Artificial Intelligence Chatbots Will Get More Done By Doing Less

Just a few years ago, having conversations with artificial intelligence chatbots was only a part of our favourite sci-fi movie series. Today, that is transforming into reality. With Natural Language Processing and Machine Learning algorithms, we are getting close to a point where it will be hard to tell if we’re talking to a robot or a human.

Having said that, businesses know that their customers appreciate it more when they know that they are talking to a bot. No matter how personalised or engaging the conversations are, it is always better to set the right expectation. Customers must be aware at all stages of the conversation that a chatbot is meeting their needs and demands.

At the same time, customers don’t usually complain that they want to talk a real person unless absolutely required. They like the way chatbots promptly and efficiently respond to their queries no matter what time it is.

But what has made this whole conversational journey possible? What is the scope of conversational AI in the future?

Let’s discuss this in detail.

What is Artificial Intelligence?

Photo by Franck V. on Unsplash

If you haven’t already heard of this term, let me quickly tell you what it is. Artificial intelligence, also known as machine intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by human beings.

Computers mimic cognitive functions that humans associate with the human mind.

Chatbots use AI features like NLP and Machine Learning which makes them more intelligent. But keep it in mind that not all chatbots use AI.

AI and chatbots

Artificial Intelligent chatbots come with the ability to fix a goal and then achieve it in an autonomous manner. We can say that it is easier said than done.

This is because identifying the goal for a specific situation is a hurdle in itself to cross. The chatbot, depending upon how you train it, adheres to a specified process for realizing the goal.

It is the step-by-step training cycle that helps define the intelligence of a chatbot. An AI chatbot goes through this cycle to make progress towards pre-defined goals autonomously and ensure successful customer interactions.

Thinking ability of a chatbot

In simple terms, artificial intelligence chatbots must think what to do when a user puts forward a request.

The chatbot must convert information received from a user into an understandable format and then store it in a knowledge base.

An AI chatbot makes a decision by leveraging pre-existing knowledge. In fact, it acquires this continuously without any stopping.

Based on this decision, the chatbot takes action to achieve pre-defined goals.

It also uses neural networks in machine learning to think and take actions depending on the request placed by the user.

The knowledge base influences the learning capability of the chatbot from its past conversations with users.

Take the case of Siri and Google. Their intelligence is due to the knowledge stored internally and practice over time. This knowledge base helps in learning faster, identifying relevant information and providing a response that is relevant to the user.

The information that the chatbot gathers helps it to decide on the relevant action. Taking decision is more about what the chatbot has to reply to a user’s request. In this, predictive analytics using machine learning can make the AI chatbot plan ahead and respond to queries that would come from the user. This makes the chatbot smarter and more intelligent.

Sensing ability of a chatbot

For an AI chatbot, it is important for it to understand the nature of a customer query and process it in a way for getting the information required to perform a task.

The chatbot finds it easy to listen to what the user says verbatim. Otherwise, to make sense of what is being conveyed by the user and interpret it becomes a bit of a task.

Take the case of a robot that you want to build. It is, no doubt, a challenge to infuse sensing power into the robot.

There is a dire need to integrate the robot with most modern sensors otherwise it might not be able to respond in an appropriate manner.

Quick to act

As the thought cycle gets over, the chatbot knows the action it has to take to respond to a user. Once done, the chatbot is then supposed to act.

The chatbot must type out the reply to a specific query raised by the user. Typing out a sentence is relatively easy for a chatbot when compared to responding via its audio or video capabilities.

For audio or a video chatbot, responding to the user through a suitable action becomes difficult.

This is because, in a way, it has to sound like a human. However, with the progressive nature of technology we will definitely get to that level sooner or later.

Components of AI and chatbots

1. Chatbot with AI powers makes your bot capable and intelligent to answer complex queries. The interaction, therefore, is engaging, conversational, and lively.

2. Chatbot learns from every conversation it has with your customers. It goes through the previous interaction to improve the current response and prepare for the future. This activity helps to improve the efficiency of bot response. Moreover, it helps to understand your customer’s choices and preferences.

3. Smart interactions save customer’s time by helping them find the right information and address their queries in the most appropriate manner.

Quick tip: Always train your chatbot with sufficient data. This will help them strike meaningful conversations with your customers and new users. This will also make the conversation look more natural than robotic.

Artificial intelligence has more to serve us as a technology. And chatbot is one of the aspects under it. A chatbot without AI is just a FAQ answering bot.

In this generation of smart buyers, we need to use smart tools to meet their level of expectancy. We, at Engati, as a chatbot development platform, are looking forward to what more AI chatbot technology has to unfold.

How does Artificial Intelligence learn?

Ever wondered how AI learns? AI learns with the help of the massive amount of data it collects over time.

Machine learning now involves neural networks. Neural networks mimic the neurons in the human brain.

The algorithms fed in large amounts provide information, including inputs and outputs.

Here, inputs refer to the customer questions and outputs are the responses sent by the AI. When a complex query arises, the AI is able to learn from the agent’s interactions with it.

Over time, the AI can give even more accurate answers that require less human attention.

AI in chatbots performs similar functions, making chatbots analyze results to respond to cleverly and learn easily from its user interactions.

How is Artificial Intelligence making the best chatbots today?

First, let’s get this cleared. All chatbots don’t use AI. There are mainly two types of chatbots- Rule-based chatbots and AI/keyword-based chatbots.

Rule-based chatbots are provided with a list of set answers for common questions. They are not intelligent, capable of learning nor able to formulate answers on their own.

AI chatbots use NLP, which is a subset of AI and allows chatbots to understand, learn and analyze the context of the user inputs. These chatbots perform a variety of functions and aren’t just confined to the customer service sector.

With proper implementation of AI, you can build, integrate and deploy a bot hassle-free. By incorporating AI and Live Chat, businesses will be able to combine human intellect with machine intelligence for better customer satisfaction.

How have AI chatbots made work easier than ever before?

Artificial Intelligence is still a relatively new addition to the business world. But it’s only going to continue and evolve its presence over time.

With the use of Artificial Intelligence in chatbots, it has become really easy to automate tasks, in turn reducing the need for hiring, engaging, nurturing and paying several employees. But that doesn’t mean chatbots can replace human intervention. .

When the chatbot is well-fed with the right data, it can analyze results way faster than a human can, with very fewer chances of errors. And even when the errors happen, you can always train the bot and it will never repeat it again.

Since chatbot learns easily, you don’t need to spend much time in training. And retraining is done only once in a while when required. Thanks to AI, chatbots can even learn on its own depending on its collective user experiences.

The building, integrating and deploying a bot as well has gotten really easy. Gone are the days when you had to build, code, figure out a way to integrate and deploy a bot right from scratch and have several mental breakdowns in the process.

With competent chatbot platforms popping out of everywhere, building, using and integrating chatbots today comes handy!

AI chatbots for user convenience

There are two ways in which we design AI chatbots to understand the user’s requirements.

One is with a limited set of guidelines and internal structuring. We apply these two in a way that helps the artificial intelligence chatbot to respond.

We do this when we pre-ordain the set of user interactions or questions with keywords and map them to relevant responses. This mechanism needs no real-time responses from the interactive agent. We call such AI bots — Limited Chatbots.

An example would be the Automated Banking Bot that asks the caller a set of questions to know what they want. If the caller gives a command that is out of scope, then the AI bot would either repeat the instruction. Otherwise, it would transfer the call to a real human, i.e., a banking executive.

Two is how an AI chatbot interacts by knowing what a user is looking for. This leads to producing real-time responses based on progressive conversations or increased learning.

This mechanism is still evolving due to its complexity. Meanwhile, certain applications like Amazon’s Alexa, Google Assistant, WeChat, and Facebook artificial intelligence chatbots are on the pathway towards dynamic responses.

This possibly based on human behavioral and preferential traits. Self-learning is what helps these entities understand the human mind and gain appropriate information efficiently. Therefore, this helps chatbots to produce convincing responses. These AI chatbots are, hence, called Intelligent Chatbots.

Building Your Own Chatbot

While all these chatbots seem advanced, they’re relatively simple to build using chatbot tools, such as Engati. The build-your-own chatbot platform provides 100+ ready-to-use chatbot templates for different industries and functions. This ranges from Healthcare, Education, and Automobile to Travel, White Label and more.

Further, easy integrations are available on WhatsApp, Messenger, Kik, Website, and many other well-established platforms.


If you have a constant need to interact with leads and customers, and you find yourself struggling to satisfy that need, an AI chatbot might be exactly what you need.

They find the most efficient solutions and perform them perfectly, collect and analyze data while chatting and develop a personality that aligns with your branding.

They can boost your productivity and fit into most parts of the marketing funnel. Thus, integrating artificial intelligence chabots can lessen your work and make your life easy.

Visit our youtube channel to see how Engati makes the chatbot building experience easy for you!

If you want to build artificial intelligence chatbots, click on this link and get started with Engati.

Originally published at on January 1, 2020.




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