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Chatbot vs conversational AI: What's the difference?

Conversational AI promises to improve human-computer interaction, but how is it different from chatbots?
By
January 10, 2024
Microsoft Bing Chat listening next to Google Assistant listening
Rita El Khoury / Android Authority

When the word ‘chatbot’ comes to mind, it’s hard to forget the frustrating conversations we’ve all had with customer service bots that seem unable to understand or address our inquiries. That’s because, until recently, most chatbots spit out canned responses and couldn’t deviate from their programming. Thankfully, a new technology called conversational AI promises to make those frustrating experiences a relic of the past. So in this article, let’s take a closer look at what conversational AI is and how it differs vs chatbots.

What is a chatbot?

Pixel 7 direct my call menu
Google

The term chatbot refers to any software that can respond to human queries or commands. The term chatbot is a portmanteau, or a combination of the words “chatter” and “robot”. The term chatterbot was first used in the 1990s to describe a program built for Windows computers.

Early chatbots could only respond in text, but modern ones can also engage in voice-based communication. Regardless of the medium, chatbots have historically been used to fulfill singular purposes. For example, you may encounter a chatbot when you call your bank’s customer service helpline. It may ask you a few questions and route your call to the appropriate human agent.

Basic chatbots simply look for pre-programmed keywords or phrases and respond accordingly.

In most cases, chatbots are programmed with scripted responses to expected questions. This means they fall flat in new or unfamiliar conversations. You typically cannot ask a customer service chatbot about the weather or vice-versa.

Newer chatbots may try to look for certain important keywords rather than reading entire sentences to understand the user’s intent, but even then, may not always be able to respond accurately. If you’ve ever had a chatbot respond along the lines of “Sorry, I didn’t understand” or “Please try again”, it’s because your message didn’t contain any words or phrases it could recognize.

What is conversational AI?

Alexa Emergency Assist on an Echo Pop
Amazon

Conversational AI refers to a computer system that can understand and respond to human dialogue, even in cases where it wasn’t specifically pre-programmed to do so. As their name suggests, they typically rely on artificial intelligence technologies like machine learning under the hood.

We’ve seen big advancements in conversational AI over the past decade, starting with the release of Siri, Google Assistant, and Alexa. These services use natural language processing (NLP) to understand human language and respond with unique responses beyond predefined ones.

It’s worth noting that the term conversational AI can be used to describe most chatbots, but not all chatbots are examples of conversational AI. In other words, Google Assistant and Alexa are examples of both, chatbots and conversational AI. On the other hand, a simple phone support chatbot isn’t necessarily conversational.

Conversational AI relies on natural language processing (NLP) and machine learning to generate new responses.

Newer examples of conversational AI include ChatGPT and Google Bard that can engage in much more complex and nuanced conversation than older chatbots. These rely on generative AI, a relatively new technology that learns from large amounts of data and produces brand new content entirely on its own.

Generative AI allows modern chatbots to converse about a range of different topics, without any guidance or programming beforehand. And in many cases, they can understand and generate natural language as well as a human.

Chatbots vs conversational AI: What’s the difference?

Google Assistant pop-up on a Pixel
Mishaal Rahman / Android Authority

We’ve already touched upon the differences between chatbots and conversational AI in the above sections. But the bottom line is that chatbots usually rely on pre-programmed instructions or keyword matching while conversational AI is much more flexible and can mimic human conversation as well.

In spite of recent advances in conversational AI, many companies still rely on chatbots because of their lower development costs. Generative AI products require much more computational power as they rely on large machine learning models.

Here’s a table that highlights the differences between chatbots vs conversational AI:

ChatbotsConversational AI
Language understanding
Chatbots
Basic, responds to keywords or phrases
Conversational AI
Advanced, responds to wider variety of questions or commands
Intelligence
Chatbots
Low, mostly pre-programmed question-answer pairs
Conversational AI
High, can understand complex conversations
Memory
Chatbots
Little to none, won't remember key details in long conversations
Conversational AI
Medium to high, may remember context throughout longer conversations.
Personalization
Chatbots
Minimal, may narrate singular data points like account number
Conversational AI
High. For example, can dynamically change conversational tone based on user preferences
Computational requirements
Chatbots
Low, can run on basic hardware
Conversational AI
High, requires powerful servers
Use cases
Chatbots
Basic customer support, troubleshooting, simple task fulfillment
Conversational AI
Digital assistants, problem solving with logical reasoning
Examples
Chatbots
Food delivery chatbot, feedback or questionnaire chatbots
Conversational AI
Google Assistant, Bard, Alexa, ChatGPT

FAQs

Yes, ChatGPT is an example of conversational AI. It can mimic human dialogue and keep up with nuanced and complex conversations.

Conversational AIs are trained on extremely large datasets that allow them to extract and learn word combinations and sentence structure. For example, ChatGPT was trained on 300 billion words or 570 GB of data.

ChatGPT Plus with the latest GPT-4 Turbo language model is universally regarded as the best AI chatbot. However, this position may change as competitors improve over time.