Chatbots vs. Conversational AI: What is the Difference?

What is Conversational Ai?

Conversational AI is an umbrella term used to describe technologies that can automatically understand and respond to voice-based or text-based human conversations.

They use a combination of technologies to provide these smarter experiences, including:

• Natural language processing (NLP): A subset of AI technology that can carry forward conversations in a natural way.
• Machine learning(ML): This technology remembers massive amounts of data in a short time, and at some point, it starts to recognise patterns to make better predictions.

While not all conversational AI systems are created equal, most of them feature a conversational interface that serves as a gateway for requesting various services. Those requests are either addressed with a simple question-and-answer format or associated with a complex conversation flow.

Some well-known examples of conversational AI systems include chatbots, virtual assistants, and voice AI systems.

What are Chatbots?

Chatbots are computer programs designed to automatically converse with users. Its name came from a combination of the words chat (a conversation) and robot.

While chatbots can come in various forms, currently they are either powered by rules-driven engines or artificial intelligent (AI) engines:

• Rules-based chatbots operate off predefined scripts where commonly asked questions are paired with specific answers. These chatbots then look for keywords in user input and respond with the corresponding information. This type of chatbot can't answer complex or unscripted questions.

• AI chatbots, on the other hand, use ML (machine learning) and NLP (natural language processing) to complete more complex tasks. The use of NLP technologies in these systems is for understanding user's language patterns, such as—intent, entity, and dialogue essence— and then automating a human-like response.

Added to that, machine learning algorithms give these chatbots the ability to learn from experiences—just like a person can. The more conversations these chatbots have, the better they become at resolving complex issues.

What is the Difference Between Chatbots and Conversational AI?

There is often confusion about the differences between chatbots and conversational AI. Keep in mind that while there is much overlap between the two—both can perform tasks automatically—there are still some critical distinctions. 

For the most part, conversational AI covers a broader area of AI technologies that use natural language processing (NLP), machine learning, and other AI techniques to understand user intent and communicate with people naturally.

One common use of conversational AI is chatbots. They usually appear like a chat widget on webpages or social media channels to interact with users. When a user interacts with these chatbot applications, the system learns and responds appropriately using databases and past user interactions.This, in turn, keeps users engaged and adds a personality to a company’s messages.

Instead of scrolling through endless help centre articles or waiting on hold to speak to an agent, users can instantly resolve their issue by self-serving themselves.

However, not all chatbots are powered by AI. Rule-based chatbots follow a flowchart created by human agents. These charts map out conversations, anticipate what users might ask, and program how the chatbot should respond.

In short, think of conversational AI as the main power behind most modern chatbots.

Future of AI : What Lies Ahead ?

Here are some key predictions on what the future might look like for AI:

Rise of Voice Bots

IVR (interactive voice response) has gotten a bad reputation over the years. Simply put, users are frustrated with the hassle of going through multiple steps to solve a problem.

But with the advancement of AI, a new tool has emerged known as VoiceBot, which makes it easy to navigate the IVR.

When you speak out loud into your phone or computer, the speech recognition, text-to-speech, and conversational AI technologies within the system immediately transform your voice into text, transcribe it for analysis, and identify your intent. They then personalise the experience according to your actions to provide better support.

AI Chatbots Could Become the Primary Channel for Support

AI chatbots can answer 80% of user queries without human intervention. This means businesses can serve users 24/7 while agents can focus on complex tasks.

Building on this efficiency, industry analysts predict that the use of AI chatbots in customer service will increase from 1.6% to one in every ten encounters by 2026. And the numbers make sense.

A traditional rule-based chatbot can only answer common support issues and route complex ones to your human agent. They are less adaptable when it comes to dynamic user behaviours or unique language patterns.

An AI chatbot, on the other hand, can resolve complex queries autonomously. This is due to their ability to learn and respond appropriately using databases and user responses recorded in the past.

For example, Mevrik offers next-generation AI chatbots that are trained on high-quality customer experience data. It can easily generate human-like conversations, create a personalised experience, and automate simple tasks. Plus, it supports 130+ languages in text and 70+ in voice, so you can support your user's  around the globe.

Finding the Balance Between Personalisation and Privacy

The more and more use of personal data for marketing strategies has raised concerns among users regarding data protection. Users believe that if there is a flaw in the system or a data breach, millions of people will have access to their personal information.

While personalisation is pivotal for any brand engagement, it is also important to put your users at ease. Thus, a balance between personalisation and privacy is critical for the success of your business.

To secure a balance between personalisation and privacy, here are some key strategies used by businesses:

• Transparency: Communicate the data policy clearly with users . Inform them about how you are going to use their personal data, why you are using it, and how you will protect it.
• Limited data collection: Collect only the information needed to deliver a personalised experience.
• Data control options: Give users the freedom to control their data. They can change cookie settings, opt out of data sharing, or have their data deleted.

Final Thoughts

Whether it is conversational AI or chatbots, there is one thing that is certain: every AI tool is designed to make humans more efficient.

And Mevrik is leading the way in this effort. With its AI-powered chatbot, you can maintain constant customer contact, cut costs, and deliver personalised support. Try it for free today.

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