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Posted on Jul 01, 2020
byNitin Bhosekar (Head Analytics, Artificial Intelligence, BI Practice & Executive Vice President)

Rise of Chatbots

Over the last couple of years, chatbots have been finding numerous use cases in various industry verticals including banking non-banking finance, healthcare, manufacturing, retail, e-commerce and insurance. This is no surprise, as chatbot technology is beginning to mature and offer more sophisticated areas of business applications.

Chatbot is a software program that uses artificial intelligence (AI) to have a conversation with humans. Users can ask questions, raise requests and respond to questions from chatbot using natural language. Chatbots offer a conversational experience using AI and natural language processing (NLP) to mimic conversations with users. The terms chatbot & virtual assistant could sometimes get used interchangeably.

As chatbots modernize and streamline communication between users and services that organizations provide, they aid in enhancing customer experience. This helps organizations explore opportunities to improve the customers’ engagement and enhance operational efficiencies owing to reduced time and cost needed to service their customers.

Chatbots come in varying levels of intelligence that range from answering questions to having the more wide-ranging capabilities of a skilled & knowledgeable employee.

A right level of intelligence embedded within a chatbot would need to be picked depending on the use case and the chatbot needs to be architected accordingly

A chatbot may be as rudimentary in functionality as providing basic pattern matching with a response looking for key phrases & presenting pre-de?ned responses. In this simple form it could be used as an FAQ (Frequently Asked Questions) automation agent. Or it may have a sophisticated interlacing of artificial intelligence & machine learning functionalities and integration with several existing organization specific services. Such sophisticated chatbots mimic different functions of the human brain including -

  • Understanding language (capability to ‘Read’ and parse human language/ text, which is a pre-requisite for understanding natural sentences
  • Comprehending that some text refers to entities e.g. ‘July 9’ equals to date or ‘Electronic Health Record’ equals to an entity/ means EHR. This is required for more complex usage and analysis.
  • Deriving context and intent recognition (capability to ‘Guess’ what the user could be asking for. This is required to enable natural conversation and to reduce user frustration)
  • Ability to accept user made corrections over usage time to improve aptness of responses. Permits the chatbot to improve and self-learn from user inputs.

At Aress, we have been working on architecting/ designing, developing & deploying chatbots thereby keeping pace with the rise & evolution of chatbots. Aress has a strong team possessing AI engineering capabilities, AI solution architecture and UX/UI design expertise that could help in successful chatbot development and deployments.

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About Nitin Bhosekar

Head Analytics, Artificial Intelligence, BI Practice & Executive Vice President

Nitin Bhosekar heads our Analytics, Big Data, BI and DW practice and is the company’s Executive Vice-President as well. Nitin has built a career on gaining business insight from data. He is a hands-on leader in business intelligence, big data & analytics with over 25 plus years of international experience.


Category: Data Analytics, RPA & AI

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