What is conversational AI?

Introduction to conversational AI

Conversational AI has revolutionized how customers engage with brands. Early attempts to deploy this technology have resulted in robotic experiences. However, a new generation of conversational AI-driven voice assistants lets customers communicate naturally, much like they would with a human, enhancing conversational flows.

As conversational AI technology advances, it’s easy to get caught up in the complexities of the technology required and how to apply it in a contact center setting, which is why very few companies have the confidence to deploy AI in customer service conversations.

Read on as we explain conversational AI, its use cases, how it works, and the main benefits it can offer your business.

What is conversational AI?

Conversational AI is a set of technologies that use artificial intelligence to allow people to communicate with machines. Some common use cases of conversational AI include customer support, appointment scheduling, and order tracking. It powers systems like AI chatbots, AI-driven virtual assistants, apps, and smart assistants like Amazon Alexa, which can hold conversations, answer questions, solve problems, and perform tasks based on user input.

Unlike traditional automated systems, like touch-tone and keyword-driven IVRs, which often rely on pre-defined menus and responses, conversational AI can understand the context and handle a variety of inputs, including voice and text.

How does conversational AI work?

Until recently, automating voice transactions has been nearly impossible for companies because people don’t speak the way they type, people have different accents and speech patterns, and voice lacks a graphical interface. Deep learning and advanced AI models now allow systems to understand these variations, improving accuracy and response times and ultimately streamlining business workflows.

For human-to-human conversations to be effective, both people must listen, understand, and respond. The same idea applies to human-machine interaction, but instead of relying on brain power, it depends on various technical components to function. Here are the most common parts of the conversational AI tech stack.

• Automatic speech recognition (ASR): Converts spoken language into text for large language models. Custom ASR enhances accuracy, leading to smoother customer interactions and reduced frustration.
• Natural language understanding (NLU): NLU is the process that allows technology to understand human language. It’s especially important in voice interactions, where people may not use exact keywords or might speak in longer, more detailed ways to express their point.
• Large language models (LLMs): These machine learning models can extract meaning from words and sentences by analyzing large datasets and defining the next steps the system should take in the context of the conversation.
• Dialog management: Acts as a control layer that sits on top of LLMs to enable your company to have full control over transactional processes. It allows systems to remember past interactions and context for appropriate responses to create smooth and productive user interactions with AI.
• For example, if a user asks, “What’s the weather in New York?” and then says, “What about tomorrow?” the system knows “tomorrow” refers to the weather in New York.
• Speech synthesis: Text-to-speech (TTS) models transform text transcriptions into spoken utterances. Traditional TTS has delivered robotic-sounding voices, but a new generation of TTS can leverage voice cloning and intonation training to deliver a more natural experience.

The difference between conversational AI and generative AI

Conversational AI and generative AI serve different purposes. Conversational AI focuses on understanding what users say, maintaining context, and responding appropriately. Generative AI creates new content—like text, images, or code—based on patterns it has learned, such as writing detailed responses or generating creative content from prompts.

The two can combine to create more advanced interactions. Conversational AI manages the flow of the conversation, while generative AI steps in to produce more flexible or detailed responses when needed to extend the duration and complexity of interactions it can handle.

7 benefits of conversational AI

While AI implementation has become a popular strategic goal to address contact center challenges like rising call volumes, high agent turnover, and increasing training costs, successful real-world applications in customer service are still thin on the ground.

A new generation of conversational AI solutions, like voice assistants, offers a solution to several by empowering businesses to automate customer inquiries and provide a seamless customer experience. These solutions allow customers to interact naturally, just as they would with a live agent, helping them resolve issues efficiently and at scale.

1. Elevate your customer experience

As consumers, we’ve grown used to the instant gratification provided by digital experiences. So, when your customers pick up the phone, they expect immediate help. Instead, they often face long wait times and pre-recorded messages telling them to go online instead.

According to HubSpot research, 33% of customers get frustrated by long hold times, and another 33% by having to repeat their issue to different support reps. Add hold music to the mix, and the experience gets even worse.

Voice assistants powered by conversational AI can improve your entire contact center program and customer satisfaction by allowing customers to access support anytime and solve issues as quickly as possible.

2. Upskill and redeploy your agents

Your agent’s time is best spent on high-value, revenue-generating calls that offer true value to your customers. The repetitive nature of an agent’s role is the reason some organizations experience attrition of up to 100% annually. That’s not necessarily replacing 100% of agents, but the bottom 25% of agents 4 times.

When a voice assistant handles low-value calls, including out-of-hours calls, your agents get a better work-life balance and time back to handle more complex, high-value calls with care.

By letting callers speak however they like and providing helpful responses at every step of the conversation, voice assistants can build trust and keep customers engaged when answering FAQs.

3. Get your operational costs under control

The time your customer support teams spend on low-value calls (such as password resets, order tracking, or FAQs) varies, but PolyAI clients have reported that 30-60% of agent time is spent answering queries that could easily be resolved online or through other, cheaper channels.

Automating the low-value part of a call, like customer password resets, ID&V, or simple FAQs, can streamline processes and drive down AHTs by 20-30%, giving additional capacity to your call center without sacrificing customer service. This enables effective self-service options for customers, allowing them to resolve their issues without needing to speak to an agent.

4. Turn your contact center into a revenue generator

Every phone call that is missed in your contact center has the potential to be a missed revenue opportunity. When a voice assistant handles your low-value calls, your agents have the time to focus on high-value and often revenue-generating calls.

With the ability to take reservations, schedule appointments, collect payment information, and complete outstanding payments, voice assistants not only optimize processes, but actively generate revenue for your business

5. Understand what your customers need with better insights

For a voice assistant to understand what a caller wants, answer common questions, and route calls to the right department, every spoken word has to be transcribed into text and processed by machine learning models. This process allows voice assistants to automatically convert unstructured speech into structured data, like 40% of support calls are related to billing issues, or 15% of appointments made on weekends are for repeat customers.

With structured, real-time customer data, including insights from sentiment analysis, you can identify friction in the customer journey, highlight trending topics, and enhance your service offerings to better serve your customers and drive more revenue, not just from the contact center but across your entire organization.

6. Communicate better with your customers in any language

Language barriers shouldn’t prevent your customers from getting the support they need. Many companies turn to cheaper options like outsourced BPO contact centers, but language differences can still cause frustration.

Customers should be able to explain their issues in their own words, whether that includes regional slang, non-technical language, or personal stories. Effective AI-powered multilingual voice assistants can understand and respond to both spoken and written queries in multiple languages, unlike traditional single-language bots. This makes customer support more inclusive and accessible.

7. Offer the same great customer service regardless of scale

Effective voice assistants have been proven to handle the workload equivalent to between 50-95 full-time agents, optimizing customer support workflows and offering scalability in your contact center without the hiring and training costs of new agents.

Elevating your customer experience with PolyAI

Implementing conversational AI in your contact center is an essential step to staying competitive and delivering effortless customer experience at scale.

PolyAI offers the world’s most lifelike voice assistants for enterprise customer service and delivers high-quality, human-like conversations optimized for customer engagement at scale. We help enterprises be the best versions of themselves in every customer call by consistently delivering the best brand experience, achieving accurate resolution, and uncovering data-driven business opportunities.

With advantages spanning operational efficiency, proactive issue resolution, and revenue generation, the implementation of this technology is a crucial step toward optimizing contact center performance.

Join our monthly live demo to find out more about how PolyAI can help you answer every call immediately, improve loyalty, resolve over 50% of calls, and deliver effortless CX at scale.

Expect to learn more about:

• The ROI of voice AI
• The best way to design voice experiences for customer engagement
• How other companies have successfully deployed voice AI
• How to begin your voice AI journey

Register now