Serving your customer with conversational AI can enhance overall business communication and automate customer support interactions with tailored and dynamic responses that suit individual user queries.

These conversational AI can provide 24/7 customer assistance and consistency of work quality during high inquiry volume, and they have a higher scalability capacity than traditional ones with suitable dynamic responses.

This guide covers comprehensive information on what is conversational AI and how it works with its benefits, practical use case, and best contact center solution with conversational AI capabilities.

🔑 Key Highlight
  • Conversational AI (CAI) uses machine learning (ML) and natural language processing (NLP) to simulate natural conversation with humans.
  • Compared to traditional chatbots, CAI offers dynamic and varied responses due to its understanding of context and intent.
  • Generative AI can generate completely new content, including different formats of text, audio, video, code, and tables according to the user input.

What is conversational AI?

What is conversational AI

Conversational Artificial Intelligence (AI) is an AI technology that offers the user an interactive and conversational user interface like an AI chatbot, voice assistant, or virtual agents that use machine learning(ML), extensive data, and Natural language processing(NLP) tech to understand and provide different variations of the response in as conversation and engaging model according to the given queries or data the users.

Compared to traditional chatbots, conversational AI can understand human language very accurately and provide dynamic and varied responses based on the topic and context of the given data. These responses are helpful for users to engage in human-like conversation responses since they also use Natural language Understanding(NLU) technology.

Difference between Conversational AI and Generative AI

Features Conversational AI Generative AI
Goals Facilitate natural and interactive communication between humans and machines. Generate new content, including text, code, images, or audio.
Technology Natural Language Processing (NLP), Machine Learning (ML) Machine Learning (ML), Deep Learning, Large language model
Function Understand user intent, respond to questions, manage dialogue flow. Generate creative and original content based on learned patterns.
Application Chatbots, virtual assistants, customer service automation. Art, design, content, code generation, music composition, creative writing
Focus Understand and respond to human communication or conversation Creating new, dynamic, and innovative content.
Creativity level Limited creativity if it relies on pre-programmed responses or learned patterns. High potential for creativity, can produce original, dynamic, and unforeseen content.
Training data Large datasets of conversations and dialogues. Large datasets of existing content (text, code, images, audio) depending on the specific case.
Scalability Scales well for handling large volumes of user interactions Depends on the complexity of the content being generated.

How does conversational AI work?

Conversational AI combines a few principles of technology:

  • ML, aka Machine learning, is a type of technology that collects information from its interactions with past user input data and gives a response to learn and grow further.
  • NPL, aka Natural Language Processing, is artificial intelligence technology that can understand and respond to human language

NLP has two sub-components: Natural Language Understanding, which tries to make sense of input text or data to understand user intent, and Natural Language Generation (NLG), which generates appropriate responses to satisfy user queries and intent and converts them into a human-understanding format such as text or natural languages.

Essentially, this is how an AI agent would work: text input is fed into the conversational AI software, and then the NLP deciphers the user’s intent and generates an appropriate response. 

As time passes, machine learning automatically improves the quality of the responses and delivers more accurately, with self-learning capabilities that include past conversational data history for future interactions.

What are the benefits of conversational AI

Benefits of conversational AI

There are several benefits of AI-powered chatbots or conversational AI for businesses and users:

1. Scalability and availability:

Conversational AI systems can work 24/7 to deliver instant responses and support to users anytime. This is especially helpful when you have globally distributed customers and support teams. Businesses and professionals no longer need staff available around the clock to respond to customers and offer instant real-time support at all times. 

Also, Conversational AI and AI-powered chatbots can handle a high volume of concurrent interactions, ensuring scalability and sustainability without compromising the quality of customer service.

2. Enhance Customer Experience: 

Instant response, providing customers without waiting for interactions, and delayed response can help solve their issues in real time and will obviously enhance customer experience. With the help of virtual assistant AI, businesses can even provide predetermined scripts and present personalized conversations with clients. This also helps companies retain customers and improve customer loyalty toward their brand.

3. Cost reduction of operational and scalability: 

Implementing Conversational AI can help in contact center optimization and reduce business costs on operation-related expenses, where they can optimize the customer support service and manage live agents in the real supportive task, giving organizations leverage to scale business and cut unnecessary money and time expenses while operating by doing repetitive task with human support.

4. Data-driven insight in real-time: 

With the help of CRM integration and tracking platforms, these AI chatbots can generate accurate data promptly in real-time, giving insight into customer behavior and interaction, agent performance, customer experience, and user satisfaction.

5. Improve agent performance: 

Customer support representatives can improve their performance through report generation from conversational AI and data, helping team leaders identify and provide the necessary training or knowledge resources to upgrade employee’s individual performance and weaknesses.

Practical case of conversational AI

Online customer support: Online chatbots can replace human agents along the customer journey without errors. They can automatically answer frequently asked questions (FAQs) about shipping, provide personalized advice, cross-sell products, or make various user suggestions, dynamically improving customer engagement across websites and social media platforms with an omnichannel presence.

Health care: AI-powered chatbots and Conversational AI can facilitate healthcare services that are instantly accessible and affordable for patients during medical emergencies, improve operational efficiency, and streamline administrative processes simultaneously, such as medical claim processing.

Virtual Voice Agent and Internet of Things (IoT): These virtual chatbots can also facilitate users with conversational AI to understand their voice commands with speech recognition for interaction with the various user ends or devices for 

Playing recommended music, providing weather updates, controlling smart devices at home such as AC, Washing machine, and lights, and more with the interpretation of voice commands, allowing users to perform specific functions without making physical actions such as pressing multiple buttons.

Examples of virtual voice assistants or agents are Amazon Echo, Apple’s Siri, and Google Voice.

Embrace conversational AI in your contact center with Dialaxy.

Conversational AI is a powerful application of modern technology that is shaping contact centers and business customer support operations in an effective way while minimizing customer support and operational costs at the same time. 

But this doesn’t mean there is no need for human agents. Businesses need human agents to solve and understand complex issues along with conversational AI, where AI lacks an advanced human approach that can resonate with and comply with another human.

With Dialaxy’s dedicated cloud-contact center solution features like virtual numbers, sentiment analysis, automating tasks, Interactive Voice Response (IVR), intelligent call routing, predictive analysis, and performance monitoring, contact centers and businesses can optimize their customer service to provide better customer support experience, identify new opportunities, improve agent performance, make data-driven decisions, and streamline business operations.

Try our 7-day free trial to experience the complete cloud communication solution and optimize your customer support service with enhanced customer experience.

FAQs

What is the difference between Conversational AI and Chatbots?

Chatbots interact and respond to user input based on predefined answers and programmed rules. 

Conversational AI does not depend on predefined criteria but offers a dynamic and advanced approach through machine learning (ML), Natural language processing (NPL), and large language models (LLM).

What are the drawbacks of conversational AI?

Some of the drawbacks of the conversational AI are:

  • Dependent on the data
  • Struggle to understand the context sometimes
  • Lack of empathy and understanding of emotion in conversation

How can businesses or contact centers use conversational AI?

Business and contact centers can use conversational AI to improve customer experience, streamline operations, and gain valuable customer insight.

For example: AI can help in the call center or contact center business by automating simple and repetitive tasks, providing virtual assistance and chatbot support for the customer with 24/7 availability, and handling high inquiry volume traffic during peak hours by providing effective self-service options.

Is ChatGPT a conversational AI?

Yes, ChatGPT is a conversational AI model that uses natural language processing (NLP) to create human-like conversations. It is an AI chatbot developed by OpenAI that can respond to questions and generate text responses based on user input or queries.

What is the difference between conversational AI and generative AI?

The major difference between conversational AI and generative AI:

  • Conversational AI focuses on human conversations.
  • Generative AI focuses on creating content in various forms.

Prasanta Raut

Prasanta is the founder and visionary CEO of Dialaxy. He is on a mission to redefine the landscape of SaaS solutions, infusing creativity and ingenuity into every aspect of Dialaxy’s offerings. His fervent dedication to simplifying sales and support processes drives Dialaxy’s forward momentum, delivering unparalleled value to businesses of all sizes. Embark on a transformative journey with Prasanta and Dialaxy as they pave the way for a new era of sales and support excellence.

Prasanta is the founder and visionary CEO of Dialaxy. He is on a mission to redefine the landscape of SaaS solutions, infusing creativity and ingenuity into every aspect of Dialaxy’s offerings. His fervent dedication to simplifying sales and support processes drives Dialaxy’s forward momentum, delivering unparalleled value to businesses of all sizes. Embark on a transformative journey with Prasanta and Dialaxy as they pave the way for a new era of sales and support excellence.