At its core, conversational AI refers to the use of artificial intelligence (AI) to facilitate human-like interactions between machines and users, such as chatbots or virtual assistants. Powered by deep learning, these technologies use natural language processing (NLP) and machine learning (ML) to understand, interpret, and engage in interactions in a more natural, human-like way. By doing so, conversational AI enables computers to understand and respond to user inputs in a way that feels like they are in a conversation with another human.CX 

For contact centres, conversational AI can be used to optimise customer experiences. By enabling tools like chatbots, voicebots, and virtual assistants, organisations can provide self-service options, empowering customers to resolve issues on their own, at their own pace, and from anywhere. This shift not only enhances the customer experience but also streamlines operations, boosts agent efficiency, and improves the effectiveness of support efforts. 

Ultimately, conversational AI supports business growth by driving better customer engagement, increasing satisfaction, and optimising internal processes. Its ability to reduce operational costs and deliver faster, more personalised support makes it a valuable asset for modern contact centres. 

How does Conversational AI work?

Conversational AI relies on a combination of advanced technologies to process and respond to text or speech inputs in a way that feels natural and meaningful. For example, it might take a message from a customer in a chatbot conversation, understand what the customer is asking, and generate a helpful response. Here’s a breakdown of the key components behind conversational AI: 

• Natural Language Processing (NLP): Natural language processing is the component that helps machines understand human language. It analyses the structure of words and sentences, identifies the user’s intent, and even detects emotions or tone. By breaking down the input into manageable data, it allows the system to respond with relevant and accurate information.
  

• Machine Learning (ML): Machine learning is a branch of AI that uses algorithms and statistical models to identify patterns in data, enabling it to make predictions based on the data. ML enables conversational AI systems to get smarter over time. By studying past interactions, these systems learn patterns, adapt to customer preferences, and improve their responses to future queries.
  

• Speech Recognition (ASR – Automated Speech Recognition): For voice-based interactions, like those handled by voicebots, ASR converts spoken words into written text, enabling the conversational AI system to understand human voice inputs. This text is then analysed so the system can understand and respond to the customer’s query and simulate a human-like response. For this, it uses text-to-speech technology to allow the system to turn written responses into spoken words, creating natural and human-like voice replies. This makes interactions with voicebots and virtual assistants more engaging and accessible.
  

Thanks to Machine Learning, conversational AI systems can remember details from previous conversations, and continously learn. This means they can respond with better context and continuity, ensuring smoother and more personalised interactions. 

Together, these technologies work to deliver intelligent, responsive, and human-like experiences in customer service, whether through a chatbot on a website or a voicebot on a call. By implementing conversational AI, contact centres can create elevated customer support that improves customer experience, automates manual processes, and drive great business outcomes.  

What is the difference between Conversational AI and Generative AI?

As mentioned, conversational AI technologies are designed to generate responses based on a user’s intent and the context of the conversation. This brings us to generative AI, a term often used interchangeably but fundamentally different in purpose and functionality. So, what sets them apart? 

Generative AI refers to AI systems capable of creating entirely new content—whether it’s text, images, audio, video, or even code. These systems learn patterns from large datasets during training and use that knowledge to generate outputs based on user input. 

Conversational AI is a subset of generative AI specifically focused on enabling human-like conversations in real-time. Its core purpose is to understand, process, and generate meaningful dialogue, making it ideal for interactive communication with users. 

In short, generative AI is designed for creating new content, while conversational AI focuses on enabling interactive dialogue. For example, Generative AI powers tools like Midjourney for images and code generators, whereas conversational AI powers chatbots, voicebots, and customer support tools. 

Types of Conversational AI technologies

Conversational AI encompasses a range of tools and technologies that cater to different customer service needs. These tools play a crucial role in improving efficiency, enhancing customer experience, and streamlining operations in contact centres. Here’s a closer look at the key types of conversational AI: 

AI chatbots: 
AI-powered chatbots are text-based conversational agents designed to handle customer queries, assist with troubleshooting, and guide users through various processes like making purchases or finding information. These chatbots can be integrated into websites, messaging apps (such as WhatsApp or Facebook Messenger), and mobile apps, enabling customers to receive support anytime and from anywhere. For contact centres, AI chatbots manage routine tasks—such as order tracking, password resets, or checking account balances—freeing human agents to focus on more complex issues. For example, a chatbot can help customers navigate a return process on an e-commerce site, improving both efficiency and customer satisfaction. 

Related content: What is a chatbot? 

Voicebots: 
Voicebots allow customers to interact with businesses using spoken language, bringing an auditory dimension to conversational AI. These voice-driven solutions are particularly useful for automating call centre operations and providing hands-free, accessible support. Voicebots handle phone queries, such as scheduling appointments, updating account details, or processing payments. They’re an effective way to manage high call volumes and reduce wait times, ensuring customers can get quick responses without being put on hold. For contact centres, voicebots enhance both customer satisfaction and operational efficiency. 

Related content: What is a voicebot? 

Virtual Assistants: 
Virtual assistants, such as Alexa, Siri, or Google Assistant, are sophisticated conversational AI tools designed for both personal and business use. These tools manage a wide range of tasks, from setting reminders to answering complex queries, and even assisting employees with their workflows. In a business setting, virtual assistants can surface customer purchase histories, suggest resolutions, or automate post-call summaries for agents. Their ability to integrate with business systems helps streamline operations and enhance the efficiency of customer service teams. 

AI Copilots: 
AI copilots are emerging as a powerful tool in contact centres, acting as smart assistants for agents. These AI-driven tools provide real-time suggestions, assist in decision-making, and help agents resolve customer issues more quickly and accurately. By analysing customer data and interaction history, AI copilots offer relevant responses and guide agents through processes, improving productivity and reducing human error. AI copilots are becoming an essential part of the agent experience, empowering them to provide more personalised, efficient service. 

How contact centres benefit from conversational AI tools

Conversational AI is transforming contact centres by streamlining operations, cutting costs, and significantly improving customer experiences. With the help of tools like chatbots, voicebots, and virtual assistants, contact centres are able to offer quicker, more efficient service while freeing up human agents to focus on tasks that require a personal touch. Here's a deeper look at the ways conversational AI benefits contact centres: 

• Reduce workload for agents: One of the most immediate benefits of conversational AI is its ability to handle repetitive, time-consuming tasks. Chatbots and voicebots can respond to simple queries like checking account balances, tracking orders, or resetting passwords without any human intervention. This reduces the pressure on human agents, allowing them to dedicate their time to more complex or sensitive issues that require problem-solving or empathy—areas where human expertise truly makes a difference.
  

• Reduce response times: Conversational AI tools are designed to deliver instant responses, drastically reducing customer wait times and speeding up issue resolution. Whether it’s answering FAQs, providing product recommendations, or guiding customers through troubleshooting steps, AI systems can handle these tasks in real-time. By immediately addressing basic queries, AI ensures customers don’t have to wait for an agent to become available. This leads to faster issue resolution and a more seamless customer journey.
  

• Give 24/7 availability to customers: Unlike human agents who work on set schedules, conversational AI systems are available 24/7, providing round-the-clock support for customers regardless of time zones or peak hours. This constant availability ensures that customers can reach out for help anytime, which is especially valuable for businesses operating in global markets or those with high-volume service needs.
  

• Cost savings: By automating repetitive tasks and handling a high volume of customer interactions, conversational AI can help contact centres reduce the need for large customer service teams. With AI systems managing basic requests, businesses can lower their labour costs while still providing excellent customer service. This allows contact centres to allocate resources more effectively and invest in areas that require human expertise.
  

• Get data-driven insights: Virtual assistants and AI tools integrated with customer relationship management (CRM) systems can gather and analyse vast amounts of data from customer interactions. This data is invaluable for agents, helping them to provide tailored solutions and personalised service. By giving agents real-time access to customer histories, preferences, and previous interactions, conversational AI enables more informed decision-making. Agents can make better recommendations, resolve issues faster, and provide a higher level of service.
  

• Scalability: Conversational AI is designed to scale, meaning it can handle large volumes of customer interactions at once without compromising on quality. Whether it’s a sudden surge in demand due to a product launch or seasonal spikes in customer inquiries, AI tools can adapt to meet these needs. 

Conversational AI is transforming the way contact centres operate, providing a range of benefits that lead to more efficient operations, cost savings, and improved customer experiences. By reducing the workload on agents, delivering faster resolutions, offering 24/7 availability, and providing valuable data-driven insights, AI tools are enhancing the overall performance of contact centres. With the ability to scale easily and manage high volumes of interactions, conversational AI is an essential tool for businesses looking to stay competitive and meet the ever-growing demands of today’s customers. 

Examples of conversational AI use-cases

Many businesses in various industries are increasingly implementing conversational AI tools to improve customer service, optimise operational efficiency, and deliver more personalised experiences. By leveraging AI-powered chatbots, voicebots, and virtual assistants, organisations can handle customer inquiries more effectively, allowing human agents to focus on more complex tasks. Let’s look at some examples of how the technology can be used in different industries. 

Retail 
The retail industry is one of the most visible adopters of conversational AI. With customers increasingly seeking fast and convenient ways to interact with brands, conversational AI has become a key player in enhancing CX. AI-powered chatbots and voicebots allow retailers to offer 24/7 support, assist with order tracking, answer product queries, and even offer personalised shopping recommendations. 

Healthcare 
In healthcare, conversational AI has revolutionised patient interactions, making it easier for patients to book appointments, receive medical information, and even get reminders for prescriptions. Voicebots and chatbots in healthcare provide round-the-clock assistance, helping to streamline administrative processes and improve patient outcomes. 

Banking and finance 
The banking sector is another industry where conversational AI is making waves. AI tools like chatbots and virtual assistants enable financial institutions to offer real-time customer support for a wide range of services, including account management, loan applications, fraud detection, and general inquiries. With these AI solutions, banks can enhance the customer experience while ensuring a high level of security. 

Travel and hospitality 
In the travel and hospitality industry, conversational AI plays a crucial role in delivering seamless customer experiences. From helping customers book flights to providing real-time travel updates, conversational AI is streamlining many of the traditionally manual processes within the industry. Chatbots and voicebots can answer questions about availability, weather forecasts, booking modifications, and even provide personalised travel recommendations.