Chatbots
Conversational AI vs Chatbot: What’s the Difference
The definitions of conversational AI vs chatbot can be confusing because they can mean the same thing to some people while for others there is a difference between a chatbot and conversational AI. Unfortunately, there is not a very clearcut answer as the terms are used in different contexts – sometimes correctly, sometimes not.
Most people can visualize and understand what a chatbot is whereas conversational AI sounds more technical or complicated. This is actually where the true differentiation comes in.
Let’s start with some definitions and then dig into the similarities and differences between a chatbot vs conversational AI.
What is a Bot?
From the Merriam-Webster Dictionary, a bot is “a computer program or character (as in a game) designed to mimic the actions of a person”. Stemming from the word “robot”, a bot is basically non-human but can simulate certain human traits.
What is a Chatbot?
A chatbot or virtual assistant is a form of a robot that understands human language and can respond to it, using either voice or text. Hence the use of “chat” before “bot”. This is an important distinction as not every bot is a chatbot (e.g. RPA bots, malware bots, etc.). Chatbots can be extremely basic Q&A type bots that are programmed to respond to preset queries, so not every chatbot is an AI conversational chatbot. Natural language processing (NLP) technology is at the heart of a chatbot, enabling it to understand user requests and respond accordingly (provided it is trained to do so).
What is Conversational AI?
Conversational AI is a higher-level concept of a chatbot. In order to provide a more individualized customer experiences while reducing the cost to serve, conversational AI bots frequently mix artificial intelligence (AI) technology with others (natural language processing, machine learning, identity management, secure integration, process workflows, dialog state management, voice recognition, etc.).
In essence, conversational Artificial Intelligence is used as a term to distinguish basic rule-based chatbots from more advanced chatbots. The distinction is especially relevant for businesses or enterprises that are more mature in their adoption of conversational AI solutions.
The similarities between the two concepts, however, lie in the fact that they are both conversational and may be used to interact with human users (such as clients, employees, etc.) through conversational interfaces by leveraging the benefits of real-world communication. Digital channels including the web, mobile, messaging, SMS, email, and voice assistants can all be used for conversations, whether they be verbal or text-based.
The Evolution of Chatbots and Conversational AI
Early conversational chatbot implementations focused mainly on simple question-and-answer-type scenarios that the natural language processing (NLP) engines could support. These were often seen as a handy means to deflect inbound customer service inquiries to a digital channel where a customer could find the response to FAQs.
However, these basic chatbots stopped short of executing anything more complex, often handing off quickly to human agents to continue processing the request, especially when the customer query did not follow the expected path. In doing so, the customer experience was poor and agents were frustrated. As chatbots failed they gained a bad reputation that lingered in the early years of the technology adoption wave.
As natural language processing technology advanced and businesses became more sophisticated in their adoption and use cases, they moved beyond the typical FAQ chatbot and conversational AI chatbots were born.
Features of Conversational AI vs Chatbot Solutions
Conversational AI solutions are more advanced chatbot solutions that integrate natural language understanding (NLU), machine learning (ML), and other enterprise technologies to bring AI-powered automation to complex customer-facing and/or internal employee engagements. The fact that the two terms are used interchangeably has fueled a lot of confusion.
To make it easier to understand the difference between conversational ai and chatbots, here is a description of some of the more typical features* of a conversational AI application versus a basic conversational bot.
*not all these features are necessarily part of a conversational AI solution
Features/Capabilities |
Conversational AI |
Basic Chatbot |
| Natural Language Understanding | Advanced | Basic keyword recognition |
| Multi-channel/Omnichannel | √ | single channel |
| Multi-Lingual | √ | limited |
| Machine Learning | √ | no |
| Personalization | √ | limited/none |
| Dialog State Management | √ | no |
| Integrated Processes/Workflows | √ | no |
| Data/System Integration | √ | simple/limited integration |
| Identity & Access Management | √ | no |
| Security Management | √ | no |
From the list of functionality, it is clear to see that there is more to conversational AI than just natural language processing (NLP). And because conversational AI or advanced chatbot solutions are tasked with automating underlying workflows or tasks to respond to user intents and fulfill customer needs, they generally combine conversation flows with process flows. This makes it less complicated to build advanced bot solutions that can respond in natural language while also executing tasks in the background.
Creating and managing conversational AI applications is not simple which is why many enterprises turn to a conversational AI platform to help incorporate many of the above-mentioned capabilities more easily without having to have a big pool of AI and developer talent.
Read about how a platform approach makes it easier to build and manage advanced conversational AI chatbot solutions.