Chatbot Development, Chatbot News

The Evolution of Bots: From Simple Tool to Intelligent Assistant Strengthening our Capabilities

Bots have come a long way in making our life easier in many ways and ensuring the interaction with the machine is evolved, interesting, and contextual. With accelerated digital transformation and changed consumer behavior, we will only see faster adoption of both the automation and conversation bots in times to come.

By Manish Goyal
January 22, 2021

We have always been intrigued by our relationship with machines. Inquisitiveness and curiosity have led to various inventions in every aspect of our life. It was during World War II when Alan Turing, a well-known British mathematician, and cryptographer, talked about the ability of machines to think and interact. Since then, we have come a long way in understanding and interacting with machines and making them intelligent.

Software bots

One such interactive and innovative solution, which has become the mainstay of human interaction with machines, is the development of a software bot. The software bot, also known as a chatbot or digital worker, has made tremendous progress in recent times. From being a simple tool, which is an information pusher, to having the ability to understand and infer the meaning of conversations, bots have evolved tremendously in the last few years.

Automation bots and intelligent automation bots

Software bots are used in many ways within an enterprise environment. When deployed as a digital worker, they automate repetitive tasks, known as robotic process automation (RPA), and are done using automation bots. These automation bots augment the enterprise productivity by automating highly repetitive and routine tasks, like simple jobs of filling out the forms, copying and pasting information, scraping data from the web, making simple calculations (financial/sales), opening and moving files, etc.

Similar bots can be made more intelligent by using artificial intelligence technologies, such as machine learning, computer vision, and natural language processing (NLP). All of these processes enable automation of even complex tasks by understanding any type of unstructured data from any type of document, extracting the data, classifying the information, and bringing empowerment in decision-making.

Intelligent bots learn more as more data is ingested into their system, thereby increasing the accuracy levels.
Both automation and intelligent bots are used by enterprises to bring in productivity and efficiency gains.


When the bots enable two-way communication, the software bots are called chatbots. Businesses use these chatbots to automate their communication with the internal customer (employees within an enterprise) or external customer (outside customer). These chatbots also have varying degrees of complexity—from being simple rule-based bots where the user inputs must confer to the predefined rules to get a response, to complex bots that can understand the intent of the user.

Simple chatbots

The conversation when using simple chatbots is restrictive and within a periphery. There is no intelligence, and open conversations are not enabled. Simple bots are mostly menu-based bots, which can be used to help users navigate a website or inform users about products, services, features, or general facts. These bots, when deployed internally within an organization, can be helpful in employee onboarding, streamlining HR support, directory services, taxation and leave details, and many more. Any website can use simple chatbots to answer menu-based questions. Other simple bots are keyword-based bots, which are able to identify the word/phrase and then pull out queries and respond accordingly.

AI-based intelligent bots

But, as we make the chatbots intelligent by using artificial intelligence, a whole new world of interaction with the machines opens and enables enterprises to leverage various digital spaces where these bots reside. The intelligent bots use AI-based NLP to understand and infer from the input and give an answer to questions being asked. The NLP bots learn as conversations happen, which enables them to make connections from the trove of data, interpret it, and give the best reply as suitable. Some of the most commonly used AI bot development platforms include IBM Watson, Google Dialogflow, Amazon Lex, BotMan, Microsoft Bot Framework, etc.

These AI-based conversational bots are not only capable of understanding a customer’s intent but are also able to understand the sentiment and behavior of the user—no matter how the question is phrased. They can fill out forms, make recommendations, upsell, book appointments, and even integrate with third-party or backend software, like automation bots (referred to earlier), enterprise resource planning, or customer relationship management systems, to carry out further tasks.

Some deployments of intelligent bots

Intelligent bots are used for employee engagement, which could range from providing answers to various policy questions to hearing their grievances and predicting the attrition of employees.

Intelligent bots are used by various banks, enabling them to not only handle relevant conversations with the customer but also ensuring real-time transactions—unleashing the true power of AI bots.

AI-powered chatbots are also deployed by call centers to make human-like voice interaction and to make inbound and outbound calls of various natures, which is not only cost-effective but also acts as a bridge between human agents.

AI-powered bots, when deployed by retailers, have helped them in ensuring omnichannel presence across various digital platforms (such as WhatsApp, Facebook, and websites), deliver a personalized experience, provide 24/7 support, book orders, cross-sell and upsell, and provide exceptional customer satisfaction.

AI bots, when deployed by the hospitality industry (such as hotels, hotel aggregators, and airline aggregators), help in reservations, cancellations, and refunds—a big relief and help to the customer care agents.


Bots have come a long way in making our life easier in many ways and ensuring the interaction with the machine is evolved, interesting, and contextual. With accelerated digital transformation and changing consumer behavior, we will only see faster adoption of both the automation and conversation bots in times to come.