We are frequently questioned about if there is a significant distinction between conversational AI and chatbots. Both of these phrases are frequently used synonymously, which is acceptable to some extent. Overall, though, their distinctions are glaring and considerably more significant in a professional situation. We need to strip away the stories surrounding chatbots and conversational AI in order to properly distinguish between the two.
What is a chatbot?
Software programmes known as chatbots are created to mimic human-like text exchanges with users. They interpret incoming inquiries using natural language processing and give appropriate answers. The majority of chatbots are rule-based, which essentially distinguishes them from conversational AI because they are trained to simply respond to a limited set of inquiries, primarily FAQs.
On the other hand, classic rule-based bots divert most discussions to a human agent since they lack the contextual knowledge. This defeats the main purpose of deploying a bot and adds to the load of unanswered questions on your human agents.
How kAIron’s conversational AI different from chatbot?
To make conventional bots smarter and more conversant with humans, conversational AI combines artificial intelligence, natural language processing, and machine learning. As you amass a larger corpus of user inputs, conversational AI agents get better over time at identifying trends and providing recommendations.
Businesses can now provide their customers with more personalised experiences by conducting more natural and intelligent conversations thanks to conversational AI. End-to-end user journeys can be transformed and automated with the aid of artificial intelligence thanks to its abilities to understand natural language, active learning, dialogue flow management, and data mining.
Conversational AI has five advantages over conventional chatbots.
1. Advanced natural language comprehension
Traditional chatbots are composed of logic rules and provide responses depending on pre-programmed or system-written keywords. Chatbots won’t respond to inquiries that fall outside the scope of their algorithm.
While natural language processing and response are the foundation of conversational AI. Multiple technologies, including machine learning, deep learning, and predictive analytics, are used to react to a query while yet providing a human touch. As a result, AI develops its own learning process and adapts its responses based on previous queries and searches.
2. Context maturity
A rule-based bot can only give the user so much information before running out of information. They won’t be able to respond appropriately to requests that haven’t been input into their systems, which can lead to a lot of consumer unhappiness.
On the other hand, conversational AI focuses on the customer’s past conversations, chats, questions, purchases, and history and bases its recommendations on those. The customer becomes even more content and devoted as a result of the contextual awareness. According to studies, 56 percent of consumers stick with companies who “understand them.”
3. Cognitive flexibility
There isn’t a universal solution to every problem. For instance, a consumer could want to know whether their product has been sent and how long it would take for it to arrive. The consumer will have to answer the question again because a rule-based bot can only respond to one of those. The customer can become irritated by this if they didn’t initially find the information they were seeking for.
On the other hand, conversational AI platforms can answer inquiries with several questions and change the subject of the conversation as needed. The user will likely be more satisfied because they won’t have to repeat their inquiry or question.
4. Compatibility, accuracy, scalability, and integration
Despite being economical, chatbots are dispersed and unconnected. They are individually integrated into a variety of systems; uniformity and scalability are largely absent. Efficiency is hampered by the requirement to restart the entire investigation after changing the platform.
Solutions utilising conversational AI offer quality consistency, scalability in terms of the number of queries it can handle, and integration with various social media platforms. Therefore, conversational AI makes it possible to have a widespread omnichannel presence. Customers enjoy a better overall product as a result.
5. The ability to speak assistance and several languages
Chatbots don’t have the same capabilities as conversational AI, such as voice assistance and language support. Users of these platforms are unable to provide voice commands or ask questions in any language other than the one that is registered with the system.
The best conversational AI technologies include Siri, Google Assistant, and Alexa. Voice mode makes it more simpler for users to communicate with one another and receive responses because they can understand commands issued in a variety of languages.
How do you begin with conversational AI?
It’s a frequent misperception that creating conversational AI solutions requires a lot of money and time. It may be true if you create a solution from scratch by working with expert developers, but it is not required.
You may create unique AI-powered bots by using the proper solution. There is no need to invest time and money hiring developers to create a solution from scratch. Without writing a single line of code, you can quickly design and deploy AI-powered chatbots tailored to your industry and use case utilizing next-generation conversational AI platforms like kAIron. Try it for yourself if you don’t trust me.
Schedule a demo and speak with us if you are seeking an AI chatbot. We can assist you in setting up and utilizing a conversational AI system to the fullest extent.