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10 Use Cases of Conversational AI for Customer Service in 2024

In today’s competitive market, exceptional customer service is a must for success. Traditionally, a customer service representative has been the primary point of contact to resolve customer issues. However, the increasing volume of inquiries is a complication for businesses to maintain quality support. 

The solution to this problem lies in adopting conversational AI for customer service activities, enabling organizations to streamline interactions while preserving the personalized experience customers desire. In fact, according to Deloitte’s survey, ~75% of companies are planning to invest in high-tech automation such as contact center AI and process automation in their customer service operations (See Figure 1).

Figure 1. The share of emerging technologies that are planned to be invested in by contact center leaders

Source: Deloitte Global Contact Center Survey

In this article, we explain the top 10 use cases and benefits of conversational AI for customer service.

How is conversational AI used in customer service?

Conversational AI is a machine learning technology that enables computers to understand and communicate with humans using natural language. It is used in customer service departments to provide quick and efficient assistance through different types of tools like voice bots, chatbots, and smart assistants.

Voice bots

Voice bots are like virtual agents that can talk to customers over the phone or through smart speakers. They understand what customers say and can answer questions or perform tasks for them, such as providing information or helping with a service.

Voice bots use the speech-to-text technology for processing the customer input. Then, with natural language processing (NLP) abilities, the AI classifies the customer intent for generating a targeted response. Finally, by using text-to-speech technology, the textual response generated by AI is delivered as vocal output.


These are text-based virtual agents that customers can interact with through messaging apps, websites, or social media. They understand what customers type and can respond to their questions, guide them through a process, or help them find the right product or service.

According to Gartner, by 2027, chatbots will become the number one customer service channel for 25% of businesses.1 


Zoho SalesIQ is amongst domain-specific platform with its specifically tailored services in customer engagement. SalesIQ offers wide-scale of services in customer interaction. Some of them are:

  • Businesses can proactively launch chats on error pages to deliver support on demand.
  • Businesses can build bots according to their needs with a codeless process.
  • Businesses can set work hours for their support team to help customers, and the chat widget will only appear within this specified period.
  • SalesIQ Offers prepared answer templates to accelerate the process.
  • Zoho SalesIQ provides business the details on their browser or device configurations, actions on your the websites, and chat history. (Figure 2)
  • Real-time translation in customer interaction.
Figure 2. Source: Zoho SalesIQ 2

Smart assistants

These are advanced virtual agents that can communicate with customers through both voice and text, depending on their preferences. They can be integrated into different devices like smartphones, smart speakers, or wearables and help customers with a wide range of solutions, from answering their questions to managing their calendars.


Salesforce is the CRM market leader and Salesforce Contact Genie enables multi-channel live chat supported by AI-driven assistants. Salesforce Contact Center enables workflow automation for many branches of the CRM and especially for customer service operations by leveraging conversational AI technologies.

What are the use cases of conversational AI for customer service?

1- Accessibility services

Conversational AI can be used to make customer support more inclusive and accessible to individuals with disabilities or special needs. By offering tailored assistance and adaptive solutions, businesses can ensure that they cater to a diverse customer base and provide a more equitable experience. 

Some examples of using conversational AI for accessibility services can be:

  • Text-based support for hearing-impaired customers
  • Voice-based support for visually impaired customers
  • Easy-to-understand language for cognitively impaired customers

2- Account management

Conversational AI can be an efficient tool for customer account management. With the application of AI-powered chatbots or virtual assistants, it can assist customers with various account-related tasks, streamlining the process, and providing a more efficient and user-friendly experience.

Some account management applications of conversational AI can be:

  • Account creation
  • Password resets
  • Account updates
  • Account linking and integration
  • Account deletion or deactivation

3- Answering FAQs

Conversational AI can be used in customer service for answering FAQs. It allows businesses to handle common customer queries quickly and efficiently, providing accurate and consistent responses. This application can help free up human support agents to focus on more complex issues, leading to an overall improvement in customer service experience.

4- Authenticating customers

Another use case of conversational AI in customer service is for customer authentication. It can help verify the identity of customers by asking a series of security questions or requesting specific information that only the account holder would know. This process ensures that sensitive customer data or actions are only accessible to authorized users and maintains a high level of security in customer interactions.

5- Booking and reservation assistance

Conversational AI can be used in customer service for booking and reservation assistance. It can help customers find available options for flights, hotels, restaurants, or events based on their preferences and requirements. The AI system can also guide customers through the booking process, helping them complete the necessary steps, and provide confirmation details once the reservation is made.

6- Intent detection

One of the most important uses of conversational AI in customer service is intent detection. Conversational AI tools can analyze customer queries or statements to understand their underlying purpose or goal.

By accurately identifying the customer’s intent, the AI system can provide relevant responses, guide the user toward the appropriate information or solution, or route the inquiry to the right human agent or department.

7- Multilingual support

As it has the capability of understanding various languages, conversational AI can be used in customer service for multilingual support. It can communicate with customers in various languages, enabling businesses to cater to a diverse and global customer base.

By understanding and responding to customer queries in their preferred language, conversational AI ensures a more seamless and personalized support experience.

8- Order tracking and updates

Conversational AI can be leveraged in customer service for order tracking and order updates. It can provide customers with real-time information on the status of their orders, such as the current location, estimated delivery date, and any possible delays. 

Additionally, the AI system can send proactive notifications to customers regarding any changes in their order status, ensuring they are kept informed throughout the entire process. This application enhances the customer experience by offering timely, accurate, and convenient access to order information.

9- Payment management

Conversational AI can assist customers in managing their payments, such as:

  • Setting up automatic payments
  • Changing their payment method
  • Resolving billing-related issues 

Additionally, conversational AI can help customers understand their bills or invoices and provide guidance on how to make payments or resolve any discrepancies.

10- Troubleshooting

Conversational AI can help customers diagnose and resolve common issues they may encounter with a product or service. By asking targeted questions and analyzing customer responses, conversational AI can guide users through basic troubleshooting steps, provide helpful tips and suggestions, or escalate more complex issues to human support agents. By doing so, it improves the customer journey.

Why should companies use conversational AI for customer service?

There are several reasons why companies should consider using conversational AI for customer service:

  1. Improved customer experience: Conversational AI can provide quick, accurate, and personalized support to customers, enhancing customer satisfaction. 80% of business executives report that the implementation of AI technologies increased customer satisfaction.
  2. Increased efficiency: Companies can handle a large volume of inquiries and tasks simultaneously with the help of conversational AI, freeing up customer service agents to focus on more complex issues and improving response times.
  3. Reduced costs: Companies can reduce customer service costs by automating routine tasks, such as answering frequently asked questions, and reducing the need for additional support staff.
  4. 24/7 availability: Conversational AI can provide support to customers around the clock, ensuring that inquiries are addressed in a timely and efficient manner, regardless of the time of day.
  5. Scalability: Businesses can easily scale up or down the conversational AI based on the volume of customer inquiries, ensuring that support resources can be adjusted to meet demand.
  6. Consistency: Conversational AI can provide consistent responses to customer inquiries, ensuring that customers receive accurate and reliable information every time.
  7. Data insights: Companies can generate valuable data insights on customer behavior and preferences through conversational AI, allowing companies to improve their products, services, and customer support strategies.

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Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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