Conversational AI for Data Scientists: Tech Stack in 2022

June 16, 2022

Conversational artificial intelligence (AI) refers to innovative technologies like virtual agents and chatbots, which customers can talk to. They use machine learning, natural language processing and high volumes of data to help mimic human interactions, recognise the text as well as audio inputs and translate their meanings into a wide range of languages. 

Why Use Conversational AI in 2022?

Conversational AI plays an important role in human interactions with intelligent applications and machines from robots to mobile applications and smart home assistants. Enabling computers to understand several human languages and respond to them quickly in a human-like way has always been a dream of AI researchers. However, building such systems with NLP (natural language processing) capabilities was nearly impossible before the advent of modern artificial intelligence techniques that we use today. 

In the past few years, deep learning has made conversational AI a powerful technology and packed it with superhuman accuracy to perform certain tasks. Further, deep learning has eliminated the need for rule-based and linguistic techniques for constructing language services. This has resulted in the increased adoption of conversational AI in sectors like health, retail and finance. 

Believe it or not, the demand for state-of-the-art conversational AI tools is increasing day by day. 

Best Use Cases of Conversational AI 

Efficient and optimised conversational AI models can be used in industries like retail, healthcare and finance, for a range of applications like voice assistants and customer service lines. These high-quality conversational artificial intelligence models allow businesses across all sectors to provide a highly refined level of personalised services to their customers and improve their business-customer relationships. 

Given below are some of the use cases of conversational AI:

Retail

Chatbots are very common in the retail sector. They are used for analysing customer queries and generating accurate recommendations and responses. These tools help in streamlining the journey of customers and improve the efficiency of their business operations. Natural language processing is also used for analysing customer behaviour. 

Healthcare

The main challenge faced by the healthcare sector is to make medical facilities easily accessible to all people. Calling a doctor and having to wait is a common situation faced by patients. Also, connecting with doctors over call is a very lengthy process. The implementation of conversational AI tools like chatbots in healthcare to compensate for the shortage of healthcare professionals is an application of AI

Another application of this technology in the healthcare sector is in biomedical text mining. With the growing rate of biomedical publications and the huge volumes of biological literature, NLP is an important tool for extracting data within the publications for knowledge advancement in the biomedical field. 

Financial Services

NLP plays a very important role in building advanced conversational AI models and chatbots in the financial sector. One good example of the use of conversational AI in this sector is banks using NLP to determine the creditworthiness of clients without any credit history. 

Out of hundreds of language models used in NLP based applications, BERT tops the list for being the best NLP-based language model with the power of machine learning

Advantages of Conservational AI 

Cost-effectiveness is the very first advantage of conversational AI. There is no hidden fact that humans are expensive.Replacing human officials with chatbots will help in saving a huge chunk of the budget. Moreover, studies have shown that most customers are more comfortable chatting with a bot than conversing with a customer service executive. 

Conversational AI is far better than simple keyboard interactions in many cases such as when a person is driving or occupied with some other work. In situations like these, most people turn to voice assistants rather than interacting with keyboards. 

Conversational AI can do wonders when leveraged carefully. Looking at the increasing demand and efficiency of conversational AI, it is surely one of the best technologies for 2022. We have discussed everything you need to know about conversational AI, we hope it helps. 

References:

https://www.invoca.com/blog/ai-based-conversational-analytics-why-its-the-future-for-first-party-marketing-data

https://www.nvidia.com/en-us/glossary/data-science/conversational-ai/#:~:text=You%20use%20conversational%20AI%20when,with%20speech%20that%20sounds%20natural.

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Reference Links

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