12 Conversational AI Examples in Different Industries

Conversational AI is changing customer interactions. Today, more people use chatbots instead of waiting for a live agent to get quick, convenient, and round-the-clock support. 

In this blog post, we explore the best conversational AI examples across industries and explain how they streamline operations. 

What is Conversational AI?

Conversational AI uses natural language processing (NLP), machine learning, and dialogue management to mimic human-like interaction through text and voice channels. 

It recognizes the user intent and offers assistance in speech or text in multiple languages to deliver an empathic engagement. Furthermore, it works around the clock without human intervention and enables self-service customer support.

Types of Conversational AI

Here are some common types of conversational AI used by businesses:

1. AI-powered Chatbots 

One of the most popular uses of conversational AI is chatbots that stimulate human language with users and answer their queries, schedule appointments, raise support tickets, and connect to the correct department. 

Integrating AI tools into messaging platforms like WhatsApp or Facebook Messenger assists with real-time text-based communication for customer service. 

2. Voice Assistant 

Tools like Siri, Microsoft Cortana, Alexa, and Google Assistant are popular examples of conversational AI. These voice assistants interpret voice commands and provide information or perform tasks such as setting reminders, accessing information, and searching the web. 

Interactive voice assistants offer a hands-free and intuitive method to complete activities, enhancing user convenience.

3. Voice Bots

Voice bots are AI-powered contact center channels that allow users to use their voice to navigate an interactive voice response (IVR) system. The tool assists callers in resolving their queries when contact center agents are unavailable. 

The IVR guides callers through automated menus, provides resolution, and routes calls to appropriate agents when requested, thus improving efficiency.

4. Speech Analytics 

Speech analytics is a type of conversational AI that helps contact centers analyze customer interactions to identify trends, monitor agent performance, and ensure call compliance. It enables agents to analyze customer sentiment and service quality to optimize call strategies in real-time. 

12 Conversational AI Examples in Different Industries

Conversational AI is transforming customer service experiences across industries. Here are the top examples:

1. Self-Service Customer Support

Businesses can use conversational AI to help customers resolve issues without connecting with a human agent. This includes options like chatbots and voice assistants. 

Customer support automation can help customers follow steps to resolve issues, access information, and perform basic tasks like transactions or upgrading subscriptions.

For instance, a retail brand can integrate a chatbot on its app/website to help customers track orders or return it.

2. Customer Engagement Automation 

AI can also help personalize customer communications in their preferred language and tailor messages based on customer sentiment. It ensures seamless interactions across multiple channels, making customer engagement more meaningful. 

For instance, a hospitality company can use conversational AI to engage customers in their preferred language through their website, email, or messaging platforms or offer contextually relevant responses.

3. Personalized Marketing Campaigns 

With conversational AI, you can personalize marketing messages based on customer preferences and their actions on the website. 

For instance, an e-commerce website can use chatbots to offer personalized recommendations based on the pages the customer visits. It can also recommend similar products to customers when they’re shopping and help them make purchase decisions. 

4. HR Automation

An innovative example of conversational AI in the HR industry is the automation of tasks like interview scheduling, responding to employees, and screening candidates. 

For example, an HR manager can screen candidates, send emails, and schedule interviews, saving time and effort during the recruitment process. 

5. Scheduling Appointments

The AI allows customers to conveniently book, reschedule, or cancel an appointment without human intervention. A chatbot can help a customer find available appointment slots and guide them through the steps to confirm it. 

For example, healthcare providers allow patients to book appointments through voice assistance or chatbots. This helps patients find available doctors and times based on their preferred location and book the appointment. 

Exotel’s AI voice assistant is designed to revolutionize customer interactions. With its seamless integration and continuous learning, this voice assistant can easily handle a wide array of tasks. Book a Demo today to experience Exotel’s voice assistance. 

6. Intelligent Call Routing 

Another powerful example of conversational AI is routing, where AI analyzes the caller’s intent for inbound calls and directs the call to the right department or agent. 

For example, a customer may have specific requests for investment or retirement plans in financial services. For such complex issues, AI can identify the caller’s intent and forward the call to the agent with the right skill so the customer can get personalized financial advice. 

7. Lead Generation 

Conversational AI tools can be efficiently used for lead generation. They can engage with potential customers in real time, sparking their interest in the company or its offerings. By gathering insightful information during every interaction, it helps identify potential leads and qualify them for the sales team to follow up on, making the lead generation process more efficient. 

For example, a retail company can use the website chatbot to engage visitors, ask questions to understand their needs, converting the browser into a potential buyer. 

8. Agent Assistance & Training 

It offers real-time support to contact center agents during customer interactions, guiding them through complex conversations and delivering better service.

Analyzing customer interaction enables conversational AI systems to suggest responses, provide relevant information, and alert agents of any compliance issues. This allows both agents and supervisors to monitor performance and identify areas for improvement. 

For example, a financial service contact center can deploy agent assistance to guide agents through compliance protocols and provide responses to sensitive customer queries. 

9. Automated Customer Surveys 

AI tools like chatbots or smart IVRas also help you to automate customer data collection naturally and conversationally. This ensures that you follow up at the right time, increasing the response rate and gathering valuable customer feedback.

For example, a healthcare provider can use AI-powered IVR surveys to gather patient feedback post-treatment, ensuring meaningful insights to improve service quality. 

10. Virtual Assistance for Telemedicine 

A good example of conversational AI is making healthcare accessible through smart IVR and chatbots. These tools allow patients to receive virtual consultations from anywhere at their convenience. 

For example, a telemedicine platform can deploy AI-powered chatbots to guide patients through systems and connect them with appropriate doctors for virtual consultations, ensuring timely, convenient, and efficient care. 

11. Fraud Detection & Prevention

Conversational AI can monitor customer interactions and automate calls or messages to verify users using OTP. It helps flag suspicious activities, identify potential fraud, and take immediate action. 

For example, a retail brand can use AI to monitor transactions and unusual purchase patterns. If the brand detects a bulk order from a new location for an old customer, the system can trigger an OTP via SMS to confirm the customer’s identity. 

12. Customer Onboarding

One example of conversational AI is the customer onboarding process, where AI can guide new users through the necessary steps and provide real-time support on its usability. This can reduce user drop-offs and ensure a smooth onboarding experience. 

For example, a banking service can use AI chatbots to assist new customers in setting up their accounts. The bots can also help users identify and learn useful features and enhance their experience. 

You can optimize your contact center operations with AI-powered communication platforms like Exotel. It offers solutions that help you route inquiries, engage customers across channels, and offer uninterrupted customer service.

You can book a demo today to design personalized and interactive experiences for your customers using Exotel. 

Benefits of Implementing Conversational AI in Contact Centers

Conversational AI technology enables businesses to enhance customer experience, streamline operations, personalize support, and increase accessibility. Here are some of its benefits:

» Omnichannel Communication: Conversational AI integrates across multiple channels, providing consistent customer support. It offers the contact center reps a unified and contextual view of every interaction, allowing them to provide a cohesive journey across various channels. 

» Round-the-Clock Accessibility: Contact centers worldwide use AI technology to provide 24/7 support. This boosts customer satisfaction by instantly addressing their requests and queries anytime.  

» Faster Resolution: The tools identify and promptly resolve pain points, reducing customers’ need to interact with agents and improving customer satisfaction. Additionally, resolving common queries allows human agents to focus on complex issues. 

» Lower Agent Burnout: Streamlining routine tasks and queries lightens the workload for contact center agents, preventing burnout and improving job satisfaction. Agents can concentrate on value-adding tasks.

» Self-Service Customer Support: Conversational AI empowers customers to resolve issues without human intervention. AI-driven self-service tools save the customer’s time and effort otherwise spent on connecting with a live agent. 

» Scalability: AI technology can seamlessly scale with your business, efficiently handling increasing volumes of customer interactions without additional staffing or exhaustion. This ensures that your contact center remains responsive to growing demands. 

Conversational AI Examples: Key Takeaways 

Conversational AI is a game-changer for businesses, offering many advantages in customer interactions and operational efficiency. Unlike human agents, it can operate around-the-clock scale contact center operations without compromising quality and efficiency. 

As AI technology evolves, it will understand user intent more precisely, and its response accuracy will also evolve. With the advancement, it will become more sophisticated, offering more capabilities for personalization and meaningful customer conversations. 

If you want to utilize AI’s potential, Exotel’s AI Voice Assistance provides a seamless way to engage customers and deliver efficient, multilingual support. Book a demo today to experience how Exotel can transform your customer experience strategy. 

FAQs

1. What are the Use Cases of Conversational AI?

Conversational AI is used in areas like contact center service, sales, marketing, and e-commerce.

2. What are the Components of Conversational AI?

The four main components of conversational AI are machine learning, natural language processing, data mining, and speech recognition. These components work together to interpret inputs and offer human-like interactions.

3. What Is the Difference Between Chatbot & Conversational AI?

A chatbot can handle specific tasks or answer predefined questions using simple, recorded scripts. Conversational AI, on the other hand, enables more complex, human-like interactions using NLP, machine learning, speech recognition and data mining to respond in a more contextual manner. 

4. How Does Generative AI Differ From Conversational AI?

Generative AI creates new content based on the data it has been trained on, like GPT. On the other hand, conversational AI applications stimulate conversation using user input and dialogue management.