, remember what was said previously and learn from any mistakes that you point out.

For example, a simple chatbot can't understand if the customer is happy or not. However, conversational AI chatbots understand if they are dealing with happy or unhappy customers and based on the input they have, they can tailor the answer so it reflects the way a customer is feeling.

Conversational AI makes a simple chatbot more sophisticated and smart. It adds a "human" touch to a "cold" machine, making it more conversation-appealing.

Chatbots and conversational AI go hand in hand. We could also say that nowadays every new chatbot has conversational AI in it. 

Although basic chatbots with linear decision tree-based answers are still used for simple customer interaction, chatbots that have conversational AI incorporated offer greater flexibility and a more personal approach with the customers.

It's also worth mentioning that AI technology is evolving every single day and better conversational AI also means that chatbots will also get better.

Examples of chatbot platforms

Some of the most used chatbots on the market are:

1. Chatfuel

2. TidioLyro

3. Kommunikate

4. Drift

Chatfuel

Chatfuel is an advanced chatbot platform for automating client communication on WhatsApp, Facebook, Messenger and Instagram. It utilizes AI and natural language processing to give meaningful answers and communicate with customers naturally and flexibly - thus, we can say that it falls into the AI chatbot category. 

It is powered by a conversational AI engine so if you are struggling with a lot of leads who need personal answers, Chatfuel is the perfect pick.

Chatfuel has ready-to-use templates and plugins that can be set up easily. It has integration with different platforms (Instagram, Whatsapp, Facebook) and provides analysis of user interactions and engagement understanding. It also offers the possibility of a custombot building service, if you have specific requests and demands.

Many users say that Chatfuel is one of thebest no-code chatbot builders. This means that you don't need to have any programming knowledge to set up your AI chatbot and have it up and running quickly.

Tidio Lyro

Tidio Lyro is a messaging platform that uses AI technology and its own AI in-house models to communicate with customers in real-time. With the help of human language analysis and machine learning knowledge, it provides human-like responses and meaningful answers.

Source: Tidio website

Kommunikate

Kommunikate is another great chatbot platform. It helps businesses improve their customer relations with natural communication, automated messages and fast response time. Like other solutions on the list, it’s powered by AI and combined with natural language processing, this chatbot increases customer satisfaction and reduces response time.

Source: Kommunikate website

Drift

Drift is tailored for marketing and sales businesses that want to increase the conversational satisfaction of their clients. Drift has its chatbot that they call Driftbot. It can book meetings, engage with customers in a more personalized way and route conversations so that they are results-driven and more direct.

Source: Drift website

Examples of conversational AI platforms

The most popular conversational AI platforms on the market are:

• Chatfuel

• Haptik

• Yellow.ai

• Drift

Chatfuel

Conversational AI powers almost all aspects of Chatfuel. Whether you want increased sales, chatting with customers and leads, launching new pipelines or managing appointments, Chatfuel and its conversational AI powered by machine learning and NLP can bring your business to the next level.

Chatfuel took it a step further and generated its own conversational AI model called "Fuely AI" which is under the hood of all functionalities Chatfuel offers. Whether it's WhatsApp, Instagram or Facebook chatbots that you are looking for, Chatfuel has you covered and with an all-in-one solution.

If you are still wondering how you can utilize a chatbot, here are thetop 9 reasons why your business needs a chatbot.

Chatfuel bots have a human "feel" to them, responses they generate are personalized.

Chatfuel can also make your business more efficient. For example, thanks to Chatfuel,HelloFresh reduced response time for their customers by 76%. Want to test the Chatfuel AI bot?Start a free trial.

Source: Chatfuel

Haptik

With the help of conversational AI, Haptik can automate and elevate your customer interactions. Whether you need better customer care, integration with messaging apps such as WhatsApp or Messenger and lead generation to convert passive website visitors to interested customers, Haptik can be a useful tool.

Haptik also has several templates that are ready to use and tailored for specific industries such as E-commerce and retail, financial services, travel and digital media. All solutions are powered by conversational AI and virtual assistants.

Source: Haptik website

Yellow.ai

Conversational AI present in Yellow.aipowers all of their services such as AI agents, AI assistants and AI analytics that they use to analyze the data. It excels in customer support, automated messaging and feedback reporting which is essential if you want to make your customers count and give them a more personal approach.

Conversational AI used in AI agents can be tested for free and if you ever wonderedhow to make a chatbot for free, you don't have to seek answers anymore. 

Source: Yellow.aiwebsite

Drift

Conversational AI powers Drift's signature Driftbot which is one of the most used products they offer. Thanks to the AI, with Driftbot customer experience your business can become even better as the chatbot will answer all questions in a personalized and precise way.

Drift emphasizes that their bot is smart and can turn leads into real customers. Apart from the chatbot, AI powers their live chat functionality and conversational landing pages which is a new product they offer.

Choosing between chatbots and conversational AI

Understanding the differences between the two can be hard but once you get a hang of it, it will be clear when and how chatbots and conversational AI can be used.

If you are looking for a conversational model that will enrich the way you communicate with your clients and customers, then conversational AI can help you out.

If you need a way to communicate with your clients and customers automatically and help them with straightforward information and replies, then an onboarding chatbotwould be a good way to start.

However, if you want the best of both worlds and utilize the power of AI in chatbots, then conversational AI chatbot is the way to go.

Platforms such as Chatfuel offer exactly this, so if you want to kickstart your chatbot AI journey,start a free trial.

FAQs

Are chatbots the same as conversational AI?

Not exactly - both of them exist as standalone entities and are different. Adding conversational AI to chatbots makes them more complex and "smart". Solutions offered by companies such as Chatfuel have the best of both worlds.

 What are some use cases for rule-based and AI chatbots?

Rule-based chatbots are best suited for scenarios where straightforward, consistent responses are needed, such as in retail for handling FAQs or streamlining the buying process. 

AI chatbots are better for environments where more personalized and complex interactions are required, such as in real estate, where clients may have a wide range of questions that need flexible and human-like responses.

What is the best AI chatbot for me?

There are many AI chatbots on the market and it can be hard to point out which is the best. But, with all the features it offers and integrations to different communication platforms, Chatfuel stands out as one of thebest AI customer service software in 2024.

Do I need a chatbot?

It depends on the business that you have and what you are looking for. Sure, adding a chatbot to automate repetitive communication with your customers can be a good thing, but it doesn't always have to be mandatory.