To their credit, chatbots are making our lives more efficient and convenient in many ways. Most of us use chatbots to connect with our favorite brands, schedule a doctor’s appointment, check our account balance, raise a service request, and more. And, just like our friends show up when we need them, intelligent chatbots are just a call/click away – making them perhaps our new best friends. The latest AI chatbots process the data within human language to deliver highly personalized experiences, creating clear benefits for businesses and customers. Over the past few years, we’ve all encountered “Let’s chat! ” buttons on websites that promise a quick, helpful customer service experience.

Intelligent automation (IA) combines robotic process automation (RPA) with advanced technologies such as artificial intelligence (AI), analytics, optical character recognition (OCR), intelligent character recognition (ICR) and process mining to create end-to-end business processes that think, learn and adapt on their …

Chief Operating Officer, of Gupshup, Ravi Sundararajan, discusses why chatbots will become your new best friend. It’s a lot better to train the chatbot that will automatically identify and surface common questions from the conversation history. Further, it will recognize potential variations of those questions to make conversations seamless.

Solving for conversational customer challenges

Both types of chatbots have their advantages and disadvantages. Rule-based chatbots are less complicated to create but also less powerful and narrow in their scope of usage. The programmers then validate the responses, teaching the algorithm that it has performed well.


The chatbot must be powered to answer consistently to inputs that are semantically similar. For instance, an intelligent chatbot must provide the same answer to queries like ‘Where do you live’ and ‘where do you reside’. Though it looks straightforward, incorporating coherence into the model is more of a challenge.

Chatbots are getting smarter!

Software can write stories and poems, answer trivia questions, translate dozens of languages, and has even created computer programs. These projects typically have all but unlimited computing power and tap unlimited volumes of readily accessible data across the web. Ravi Sundararajan is the Chief Operating Officer at Gupshup, the leading conversational engagement platform. Sundararajan heads Product, Operations, Sales, Marketing, Business Development, and Support for Gupshup. Under his leadership, Gupshup has grown to become the leading Cloud Messaging Platform powering over nine billion messages monthly. Tens of thousands of large and small businesses across industry verticals use Gupshup to build conversational experiences across marketing, sales, and support.

We found that a positive share of voice improved promisingly when the turnaround time is on the lower side. It is an innate behaviour that getting a quick response from someone, be it brand or a person will increase your attention towards them and subsequently, thereby make them feel special. In the last several years, much advancement has been achieved toward more human-like conversational NLU paradigms. These advancements are largely due to the incorporation of Machine Learning algorithms in the Natural Language Understanding paradigms. However, the domains of influence are still quite narrow, making these systems brittle when the dialogue leaves the domains on which the NLU agent has been trained. HAL’s NLP parsing agent can easily isolate these two intents when each intent is given in a single input text expression.

The key to successful chatbots

By freeing users from mundane jobs, they’re free to focus on more high level duties. Doing so also reduces the possibility of human error, for example when filling out a work order. Understand the basics of NLP and how it can be used to create an NLP-based chatbot for your business.


To make rowhy chatbots are smarters learn new things on their own, engineers use a process called reinforcement learning. In reinforcement learning, a chatbot is given a task to complete. This reward can be in the form of a new piece of information or a new skill. The rewards are used to reinforce the behaviors that the chatbot needs to learn. Robotics and artificial intelligence are two of the most fascinating and fast-growing fields in computer science today.

The Future of AI in Client-Agency Relationships: A Path of Intelligent Collaboration?

They are also a great way to ensure that your company keeps up with the latest trends and technologies, so you don’t get left behind in this new era of customer service. They have the potential to improve customer service by providing fast access to information and support. With advancements in conversational AI, chatbots are getting more intelligent and human-like. Brands typically use chatbots across marketing, support, and commerce.

Python is usually preferred for this purpose due to its vast libraries for machine learning algorithms. The narrower the functions for an AI chatbot, the more likely it is to provide the relevant information to the visitor. One should also keep in mind to train the bots well to handle defamatory and abusive comments from visitors in a professional way.

Rule-based Chatbots

For this reason, it’s important to understand the capabilities of developers and the level of programming knowledge required. Integrating context into the chatbot is the first challenge to conquer. In integrating sensible responses, both the situational context as well as linguistic context must be integrated.

Are chatbots really intelligent?

Unawareness of context. Intelligent chatbots were created with the vision of simulating human conversations. Multiple chatbots attempt to interact like humans but fail miserably. One of the major causes for such a failure is that chatbots cannot understand or remember the context of a conversation.

Some chatbots offer the ability to use historical chatlogs and transcripts to create these intents, saving time. Those using machine learning can also automatically adjust and improve responses over time. Virtual assistants are a modified version of smart chatbots. It can also engage in small talk which is an added benefit of smart chatbots. While smart chatbots are trained to give the most relevant response with the help of an open domain resource, they learn best by collecting information in real-time.

  • Without being trained to meet specific intentions, generative systems fail to provide the diversity required to handle specific inputs.
  • They need to understand new and updated human language to keep up with a conversation and understand customer inquiries.
  • Freshworks Neo Leverage an end-to-end, scalable, and enterprise grade platform to unify and customize your experiences.
  • While many drag-and-drop chatbot platforms exist, to add extensive power and functionalities to your chatbot, coding languages experience is required.
  • The market will witness and experience its ups and downs but that shouldn’t stop businesses from creating a path-breaking innovation with chatbots.
  • The chatbot will not make any inferences from its previous interactions.