Artificial intelligence technology is developing rapidly, and today it is possible to create interactive virtual agents that may understand and respond to a wide range of queries. Conversational AI is what chatbots would like to be.
But business owners are wondering how they differ and which one is the right choice for your organizational model? We will discuss the rivalry chatbot vs. conversational AI to answer these questions.
The definition of chatbot and conversational AI
A chatbot or virtual assistant is a robot that understands human language and responds to it with voice or text. Hence the use of “chat” before “bot”. It is an essential distinction since not every bot is a bot (e.g., malicious bots, etc.). Chatbots may be straightforward question-and-answer type bots programmed to respond to given requests. A bot relies on natural language processing (NLP) technology which allows it to understand user requests and respond accordingly (but only if trained to do so).
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Conversational AI is a higher-level concept of a chatbot. It often combines artificial intelligence (AI) technology with other technologies (natural language processing, machine learning, identity management, secure integrations, workflows, dialogue state management, speech recognition, etc., cost of service).
The features of сonversational AI:
use of deep learning technology,
the ability for self-learning.
Conversational AI is used to distinguish basic rule-based chatbots from more advanced ones. Such distinction is especially true for companies that are more demanding in their desire to implement conversational AI solutions.
The differences between conversational AI and chatbot solutions
The similarity between chatbots and conversational AI is they are both conversational and can be used to interact with users (customers, employees, etc.) through conversational interfaces using the power of natural conversation. You may have text or voice conversations over various digital channels such as the web, mobile devices, messaging, SMS, email, or voice assistants.
To better compare chatbot vs. conversational AI, the experts decided to classify all their features according to several criteria. Let’s read about the main aspects.
The standard rule-based approach to chatbots requires 6 to 9 months of training. In addition, predetermined conversation flows often cause inadequate and unsatisfactory comprehension.
With conversational AI resources, the learning process is accelerated by unsupervised NLU, allowing applications to understand user input and generate much better responses. Through studies from previous interactions, the AI-driven chatbot gained the ability to provide multiple answers.
Ability to have complex conversations
Standard chatbots can’t understand multiple intents compared to conversational AI, which may use various commands in a single conversation. Thus, simple bots only solve simple queries. If the client asks questions containing two different aspects, the chatbot will answer the first one and ignore the second part of the request. After that, to solve another part of the request, the customer must repeat it separately so that the chatbot may understand it.
Conversational AI can switch between topics and give customers complex and precise answers within a single conversation. Moreover, with the help of AI, the application may perform several tasks, for example, reserve a table in a cafe and make a note on the calendar accordingly. The AI can view orders to see which ones have been canceled by the company and not yet returned and then provide information about that scenario.
Scalability and consistency
Unlike chatbots, which are not connected and scattered across different platforms, conversational AI is powered by various sources and functions as a single conversational stream. It means conversational AI handles smooth user interactions without having to create output by manually inserting it into the stream. With conversational AI, virtual or digital voice assistants can be integrated across the company and speak the same way. If users start a conversation through one and want to switch to another, the conversational AI will automatically complete the task.
Level of personalization
According to research by Deloitte, personalization is an essential driver of customer experience and business results. Based on the characteristics of the customer, the conversational agents adapt to their preferences and change the speed if necessary. If the conversational AI determines that a customer is unhappy, it may even bring in a sales manager to help resolve the issue. In the case of chatbots, it is impossible to personalize the conversation.
In addition, it is worth remembering the multilingual nature of conversational AI, in contrast to scripted bots, which cannot execute commands in different languages.
Let’s conclude the battle chatbot vs. conversational AI. With the increasing adoption of artificial intelligence, machine learning, and natural learning processing, conversational AI is becoming more popular. Such form of digital voice assistants, virtual assistants, and virtual call processing agents is predicted to grow exponentially. The global chatbot market is on the same wavelength, with 67% of customers using a bot for customer support. Conversational AI, built on chatbots, is an advanced solution for businesses that aim to solve complex problems and provide complex solutions to their many customers.