How do chatbots and AI chatbots work?

A chatbot is any software that simulates human communication, whether powered by classic, inflexible decision tree-style menu navigation or cutting-edge conversational AI. Chatbots are available in almost every communication channel, from phones to social media to particular apps and websites.

AI chatbots, on the other hand, are chatbots that leverage several AI technologies, such as machine learning to optimize responses over time, natural language understanding (NLU), and natural language processing (NLP) to effectively read user questions and match them to specific intentions. Deep learning skills enable AI chatbots to improve in accuracy over time, allowing humans to communicate with AI chatbots in a more natural, free-flowing manner without being misunderstood.

In this article, we discuss more about how chatbots and AI chatbots work. Read along!

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How do AI chatbots Work?

The first chatbots were essentially interactive FAQ programs that were built to respond to a restricted set of frequently asked questions with pre-written replies. They often required users to select from simple terms and phrases to carry the conversation ahead because they were unable to interpret natural language. Such primitive traditional chatbots are incapable of processing complex inquiries or answering basic ones that creators have not expected.

Chatbot algorithms evolved to be capable of sophisticated rules-based processing and even NLP, allowing customers to express themselves conversationally. This spawned a new kind of chatbot that is contextually aware and equipped with machine learning (ML) to continuously improve its ability to accurately understand and forecast requests as it is exposed to more and more human language.

Today, chatbots can be classified into two categories:

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Data-driven and predictive (conversational) chatbots

These chatbots, often known as virtual or digital assistants, are far more complex, interactive, and customized than task-oriented chatbots. These chatbots are contextually aware and use NLU, NLP, and ML to learn as they go. 

They utilize predictive intelligence and analytics to personalize content based on user profiles and previous user behavior. Over time, digital assistants can learn a user's preferences, provide recommendations, and even foresee needs. They can initiate talks in addition to analyzing data and intent. Consumer-oriented, driven by data, predictive chatbots such as Apple's Siri and Amazon's Alexa are examples.

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Task-oriented (declarative) chatbots

These are single-purpose systems that perform a single function. They provide automated yet conversational responses to user inquiries using rules, NLP, and very little ML. Interactions with these chatbots are highly detailed and structured, and they are best suited for support and service functions—imagine comprehensive, interactive FAQs. 

Task-oriented chatbots can answer routine questions, such as inquiries about business hours or basic transactions with few variables. Though they use NLP to provide end users with a conversational experience, their skills could be improved. These are the most popular chatbots right now.

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Wrapping Up

Advanced digital assistants can also integrate multiple single-purpose chatbots under one umbrella, pull dissimilar information from each of them, and then use this knowledge to execute a task while keeping context—so the chatbot does not become ‘confused.’

Moreover, choosing the appropriate chatbot platform, such as CronbotAI, can pay off big time for businesses and individuals. Users benefit from fast, round-the-clock assistance, while organizations can better meet expectations without incurring costly staff changes.

‍CronbotAI is a customizable chatbot that is both data-driven and task-oriented, which makes it easily adaptable and adapts to your business’s specific demands of your business. Not only that, but the customer relationship management (CRM) application provides real-time data that you can utilize to answer your prospects' questions and turn them into sales. This also increases consumer happiness, which strengthens the reputation of your brand. Sign up now for a free.