An Introduction to Conversational AI Maturity

Have you ever come across the term conversation – AI maturity? If not, check out this write-up wherein we have provided the basic information on this subject.

An Introduction to Conversational AI Maturity
An Introduction to Conversational AI Maturity

Conversation AI is a term used more broadly than most people ever realize. AI is used -extensively in our homes to make our lives comfortable. It even helps us in our jobs. You may even go ahead and compare an AI solution to a virtual co-worker who scales your repetitive and time-consuming tasks. 

Before we head to the maturity levels of AI, it is important to have a basic understanding of the term – Conversation AI and how it can be tailored to different uses. 

What is conversation AI? 

Conversation AI is a combination of technologies that work in the background of the automated messaging and speech-enabled applications that allow human-like interactions between humans and computers.

Conversation AI allows communication by recognizing human speech and text, understanding the context, interpreting the meaning and responding in a way a human does.

Conversation AI is based on both art and science. Science is the backbone of application development, but human-like interaction needs the art of incorporating context to a message, personalizing and adding relevance to response to the received message. It must be noted that not all programs based on conversation AI are built the same.

Some can comprehend only a few keywords and respond in fragmented sentences, while some may give the exact feeling of talking to a human. The best conversational AI is the one whose response is indistinguishable from the response of a human. The most advanced conversation AI-based tool can understand complex sentences and feelings and respond like a human.  

What does it entail? 

A conversational AI can be used to communicate with humans in different forms. The interaction can be written as with chatbots or based on speech as with voice assistants like Alexa or Siri.  The four common forms in which we find conversation AI interacting with humans are as follows –

  • Chatbots – Technically speaking, a chatbot is a computer program that stimulates conversation with a human through text or voice commands.  The text message you receive from companies through SMS, WhatsApp, Facebook messenger, or other services normally come from chatbots set for the purpose. The instant message while contacting customer support also is generally sent by chatbots. These are the most basic form of conversation AI-based programs.
  • Voice assistants – Companies like Google, Apple, and Amazon use conversation AI in the form of Voice Assistant. The voice assistant is an AI-enabled program that uses voice recognition, language processing algorithms, and voice synthesis to listen to specific voice commands and respond with relevant information or perform the specific task as commanded by the user. The voice assistants are equipped to filter out ambient noise and listen to specific keywords to respond with relevant information or perform a specific task.
  • Mobile assistants – Mobile assistants are AI-based features embedded in mobile devices that help the user get a personalized experience using their device. Just like the voice assistants, the mobile assistants take command from the user and respond with specific information and perform the specific task they are designed and commanded to do. They are embedded in the device to make certain tasks easier for users and give them a personalized experience. These are one of the fastest developing programs. Most mobile assistants have ascended in the level of maturity swiftly.
  • Intelligent virtual assistants – Intelligent virtual assistant or Artificial Intelligence Virtual Assistant uses advanced conversation artificial intelligence features like natural language processing and voice synthesis, etc., to extract information from complex data to virtually assisting the users in performing specific tasks. These digital assistants are generally embedded in specific programs or applications. You can find intelligent virtual assistants in various mobile and web applications, such as an application of a bank. In addition to solving their problems, these virtual assistants guide the user with steps to complete their desired tasks. An intelligent virtual assistant in an e-commerce application can help users find products of their choice and track their orders.   

Various degrees of AI maturity 

Four levels of conversation AI maturity can be tailored based on the complexity of the tasks to be completed. 

First level – A triage mechanism like a chatbot 

The first level of AI maturity indicates very limited conversational abilities. Programs or applications with this level of maturity possess very simple comprehension abilities. They can comprehend conversation within the defined domain and respond to a very limited word. Their response to the user is restricted to fragmented sentences and keywords.

The best example of the first level of AI maturity program is chatbots. They are designed to respond to limited queries with pre-fed answers. They cannot hold a conversation with a user beyond the defined domain. And, their response cannot extend beyond the restricted words they are programmed with.

A human can easily understand that the response is given by a machine and not by a human. The first level of AI maturity lacks human touch in their conversation.  

The second level – Answer basic questions and also consists of the ability to interact with other systems to answer less predictable questions 

The second level of AI maturity enables the program to answer basic questions by the users. They have the ability to hold a short conversation with context and comprehension. The comprehension level is a little higher than the first level of maturity. Programs at this level of maturity have the capabilities to understand longer queries. Additionally, they can answer the user with full sentences. They can also memorize the context for a short conversation and respond with questions to better understand the issue with the user. While interacting with a program at the second level of maturity, a user may get a feel of human touch in the conversation. Still, the interaction will not completely feel like a human-to-human conversation.  

Third level – Driven more by accumulated data instead of reactionary AI 

The third level of AI maturity indicates the ability to indulge in a long conversation with context and comprehension at an advanced level. The programs at this level of AI maturity are driven more by accumulated data instead of reactionary AI. They can hold a conversation for longer without losing context and comprehension.

They can even understand misspelled words due to typing errors and comprehend the meaning of a full sentence. They can comprehend complex sentences and understand multiple intents in one sentence. They can respond correctly to all the queries and give the feel of human-to-human interaction though they cannot understand the feelings of a said sentence.

Due to their ability to comprehend misspelled words, they make it easier for a user to seek help and give a command.  

The fourth level – Learning from the vast amount of data and multiple fronts and back-end systems 

The fourth level of AI maturity is currently the highest level of AI maturity. This is the most advanced stage we can think of. This stage of maturity indicates the ability to hold multiple conversations at a time.

Programs at this level of maturity have the ability to learn from a vast amount of data and multiple front and backend systems. They can understand multiple input languages and respond accordingly using different languages. Unlike the three previous maturity levels, they understand words, feelings, and sentiments.

Moreover, they use this comprehension of feelings and sentiments to respond to the user. A user will not find any difference while interacting with the fourth-level AI-enabled programs or applications. The conversation at this level exactly mimics the interaction between two humans.  22

Final Thoughts 

The fourth level of maturity of conversation AI can be achieved by gathering lots of data to feed into the solution. As machine learning establishes patterns within the data, the conversation AI solution enhances and acts as an advisor to make informed decisions. 

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