Should You Use Conversational AI for Customer Service? The Total Guide

Vonage looks at what conversational AI is, how it works, and what kinds of customer support applications it can be used for. They also explore the real-world advantages it could bring to your business if you decide to make the switch.

Artificial intelligence technology has advanced so quickly over the past few years that implementing conversational AI for customer service purposes is now a real possibility for businesses of all sizes.

What Is Conversational AI?

Conversational AI is a type of artificial intelligence technology that mimics how a human interacts in conversation.

Unlike more traditional call-and-response models, conversational AI is a sophisticated beast that relies on various underlying techniques, including machine learning and natural language processing (NLP), to deliver a natural-sounding interaction.

What makes conversational AI different is that it’s dynamic. It can not only understand writing or speech word-by-word but also appreciate the full semantic context of those words.

This makes it qualitatively different from older technologies – and more useful and versatile in practice.

How Does Conversational AI Work?

Conversational AI software is first trained on a huge amount of data. For example, when using a conversational AI platform for customer service purposes, you’ll begin with general AI software and then tailor it to your own needs by training it further on data from your own resources.

This could mean customer information, details about previous request tickets, etc.

When a customer makes a query by text or voice call, the AI system analyzes the message to establish user intent.

It then compares patterns in the content of the message with its huge library of training data to find a match. Finally, it composes what it judges as the most relevant response.

Another key point is that AI continuously learns from interaction, so it’s an iterative process. Over time, it becomes more accurate and relevant as it becomes more familiar with what your customers want.

Conversational AI Customer Service Applications

You can use AI in any conversational customer service context to interact directly with your clients. But that’s not the only application of this technology.

It can also lend a hand behind the scenes in constructive ways that help make your employees’ lives easier.

Let’s take a look at how your company can use conversational AI for better customer experiences.

Virtual Assistants and Chatbots

First, there are chatbots, then there are virtual agents. They’re similar, but not quite the same thing.

Chatbots are built for specific, usually text-based tasks and simpler interactions.

Virtual assistants are more sophisticated AI systems that can understand natural language and handle a broader array of tasks.

These are customer-facing AI applications that customers interact with when they’re looking for help with an issue.

If you’ve ever used traditional text-based virtual assistants, you’ll know that their performance could be somewhat hit or miss.

They could only handle simpler queries because they were programmed to respond to a preset range of questions. If your issue were complex, they’d struggle.

Modern AI-powered virtual assistants have reduced this problem. Because they appreciate context and have a massive library of data to pull from, they’re better at understanding user intent and providing relevant information.

That’s the case whether they’re text-based, like traditional virtual assistants, or voice-based, like a virtual receptionist that works via an interactive voice response system.

Agent Guides

It’s not all about what goes on front-of-house, though. Conversational AI can be immensely helpful for human agents supporting customers.

When an agent is on a call, AI can suggest possible responses in real time. It can also assess user intent independently and pull together relevant information, such as CRM customer data, product details, and pricing sheets.

Agent guides can then highlight the most relevant facts for the agent’s attention. All of this saves a lot of time – otherwise, agents would have to do all this themselves.

What’s more, it can help post-call as well. AI can provide real-time transcriptions and automatically summarize conversations for later review.

The result is that your agents can accomplish what they need to do for each customer much more quickly and efficiently.

Other Applications

Conversational AI customer support applications reach into other areas as well. For instance, they have a key role in multilingual environments. Some systems have multi-language capability, meaning they can interact with users in their preferred language.

Thanks to developments in image recognition technology, some AI systems can even capture sign language and other non-verbal cues.

Benefits of Using Conversational AI for Customer Support

So far, we’ve looked at what kind of applications conversational AI can cope with. What benefits does it bring in practical terms? Let’s explore the main advantages of adopting conversational AI solutions.

Increased Availability

Offering round-the-clock customer support service is rarely an option for most companies. It’s simply too expensive to employ teams of agents to work in shifts so that there’s always someone available.

And even if you could do that, it’s not particularly cost-effective if there’s only a trickle of calls in at 3 am.

But conversational AI is always on. Of course, it may not be able to handle more complicated queries that require some element of human intervention. But it will certainly be more useful than a recorded message urging callers to call back during work hours.

Reduced Load on Agents

Another advantage of conversational AI is that it takes much of the burden of answering common questions from your staff. Some queries come up repeatedly, such as questions about tracking orders or changing account details.

These are easy to process but can take up a lot of your agents’ time, distracting them from being able to focus on trickier work.

It’s far better to let the conversational AI system handle these, freeing up your teams to concentrate on more demanding tasks.

Enables Deeper Customer Insights

One of the biggest strengths of AI, in general, is its ability to digest an enormous amount of data and recognize patterns in it.

This makes it ideal for deep-level analysis of a kind that can be immensely helpful for understanding customer behaviour and sentiment.

In customer service applications, AI is perhaps most useful in delivering real-time sentiment analysis. It picks up on the phrasing and tone of messages and takes these into account when formulating a response.

In the context of a voice call, this could mean prompting the agent to offer specific answers or suggest personalized recommendations to the customer.

Better Efficiency

In addition to being a huge timesaver, conversational AI also increases efficiency by reducing the risk of human error.

Since it has ready access to a large amount of information and can accurately gauge user intent, it’s ready with a relevant suggestion, whether it’s interacting directly with customers or assisting an agent.

It’s also good at picking up on potential opportunities – for instance, monitoring patterns in customer behaviour and noticing before your sales team does that specific cross-selling or upselling approaches might be successful.

How to Use AI for Customer Service

No guide to conversational AI for customer service would be complete without a list of practical examples of how it can be used. There are many ways to integrate AI into your support workflows, and here are a few of the main ones:

Order Management

Most actions related to order management are fairly straightforward. If a customer wants to change an order, cancel one they’ve submitted, or simply track an order in progress, they may call for support if they can’t do it online.

In these simple cases, conversational AI can resolve the issue quickly. The added benefit is that your human staff doesn’t have to spend ages working through mundane order editing requests.

ID Authentication

When a customer gets in touch with your support team, it’s important to verify their identity. An AI-powered virtual assistant can do this automatically by asking security questions or using agreed key phrases.

The process will be similar to the one used by human agents, but since the AI can do it at the same time as collating customer information from various data sources in the background, the interaction will take less time overall.

Billing and Payment

A virtual assistant can guide customers through the payment process smoothly, just like a human agent would. It can also deal with actions such as checking and issuing refunds, as well as answering questions about account balances.

Call Routing

One of the most common uses of conversational AI in customer service is as a virtual receptionist. This is a voice-based AI system that greets customers when they contact your call centre or helps them reach the desired department or person within an organization.

Having established customer intent, they can then work with the caller to give them what they need. They can help the caller resolve their issue via self-service options or, if needed, route the call to the most appropriate available human agent.

Collecting Feedback

You can even use conversational AI to simplify the feedback collection process. For example, a virtual assistant chatting with a customer can request feedback at the end of the conversation, taking them through the survey or feedback forms.

One of the great things about using AI for this is that more customers are willing to participate. After all, a couple of questions added at the end of the conversation they’re having anyway takes less effort to answer than responding to an email request, for example.

What Do Customers Actually Think About Conversational AI?

Given how quickly the digital environment is changing, figuring out how your customers actually feel about conversational AI can be tricky. After all, attitudes are evolving fast.

While some people seem to appreciate that AI can resolve issues efficiently, many others may not be comfortable interacting with an AI as if it’s a human being. For some customers, there could well be a hint of “uncanny valley” at play.

We surveyed over 7,000 customers in 17 global markets about their experience, reporting our findings in our Global Customer Engagement Report 2025.

This included some in-depth study of current attitudes to AI. We uncovered some fascinating insights. For example:

• 66% of customers are somewhat or very likely to use AI tools for a faster response.
• 76% of customers are concerned about personal data security when using AI-powered support tools.
• Only 22% of customers are very comfortable with AI-powered support tools handling complex/sensitive issues.

It’s clear there’s work to do to convince some customers of the benefits of conversational AI. In essence, this is all about fostering trust, so it’s critical to follow best practices when implementing a conversational AI solution.

Best Practices for Integrating Conversational AI in Customer Service

With that in mind, let’s now look at some of the most important conversational AI best practices you should be following.

For any company looking to leverage conversational AI for customer satisfaction, these are the key steps to take to ensure success:

1. Be Transparent About AI Use

It’s essential to be upfront with your customers about the fact they’ll be interacting with an AI. The last thing you want is for a customer to believe they’re talking to a real person, only to find out later they weren’t. If that happens, it could lead to a serious loss of trust.

It’s not an unlikely outcome, either, if you’re not open about how you use AI in your business. After all, today’s AI technology is much more advanced than even a few short years ago. It can be genuinely difficult for many people to tell the difference between talking to a human and talking to AI.

2. Provide a Human Option

It’s vital to give people the choice to speak to a human if that’s their preference. Clearly signpost the option to reassure your customers so they don’t feel as if they’re being forced to take the AI route.

Don’t be put off from doing this because you think too many people might choose the human option. Remember that our customer engagement survey showed that two-thirds of customers are likely to use AI tools if it means they’ll get a faster response.

Also, don’t forget that there’s a psychological element at play here as well. Giving reassurance that the human option is there if needed actively encourages people to try interacting with the AI anyway.

3. Build a Detailed Knowledge Base

Any conversational AI system is only as good as the data it’s trained on. A core element of preparing your AI platform for launch is to ensure it knows everything about your business.

What kinds of questions do your customers typically ask? You’ll need to compile a comprehensive knowledge base to answer them. Then, set up your AI system to be able to access it efficiently.

One of the most convenient ways of doing this is to use Retrieval Augmented Generation (RAG) with a large language model generative AI. This lets you embed your proprietary data directly into the LLM prompt, so AI can retrieve it more easily.

You should include information such as:

• Product details
• Service lists
• Troubleshooting guides
• Terms and conditions
• Data privacy policies
• Pricing options

The more your AI knows, the better service it will give your customers.

4. Prioritize CX Projects

To ensure conversational AI is actively improving the customer experience, you’ll first need to identify those areas where it can have the most impact. It also means you’ll need to have concrete objectives in mind.

What do you want to achieve? Are you looking to reduce support costs? Increase customer satisfaction scores? Or perhaps you’re aiming to put a big focus on personalization?

Whatever your goals, it’s crucial to decide on relevant KPIs to measure. This allows you to track progress and make sure your AI implementation is delivering genuine value for your customers. Focus on practical measures, and evaluate results as you go.

5. Monitor Performance and Fine-Tune

There’s always room for improvement. Gather feedback continuously and monitor how well your AI platform is doing. Is it meeting customer expectations? What’s it particularly good at? Are there some topics it struggles with?

Act on the feedback and tweak the AI as required. Doing this consistently means the AI will constantly improve. In turn, customers will become more comfortable using it because they trust it to deliver what they need.

How to Choose a Conversational AI Platform for Customer Engagement

There are a few core factors to consider when thinking about implementing conversational AI for customer engagement purposes. Here’s a quick overview of the best questions to ask before committing to a particular AI solution.

Will It Integrate Well With Existing Business Tools?

Any new software you adopt in your business must integrate well into your existing tech stack. Otherwise, it’s a non-starter.

Ideally, you want a conversational AI solution that works hand in glove with the rest of your communications software, so you can integrate it seamlessly into your customer support workflows.

Is It Secure?

Security comes next on the list. You’ll be giving your AI access to a huge amount of information, including sensitive customer data.

It’s essential to ensure any conversational AI platform you choose has built-in safeguards and uses top-end security to keep your data safe from unauthorized third parties.

Is It Scalable?

When thinking of using a conversational AI platform for customer engagement, you also need to consider what the future holds.

If your company grows rapidly, the solution you choose has to be able to keep up. Opt for an AI system that will scale easily as your business does.

How Customizable Is It?

Customization is key when it comes to conversational AI. You need to adapt it to fit your unique business needs. Make sure to go for an AI platform that allows you to control the finer details of implementation so that your customers recognize it as part of your own distinctive brand.

Does It Have Reporting Functionality?

Going for an AI solution with comprehensive reporting functionality out of the box simplifies the process of monitoring performance. So, it’s best to choose one that gives you good visibility into the inner workings of the process.

That way, you can gain valuable insights that help you fine-tune your customer service.

Will You Have Access to AI Expertise?

Finally, having access to expert support is essential. The AI field is fast-changing, and most companies will need up-to-date guidance not only for the initial system implementation, but also for keeping up with new developments.

You may also want to consider choosing a provider that offers a fully managed service if you don’t have the resources to deploy a solution in-house.

Will Conversational AI Replace Your Human Workforce?

The short answer is no. Conversational AI for customer experience optimization and customer support can be an excellent addition to the service you already provide. But it’s not meant to be a substitute for human skill.

Instead, the two are meant to work together collaboratively to achieve more-effective results. At its heart, conversational AI is a tool like any other – an advanced one, perhaps, but a tool, nonetheless.

AI is great at dealing with the kind of run-of-the-mill inquiries that can otherwise monopolize your human agents’ working day, such as account management, order tracking, and billing queries – the basic tasks that don’t need a huge amount of experience to handle.

This frees up your teams to focus on the more complicated queries that they alone have the experience to manage. In short, it’s the perfect partnership.

This blog post has been re-published by kind permission of Vonage – View the Original Article

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Vonage
Reviewed by: Jo Robinson