In this article, You will learn about Conversational AI and what is a key differentiator of conversational artificial intelligence.
Conversational artificial intelligence (AI) uses NLU (Natural Language Understanding) and other humanlike behaviors to enable natural conversations.
These conversations may take place via text, voice, touch, or gesture input on a variety of different devices and platforms.
Unlike traditional bots, conversational AI is omnichannel, so your customers can engage with your business using the channel that suits them best.
This means that you have more chances to make a good impression on your customers by giving them their information quickly, delivering exceptional customer service, or offering products they might be interested in.
What is Conversational Artificial Intelligence?
Conversational AI (CAI) enables natural conversations via text, voice, touch, or gesture input.
It’s important to note that CAI is different from traditional bots because it uses NLU (Natural Language Understanding) and other humanlike behaviors to make it seem like users are conversing with real people.
This makes CAI omnichannel it can be used across channels such as web, mobile, chat, SMS/messaging apps, and even IVR systems.
Conversational AI is the key differentiator of the conversational bot in artificial intelligence that enables conversations that are just like what humans have.
That’s why it’s so important for businesses to consider implementing CAI into their customer service strategies it can be used across channels such as web, mobile, chat, SMS/messaging apps, and even IVR systems.
This means that companies can improve their customer service without having to hire additional staff or build new infrastructure CAI allows them to leverage existing resources while improving engagement with customers.
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What Is A Chatbot?
A chatbot, or chat robot, is an application that appears to be able to hold conversations with human users.
Chatbots are typically integrated into messaging applications, with which they interact by sending and receiving user input.
They are often used for lead generation, customer service, and information provisioning in vertical markets such as retail and banking.
The goal of a chatbot is to simulate an intelligent conversation with humans using artificial intelligence techniques, including natural language processing and machine learning.
The most advanced chatbots can learn from previous interactions, develop their own personalities over time, and even understand the context surrounding previous conversations.
What is Natural Language Understanding?
The latest generation of conversational artificial intelligence models employ Natural Language Understanding (NLU) techniques such as Semantic Interpretation, Sentiment Analysis, and Dialog State Tracking to parse sentences and find ways to respond.
For example, some systems use machine learning algorithms to track intents throughout a conversation, so they know when you’re asking a question versus making a statement.
Others are capable of parsing input into multiple parts such as a topic or object to better match users’ needs with their data or content.
Related Article: Top 10 Natural Language Processing Tools | Text Analysis
What makes Conversational AI so Different from Traditional Chatbots?
In contrast to conventional chatbots, conversational AI makes use of NLU (Natural Language Understanding) and other more human-like features to enable genuine interactions.
Instead of interacting with only text, voice, or touch, conversational AI offers these channels alongside gestural input, which is an omnichannel user experience.
This capability also means that you can interact with your bot on whichever device you choose, whether it’s your smartphone, computer, or smartwatch.
As such, conversational AI has become one of today’s most popular forms of artificial intelligence, and for good reason.
It enables people to have interactions across channels that may have historically required multiple chat apps to accomplish the same thing and required users to be very savvy in their use of those apps.
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What is the key differentiator of conversational Artificial Intelligence?
It’s the use of NLU (Natural Language Understanding) and other humanlike behaviors to enable natural conversations.
These abilities make conversational AI different from the more traditional chatbots, which are primarily made up of rules-based actions that guide the flow of the conversation and have little flexibility beyond that.
1. Agent Mindset
To design conversational AI, it’s important to put yourself in your agent’s shoes, What would you say? How would you respond? What if someone asked you a question that was out of your wheelhouse?
Understanding how your agent feels about what it does and how people will feel about working with him or her is essential for designing an effective chatbot experience.
Also, adding intelligence to your bot means giving it feelings. So make sure your bot has them too! (As long as they don’t interfere with its ability to do its job.)
2. Emotional and Behavioral Awareness
Conversational AI is aware of your state and mood, taking into account what you’ve been talking about.
For example, if you’re angry, know to steer clear of controversial topics that could be upsetting or will lead to an argument. Because it knows how you feel, conversational artificial intelligence can help with stress relief and managing anxiety.
Like a person you’re counseling, it can guide conversations toward common goals. Why do consumers love Conversational AI? It’s because it’s more than just a conversation it’s an experience.
It has emotional and behavioral awareness that makes it feel like you’re interacting with another person, not just talking to a machine.
3. Enabling Natural Conversations
When a user types or says something, it triggers an output in response, This can range from text responses to voice-enabled audio responses, as well as actions like buttons or emojis that facilitate deeper engagement with users.
Users can engage using their preferred channel—whether that’s through SMS, Facebook Messenger, Alexa, Google Home, Slackbot, etc. and have a consistent experience across all channels.
In addition to being omnichannel, conversational AI is also cross-channel; users don’t need to leave their preferred channel for another one if they want more information about your product or service.
4. Open Channel for Communication
With traditional chatbots, you have to make sure that your users know about every single way of contacting you.
With conversational AI, there’s only one channel for communication but it can be used from anywhere and doesn’t require any extra steps.
This means that new customers will be able to reach out to you via text, voice, or touch from any channel they prefer and if they prefer all three channels simultaneously, it still works!
The user experience with conversational AI is also much more natural than with traditional bots, which can come across as pushy or awkward.
You don’t want your potential customers to feel like they’re being sold to; you want them to feel like they are communicating naturally with another human being who cares about their needs and wants.
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5. Omnichannel Interaction
With its ability to respond on every channel and device, conversational AI has become an omnichannel experience.
In short, it allows you to use your preferred channel voice, text, touch, or gesture without having to switch between them.
People will be able to interact with businesses through any channel they choose; that’s what makes conversational artificial intelligence so revolutionary.
When people want something done, they won’t have to learn how to speak another language (like traditional chatbots do), They can just communicate their needs naturally.
And when they need assistance with multiple tasks, they don’t have to go from one place to another.
Conversational AI enables natural conversations across channels and devices for both business-to-business interactions as well as business-to-consumer interactions.
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Top 5 Conversational AI-Based Products
One of the primary differences between conversational AI and traditional chatbots is the use of NLU (Natural Language Understanding) and other behaviors to simulate the sense of human conversation.
For example, text, voice, touch, or gesture input. As opposed to bots of the past, conversational AI is available on many platforms, Here are 5 companies with products based on these principles.
1. Sensay
Sensay has created an artificial intelligence platform that allows users to communicate via messaging, voice, video calls, and emojis.
Users can create their own personal AIs by answering questions posed by Sensay’s bot.
2. Pandorabots
Pandorabots is an easy-to-use tool for creating your own chatbot without any coding experience required
3. Microsoft Bot Framework
The Microsoft Bot Framework makes it easy for you to build intelligent bots that interact naturally wherever your users are talking, from text/SMS to Skype, Slack, Office 365 mail, and other popular services
4. Amazon Lex
Amazon Lex is a service for building conversational interfaces into any application using voice and text.
5. Google Dialogflow
Google Dialogflow helps you quickly build a fully managed end-to-end dialog system that leverages powerful machine learning capabilities to deliver engaging user experiences.
It provides deep integration with Google Cloud Platform services such as Cloud Speech API, Cloud Natural Language API, and Cloud Translation API
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Conclusion
What distinguishes conversational AI from a chatbot is the NLU (Natural Language Understanding) and other artificial intelligence techniques for conversing more like a human.
Unlike traditional bots, conversational AI is omnichannel, which means it can interact with users via text, voice, touch, or gesture input.
Ultimately, that’s what sets conversational AI apart: its ability to help you connect with people by speaking their language.
Key Differentiator(s) in Artificial Intelligence for Conversational AI is an NLP and NLU, This is why companies like Google have been investing so much time and money into it.
Because it’s not just about being able to have a conversation with your computer, but rather it’s about being able to interact with your computer in ways that are indistinguishable from talking with another person.
This will be increasingly important as more people start interacting with computers on an everyday basis.
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