What is conversational AI? Your guide to smart customer communication

Conversational AI lets users chat with virtual agents or chatbots, using large volumes of data and advanced technologies to imitate human interactions.

Picture the last time you needed help from a company. Not just a quick question about store hours, but something a bit trickier, like understanding a bill or asking about a delayed package. For years, these moments often led to a digital dead end. You'd type your question into a chat window, and a basic chatbot would pop up with a list of simple choices, asking you to press one for returns or two for something else.

It felt less like a conversation and more like a never-ending maze. The technology wasn't talking, only following a rigid script, leaving many customers feeling unheard and unseen. Companies got stuck between managing teams that couldn't always keep up with growing demands, or using simplistic programs that often missed the mark.

The buying environment today is complex, with win rates decreasing by 15% and sales cycles growing by 32%, indicating buyers dislike the current process. But with conversational AI, companies are revolutionizing how customers interact with support teams. It’s making customer service feel less like a chore and more like a helpful chat with someone who gets it.

What is conversational AI?

This form of artificial intelligence is a smart software designed to have human-like communication. Think of it as a very skilled language expert, one that can read, write, and understand what people mean, not just the words they use. This is a huge leap from older chatbots that only understood simple commands or a few keywords.

How does it learn this? It’s like a child learning a language. Conversational AI uses natural language processing (NLP), an intelligence that lets computers understand human language. It has four main components you should know.

1. Natural language understanding (NLU): This is the AI's ear. It doesn't just hear words. It figures out the intent behind them. If you say, "my internet is down," it understands that you mean you have a service problem and need help with it, not that you're just stating a fact. NLU can even pick up on your feelings, like if you sound happy, confused, allowing the intelligence to understand the why behind a customer’s comment.

2. Natural language generation (NLG): This is the AI's voice. Once NLU helps it understand, NLG helps it create a response that sounds natural, just like how a person would sound. It can put words together in sentences that make sense, explain things clearly, and even adjust its tone to match a customer’s mood or brand's voice.

3. Dialog management: Dialog management helps store the conversation within one single interaction. This allows the AI to guide the conversation, ask clarifying questions, and refer back to earlier points, making the interaction feel connected and logical. So, when you type, "I need to return this shirt," conversational AI doesn't just look for "return" and "shirt." It understands your intent is to initiate a return process. It might then ask, "Which shirt are you returning?" and remember your answer for the next step.

4. Large language models (LLMs): The ability to mimic human conversation is powered by LLMs. Think of them as the AI's brain filled with an immense amount of data. They allow the AI to learn patterns, grammar, and even common ways people express thoughts and emotions. They’re how the AI can predict the next most helpful and human-like word or phrase in a conversation. Gladly Customer AI, for instance, uses advanced AI models to understand nuances and respond contextually.

How conversational AI talks to humans

Old chatbots had a set path and if you wandered off it they'd get lost and confused. Modern conversational AI, on the other hand, is much more flexible, specifically built to handle the nonlinear human interactions.

This upgrade of natural conversation makes a big difference. Almost three-fourths of customers interviewed reported feeling seen by brands , up 39%, from the year before. When the AI truly gets you, even in a text chat, it creates a feeling of being understood. A recent study found that 89% of customers believe that blending human connection with AI creates better experiences, so long as the AI is meeting their needs.

How conversational AI makes customer service better

Here are some tangible benefits of having a customer service system that can truly talk, both to customers and businesses.

1. Always on, always ready to chat

One of the biggest advantages is having twenty-four hour support.

Continuous service: Customers can get answers any time of day or night. This is a huge deal, especially for global companies or those with customers in different time zones. No more waiting for business hours to get help. According to one report, 75% of customers expect immediate service when they reach out online.

2. Scaling up conversations

As a business grows, so do the number of customer questions. Balancing a growing customer base with the same amount of teams can be challenging. Conversational AI offers major cost savings, creating a way to handle a large number of conversations with existing agents. This helps businesses save money on several operational costs.

The ability to manage high volumes of chats comes especially handy during holidays or special sales periods. More conversations mean happier customers.

3. Freeing agents for the tough stuff

Conversational AI helps agents focus on what they do best–complex problem-solving, showing empathy, and building real relationships.

Customer questions are often common, asking about an order or a return policy. Conversational AI can answer these instantly, freeing up agents to focus on unique situations that need human intervention. Additionally, when a customer does need a human, this technology can even provide the agent with a summary of the whole conversation. It acts like a co-pilot, suggesting answers, finding helpful articles from the knowledge base, and even suggesting replies that match the customer’s mood and tone.

We make every interaction smoother for the customer by removing all the annoying parts from a conversation. Companies using conversational AI often see a boost in customer satisfaction scores (CSAT). For instance, some Gladly customers have seen a 65% increase in CSAT.

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The challenges of conversational AI

While conversational AI is a game-changer, it's not without its challenges. Well-informed CX leaders are usually cautious of championing one single technology as a magic bullet. For conversational AI to perform at maximum capacity, some considerations need careful attention.

Hallucinations

One major challenge is the potential for hallucinations. This is when AI makes up information that sounds convincing, but isn't true. In a conversational setting, a hallucination could mean giving a customer the wrong product details or an incorrect policy. Your brand will need strong guardrails and human oversight, like periodic quality checks, to ensure the AI shares correct information.

Complex or emotional conversations

Conversational AI can sometimes struggle with highly complex situations. It might be able to detect frustration, but it lacks human judgment and creative problem-solving.

Quality assurance

Maintaining the quality and relevance of the AI's brain is an ongoing task. It needs fresh, accurate information about product policies and customer needs to provide relevant help.

And why it is only a part of the CX puzzle

To create exceptional customer experiences that are radically efficient and radically personal, conversational AI alone isn't enough.

A great conversation manages a customer’s current mood, but what if the person you're talking to can't remember anything about your past beyond the current chat? Or, what if they can’t do anything to help you beyond giving information?

The future of customer service lies in the seamless blending of different types of AI, working together like a well-oiled machine.

1. Conversational AI provides natural, human-like dialogue. It’s the voice that makes interactions feel intuitive and effortless. It allows the AI to answer questions conversationally and dynamically.

2. Contextual AI adds crucial memory and awareness. It deeply understands the customer, interpreting their history with the brand (including past purchases, service tickets, website visits, and preferences) and what's happening in the now (like their location or cart contents). This intelligence personalizes the conversation and actions, fueling them with deep insight and recall.

3. Agentic AI brings the power to act. It takes autonomous steps to solve problems by executing tasks across different systems. For example, if a customer asks to return an item, agentic AI wouldn't just tell them how to return it. It would generate a return label using an external shipping system and update the order status all on its own.

What is agentic AI?

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It’s this powerful combination—the voice, the memory, and the action—that defines the new era of customer experience. Integration at this level means your AI can do more than just talk. It can remember every detail from across the customer's journey, understand your unique situation, and take meaningful action on your behalf.

The ability to integrate AI into your systems allows your technology to pull from the tools your team relies on and supply your customers with the latest and greatest information and support.

The future isn't about choosing between a human touch and AI automation. It's about using one to make the other more powerful, creating customer experiences that are truly exceptional, every single time.