Why Use Conversational AI? What Are The Benefits?

Lakshmi Prakash
Design and Development
5 min readMay 28, 2022

Conversational AI is seen everywhere these days. It’s suddenly on the rise for a few years now, leaving people questioning why they should use conversational AI in their businesses or projects or events. You don’t *have to* use conversational AI, but if you don’t, others still will, and that is going to leave you behind. Conversational artificial intelligence is more useful than you might think, so without further ado, let’s get down to discussing the benefits that conversational AI can bring.

Conversational AI — What Is It?

CAI or Conversational AI uses Natural Language Understanding (NLU) to understand users’ needs and in return provide users with what they want. Some of the most commonly used and successful examples would be Google Search, chatbots you see on websites, virtual assistants you can talk to, etc. And that’s not all; conversational AI is used in a wide range of sectors, helping people in a variety of cases, say for example, helping practitioners in medicine, helping you keep track of your lifestyle and fitness, helping you in making shopping much more easier for you on e-commerce, assisting you with making well-informed decisions in investments, and more.

According to IBM, “they (conversational AI technologies) They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and text inputs and translating their meanings across various languages.”

Why Use Conversational AI? — The Benefits of Conversational AI

Conversational AI lifts a lot of weight off the shoulders of human agents. It helps human agents focus on more important issues that certainly require human intervention so that the boring, easy, yet highly demanding tasks can be taken care of by the AI for you.

Conversational AI saves costs in many different ways. While the goal is not to completely replace human agents or customer support staff with AI, conversational AI, being AI, can be of help to your users or customers 24*7, answer queries and troubleshoot, offer updates, and even raise tickets for you in the absence of human assistants.

Intelligent Conversational AI can understand users’ emotions and needs. While a website or SMS or recorded voice message may convey some information but not understand users’ needs and feelings, and a human agent, being human, can understand a user’s needs and feelings but not have all the answers, an intelligent virtual assistant would be able to satisfy the user in different ways. Conversational AI achieves this by using sentiment analysis to “understand” the user.

Conversational AI can be highly user-centric. Conversational AI is trained to offer users exactly what they want and share only information that they want. Other information, even the ads we see, can be tailored to match users’ interests. Using Natural Language Processing (NLP), it is not at all difficult for an intelligent digital conversational agent to understand a users’ needs. This is achieved by combining input analysis and users’ history. Plus, a well-trained AI can easily solve several problems at one go as well.

Also, conversational AI is now frequently used in applications of Internet of Things such as Siri, Alexa, and such.

Training conversational AI is a lot easier than training human agents. Let’s be honest here. Think of programming. While coding itself can be time consuming, once you have the program, executing it will be extremely easy, but training a human to understand all that can still be more difficult. Imagine having to train several tens or hundreds or thousands of human agents like that every year. Next, imagine a conversational AI being trained, deployed, and managed by a small team.

High Speed, obviously. This one is evident. I can communicate with a conversational AI in the middle of the night, and ask, if I pick a plan, decide to invest Rs. 30,000 every quarter, then how much can I expect to get after 6 years? I could contact conversational AI and ask, if I start from my current location now, given the current traffic and weather conditions, when can I expect to arrive at the destination, and whether I would be late. When we ask a human agent such questions, they themselves have to rely on computers to give us the information we want. When it comes to speed, as we all know, a computer will always beat a human being easily.

You can give your conversational AI a Personality of your choice! Now, you can not only chooses avatars and DPs but also design personalities for bots; how cool is that? To the outside world, you are defined mostly by how you behave and communicate. Are you shy, or friendly, or funny, or geeky? What do you want to be the chief qualities in your agent? You want it to only provide necessary information? Or do you want it to share predictions and perspectives along with the data? Or do you want the agent to also be skilled in chit chat as well? Or is empathy the top-most quality you seek? A bot can easily be trained to have a “personality”. Well, “easily” doesn’t mean exactly that, but let’s leave that to the researchers!

Your Conversational AI can think along with you. While you get to drive the conversation, for angles you’re interested in, your virtual agent can assist you, providing more information and help you make informed decisions.

With these many benefits, you should be convinced that conversational AI is highly scalable and quite efficient. And it’s not just getting a product and activating it on your channel or platform. The product can be continuously improvised as users’ needs and expectations change with time and technology also keeps moving forward with more advancements.

You can see that most websites these days have chatbots, most of the renowned banks use virtual agents, and even some of your favourite apps come with conversational AI.

From graphical user interfaces (GUIs), supposedly one of the earliest forms of interactive technology online, we have come this far in technology. Yes, there are several challenges involved in the process of making a machine understand human language. For example, one of the key challenges would be getting names (and other uncommon proper nouns) right. Another problem would be translation, as you can imagine. But with ambitious scientists and researchers working behind the scenes, developments continue to happen.

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Lakshmi Prakash
Design and Development

A conversation designer and writer interested in technology, mental health, gender equality, behavioral sciences, and more.