What is Conversational AI? Works, Benefits, and Challenges

  • Riya Kumari
  • Dec 09, 2020
  • Artificial Intelligence
  • Updated on: Mar 09, 2021
What is Conversational AI? Works, Benefits, and Challenges title banner

Our world is becoming more digital day by day and conversation AI is one such digital component that is being used for facilitating communication between humans and computers. Doesn't it seem fascinating, the ability to hold a conversation with machines? 

 

In our present scenario, this is done through our Android's Google Assistant or with our Apple's Siri. Whenever we talk to computers we wish for the experience to be similar to interacting with a human being. This is where the technology 'Conversational AI' surfaces. This enables chatbots to interact with us in a way humans do. 

 

 

Definition of conversational AI

 

"Ironically, a lot of people think that they’ve never used a chatbot, they’ve never experienced it, when in fact they have. Because Siri and Google and Alexa and all those voice-activated speaking bots, if you will, those are actually audio chatbots"- Kelly Noble Mirabella

 

Conversational AI is a set of technologies that makes communication easier between computers and human beings. Now, you must be thinking about how conversational AI can communicate like humans? This can be done by understanding language and text, clarifying several languages, and reacting in a manner that mimics human conversation. 

 

In the ideal context, this technology offers an outcome that is indistinct from what might have been conveyed by a human. Consider the last time that you spoke with a business and you might have finished similar assignments, with the equivalent if not less exertion, than you might have if it was with a human and that is Conversational AI at its greatest quality.

 

Hence, this technology depends on a mix of controls, with computer science, artificial intelligence, and linguistics used to empower natural language capacity among machines. Here are the following fields characterize the techniques and algorithms used in conversational AI-

 

  • Machine Learning-  Through machine learning, the AI determines the appropriate response on the basis of what it understands regarding the user’s intention. 

 

  • Natural Language Processing - The Conversational AI understands and engages in contextual dialogue through natural language processing (NLP) as well as additional AI algorithms.

 

Recommended blog: Top 10 Natural Processing Languages (NLP) Libraries with Python

 

  • Natural Language Understanding (NLU)-  This focuses on deciphering meaning in the words of the user, without regard for how it is stated, allowing the AI to comprehend the intention of the user even amidst grammatical errors or shortcuts.

 

  • Natural Language Generation (NLG)- Through natural language generation, a response is generated by AI in a format that is easily comprehended by the user.

 

You can imagine if your company has a smart assistant that can communicate with your customers, realize their necessities, and solve their problems according to them. This will help your business in enhancing and conversational AI can assist you in fulfilling this.

 

Related blog: Artificial Intelligence and Machine Learning: 5 Developing AI and ML Trends to Watch in 2021)


 

How does Conversational AI Work?

 

Now, let's move towards how conversational AI does its work. Have you ever thought about how a chatbot gives you an exact response to your question? Here, we will learn about the technologies which make conversational AI possible. Conversational AI understands and participates in a contextual speech by NLP and other AI algorithms.

 

To start with, the AI must comprehend what the client is attempting to say, or the aim of the client's inquiry. Natural language understanding or NLU attempts to translate importance in the client's words, paying little need to how it's expressed.

 

With complex NLU, the AI will have the option to comprehend the client's goal even among linguistic errors, and shortcuts, and recollect settings starting with one proclamation then onto the next, understanding what is being said all through the discussion.

 

Second, the AI must decide the correct reaction dependent on its comprehension of the client's purpose using machine learning. As the AI responds to client inquiries after some time, and as human specialists help to manage its information, it learns more varieties of similar goals and which reactions are the most proper for every purpose.

 

At long last, using natural language generation, the AI produces a reaction in an organization that is effectively perceived by the client.

 

 

Conversational AI Benefits

 

Conversational AI has shaped the way firms communicate with their customers and here, we will discuss in detail some benefits of conversational AI.

 

  • Cost efficiency

Staffing a customer service division can be very expensive, particularly as you look to respond to inquiries outside regular office hours. So, offering customers help using conversational interfaces can decrease business costs around compensations and preparation particularly for little or medium-sized organizations.

 

Chatbots and virtual assistants can react quickly, giving 24-hour accessibility to possible customers.

 

  • Scalability

The set of technologies is likewise very scalable as adding infrastructure to help conversational AI is less expensive and quicker than the recruiting and on-boarding measure for new representatives. This is particularly useful when items grow to new topographical business sectors or during surprising momentary spikes sought after, for example, during holiday seasons.

 


From cost efficiency, scalability, superior customer service, timely and agent efficiency, Conversational AI offers a range of benefits.

Benefits of Conversational AI


 

  • Timely

It is one of the tremendous benefits of conversational AI as due to this users get instant responses. For example, if we talk to Alexa it responds quickly or while the virtual assistant talking to a customer it can reply faster than human beings.

 

  • Superior customer service

Chatbots are always supposed to be the superstars of artificial intelligence for customer service. These chatbots help customers in solving their problems faster and accurately. Thus, they similarly perform as outstanding assistants to agents.

 

Recommended blog - Customer Behaviour Analytics

 

  • Agent efficiency

At times, conversational AI can assume control over customer assistance cases totally and dispense with the requirement for human mediation. This might be the situation for simple errands, for example, checking an account balance, or looking into the location of a retail store. When AI takes over, agents have all the more leisure time to spend on complex cases that really need their consideration.


 

Use cases of Conversational AI

 

Conversation AI is an extremely lucrative technology for enterprises, helping businesses more profitable and has a wide range of use cases. These include :

 

  • Online customer support:  Online chatbots have replaced human agents alongside the customer journey. They respond to frequently asked questions (FAQs) around topics like shipping or providing personalized advice, cross-selling products, or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms.

 

This includes messaging apps like Slack and Facebook Messenger, as well as tasks executed by virtual assistants and voice assistants.

 

  • Accessibility: This form of AI enables companies to be more accessible by cutting down entry barriers, specially for users who adopt assistive technologies which includes text-to-speech dictation and language translation.

 

  • HR processes: Various HR processes can be enhanced through conversational AI, which includes employee training, as well as updating of employee data.

 

  • Internet of things (IoT) devices: All households now have a couple of IoT devices such as Apple Siri or Amazon Alexa which adopt automated speech recognition for interacting with end-users.

 

 

Challenges in Conversational AI

 

Conversational artificial intelligence confronts challenges that expect better progressive technology to endure. Here, we will catch a glimpse of some of the challenges in conversational AI.

 

  1. Security and privacy

At the point when users demand a voice assistant, the information sent must be safely prepared and put away. Voice assistance and chatbots must be paid attention in organizations and the high-security norms that organizations characterize for these channels must be conveyed to their clients to make the vital premise of trust.

 

Particularly while performing sensitive individual data analytics that can be taken, Conversational AI applications must be planned with security in mind to guarantee that protection is regarded and all personal details are kept private or redacted dependent on the channel being utilized.

 

  1. Conversations in native languages

With only a limited section of the world population speaking English, it is a challenge for a voice assistant to converse in a language other than English.

 

As a result, the choice of chatting to a voice assistant in your mother language is critical to winning more people and building faith more skillfully. The languages of varied regions as well as cultural discrepancies are required to be considered.

 

  1. Discovery and adoption

Although Conversational AI applications are getting progressively simple to use and standardized for everybody, there are still difficulties that can be defeated to expand the number of individuals who are open to using technology for a more extensive variety of use cases.

 

So, instructing your user based on opportunities can enable the technology to be all the more generally welcomed and make a better experience for the individuals who are not friendly with it.

 

  1. Language input

Language input can be a difficult area for conversational AI, regardless of whether the input is text or voice. Dialects and background noises can affect the AI's comprehension of the raw input. Also, slang and unscripted language can create issues with handling the information.

 

Nevertheless, the greatest challenge for conversational AI is the human factor in language input. Feelings and sarcasm make it hard for conversational AI to understand properly and react appropriately.

 

Recommended blog -  Introduction to Text Analytics and Models in NLP

 

  1. Simultaneous conversations

We all know that most of us keep our smart speakers in our living room and most of us use voice assistance in our smartphones. So, in these situations, we can realize that in these places numerous people could probably have a discussion or deliver instructions. In this situation, the voice assistant might get confused.

 

Hence, it requires to be skilled to differentiate identical voices from each other and not distract user accounts, therefore revealing sensitive user information.
 

 

Conclusion

 

It can be said that conversational AI is affecting our lives whether we realize it or not. This technology has made our life easier by providing us with amazon Alexa, Siri, and voice assistant features. In 2019, we have seen a tremendous rise in the use of chatbots across the industrial area and there is a belief that in the coming days we will get to see much more success because of conversational AI.

 

"Although conversing with a bot is not the same as speaking with a human, messaging a friend is the closest analogous experience. Since users are still getting used to bots, it is reasonable to take those interactions as samples of how a bot should behave"- Szymon Rozga

 

Thus, the use of chatbots is not at all restricted to any field, so any business can enjoy this technology for the advancement of their company.

0%

Comments