Yes, you got it right. Conversational AI is not exactly a chatbot, even though both of them are closely related. Conversational AI is all about the programming gimmicks or tools that allow a computer to mimic and carry out conversational experiences with people. On the other hand, chatbots are a program that can use conversational AI. In short, it’s the program that communicates with people.
Still confused? Let’s take a closer look!
Chatbots vs Conversational AI
Conversational artificial intelligence (AI) refers to the technology that consumers may converse with, such as chatbots or virtual agents. They employ big data, machine learning, and natural language processing to mimic human interactions by identifying voice and text inputs or by translating their meanings across languages. Natural language processing (NLP) and machine learning are blended well in conversational AI. These NLP procedures feed into a continual feedback mechanism with machine learning processes, allowing AI algorithms to develop over time.
Conversational AI comprises key components that enable it to process, comprehend, and respond in a natural manner. Thinking about just how your potential customers might wish to engage with your product and the main queries they might have is the first step towards conversational AI. You may then employ conversational AI techniques to guide them to the information they need. Conversational AI’s existing applications, according to experts, are poor AI since they are focused on a very limited scope of jobs. Strong AI, which is still a theoretical idea, concentrates on a human-like consciousness capable of solving a wide range of activities and issues.
Chatbots: Knowing More About the Tech Humans
Chatbots are software that employs artificial intelligence and natural language processing to comprehend what a human wants and direct them to their desired goal with the least amount of effort on their part. For your user experience touchpoints, it’s like having a virtual assistant.
In 2016, Facebook widened its developer platform and demonstrated what is achievable with chatbots with its Messenger app, accelerating the popularity of chatbots. Soon, Google joined the fray with Google Assistant. Since then, a plethora of chatbot apps have been developed for use on websites, in apps, on social networks, for customer service, and for a variety of other uses.
The range of ways to develop a chatbot is one of the most intriguing aspects of the chatbot software industry. The technology involved can differ significantly, but it all boils down to your objectives. This does, however, limit a chatbot’s ability to respond to a specified query or instruction. This means that its responses are already pre-determined, and there is only a little amount of leeway for the dialogue to progress. In practice, rather being having an actual conversation with a human, a chatbot provides pre-programmed responses to questions.
A chatbot is best used to replace or enhance the FAQ section, answer inquiries regarding a purchase, or improve customer service accessibility.
Let’s Compare Chatbot vs Conversational AI
Now that we know chatbot and AI conversational two technologies well, let’s compare their capabilities:
1. Learning at Scale
Conversational AI and automation systems get their information from a variety of places, including sites, text corpora, databases, and APIs. Modifications to the conversational AI interface are automatically applied whenever the source is edited or updated. Chatbots, on the other hand, require ongoing and costly manual upkeep to keep their conversational flow useful and productive.
2. Seamless Communication
Additionally, having complete access to a database and API gives conversational AI solutions the contextual elasticity they need to conduct fluid conversations with consumers. A conversational AI interface will immediately scrape the information needed to finish the operation if, for instance, a user changes their opinion mid-conversation or needs a different resource than the one initially requested. A chatbot is limited to the script and rules it was programmed to follow, and it cannot make any output that was not programmed into it.
Unlike chatbots, which can only respond to text orders, conversational AI can respond to speech commands. As a result, conversational AI can be used as a voice assistant (Siri, Cortana, Google Home), a smart speaker like Alexa, a conversational speech layer on a website, or even a virtual call center agent (Amazon Alexa, Google Home). Because of this capacity to work across mediums, businesses can deploy a single conversational AI system all across their digital channels, with data streaming to a central analytics hub.
4. Comprehension Capabilities
Conversational AI employs Natural Language Processing (NLP) and Understanding (NLU), both subfields of languages, computer science, and artificial intelligence, to parse and interpret inputs in the form of sentences in text or speech format rather than depending on a pre-written script. Chatbots, on the other hand, may appear to understand words or phrases when they are simply following a set of instructions. Conversational AI can understand, recognize, and respond to the subtleties of human language, reacting to rich context and idiomatic phrases rich in slang, synonyms, homonyms (words with two meanings), and jargon.
Conversational AI Uses a Combination of Tools
- Automatic Speech Recognizer
- Spoken language understanding module
- Dialog Manager
- Natural language Generator
- Text-to-Speech Synthesizer
Features of Conversational AI vs Chatbot Solutions
|S. No||Features/Capabilities||Conversational AI||Basic Chatbot|
|2||Natural Language Understanding||Advanced||Basic keyword recognition|
|3||Availability||24/7 Available||24/7 Available|
|5||Input Analysis||Keyword Focus||Machine Learning|
|7||Ready to use||Fast Deployment||Need Algorithm Training|
|9||Use case||Industry Based||Multi|
|10||Dialog State Management||√||no|
|11||Scalability||Limited capacity||Unlimited scalability|
|13||Self-improving||Self-improving over time||noSelf-improving over time|
|14||Data/System Integration||√||simple/limited integration|
|15||Interactions Type||Rule-based, linear interactions||Non-linear, dynamic interactions|
|16||Identity & Access Management||√||no|
|17||Channel||Single channel||Omni channel|
Chatbot vs Conversational AI Which is Better?
To some extent, chatbots can personalize discussions. They can address the user by name and even have a personality. Chatbots are highly good for sifting out leads and presenting relevant information to users in a small firm with a lot of repetitive inquiries.
To qualify leads, you don’t need conversational AI; you may just create a questioning flow on a chatbot without coding. Consider the case of a property manager who needs to screen rental applicants. In such a situation, it can create a chatbot that asks things like the prospect’s credit score, lifestyle choices, preferred location, and so on.
Conversational AI, on the other hand, must be integrated into your operations if your business requires a more tailored communication style. Conversational AI can help with a wide range of eCommerce tasks. “Where is the nearest fast food joint?” or “Which motels are suitable” are some questions you can ask a conversational AI bot.
Conversational AI can use NLP to answer all of these open-ended queries that a simple bot couldn’t. Because of their potential to have highly tailored, fluid dialogues with customers, manufacturers are engaged in conversational AI. Conversational AI is so close to human-to-human interaction that it’s difficult to distinguish if the user is speaking with a human or an AI.
What does conversational AI do that normal chatbot doesn’t?
- Learn at scale
- Personalize Reply
- Regular update
- Speak multiple languages
What are the case studies of conversational AI?
- Google Home
- Samsung Bixby
- AI Chatbots for 50+ banks worldwide
Advantages of Conversational AI and Chatbot
|Advantages of a chatbot||Advantages of a AI conversational|
|Faster to train||More Natural|
|Easy Integration||Can Speak Multiplace Languages|
|Accountable and secure||Decision-making skills|
|Text interactions||Understand patterns of behavior|
|Can include interactive elements and media||Create a conversational UI experience|
These two methods are not at odds, despite their appearance. Chatbots will continue to fulfill certain needs and jobs, despite the fact that conversational AI is clearly more advanced than chatbots. Conversational AI will continue to expand to become even more complex as machine learning, artificial intelligence, and natural language understanding continue to advance. What is obvious is that demand for these solutions will soar in the next decades, with consumers choosing to use chatbots for simple tasks and the majority of people wanting to use conversational AI virtual assistants to replace trips to their medical store or bank.
AutomationEdge is a leading provider of Conversational RPA, Conversational IT, and automation solutions that is helping organizations all across the world create smarter conversations and instant resolutions. Its Conversational AI and automation solutions not only give a boost to process efficiency but make your organization well equipped with AI capabilities to create a significant customer and employee experience.
There are 4 major types of chatbots.
1. Linguistic Based
2. Appointment scheduling
3. The hybrid model
4. Customer support chatbots
5. Keyword recognition-based chatbots
1. Appointment scheduling or Booking bots
2. Customer support chatbots
3. Marketing and sales chatbots
4. Entertainment bots
Conversational AI can be used for both text-based and speech-based interactions on the other hand the chatbot is most suitable for text-based dialogues. People may speak to programs, websites, and other technology in their own language with conversational AI. Eg is Alexa & Google Home
The popular example of conversational ai is Google home and Alexa.