Understanding Conversational AI: What It Is and How To Use It
Many people think of conversational AI and chatbots (also known as virtual agents) as the same thing. While the best virtual assistants leverage artificial intelligence (AI), not all do, and conversational AI can power many more communication solutions than virtual assistants. Read on to discover exactly what conversational AI is, how it works, and how to use it to benefit your business.
What Is Conversational AI?
Conversational AI combines various AI strategies to enable computers to communicate with humans like humans. This technology can analyze human speech and written text across different languages, interpret meaning and context, and respond in a way that mimics human dialogue.
It can make your virtual agents smarter. It's also what powers virtual personal assistants like Siri and Alexa. The technology enhances voice assistants and interactive voice response (IVR) applications by freeing them from scripts and by freeing customers from phone trees. Rather than offering incoming callers a list of options from which to choose, an AI voice assistant lets your customers ask questions or explain their needs in their own words.
This type of AI is often used for customer service and contact centers, but these tools can also be integrated into your company websites, ecommerce platforms, social media channels, and digital marketing platforms.
How does conversational AI work?
Conversational AI solutions combine advanced AI technologies, such as natural language processing (NLP), automated speech recognition (ASR), and machine learning (ML), to interact with humans and learn from those conversations, improving the quality of interactions over time.
Understanding how conversational AI works can be achieved by looking at a few key steps:
The human provides input. The AI model receives information from humans via voice or text.
AI analyzes the input. AI uses natural language understanding (NLU) for text-based conversations to determine meaning and identify intent. For voice conversations, AI applies ASR to translate voice messages into machine-readable text and then uses NLU to analyze it.
AI formulates a response. Using natural language generation (NLG), the AI responds in a way that mimics human speech or text.
AI learns and improves. AI leverages ML algorithms to "learn" from each interaction — so it better understands the nuance of human conversation over time and can respond more accurately and conversationally.
Conversational AI vs. chatbot
What are chatbots?
A chatbot, or virtual assistant, is software that conducts conversations with users online via text or text converted into speech. It can interact with your customers on any text-based platform, including SMS, social media, and messaging apps. You can even add these solutions to your website, e-commerce site, or other online properties using communications APIs.
Not all virtual agents are created equal, nor do they all have the ability to learn. Traditional rules-based virtual assistants are scripted by humans and told what to say in specific scenarios or responses to defined keywords. An AI-powered virtual agent employs AI technology and can tap into other data sources — such as customer history and behavioral data — and thus needs no script.
The terms "conversational AI" and "chatbot" are often used interchangeably, but they're not the same. Here is a guide to their key differences:
Traditional Chatbot
Conversational AI
Text-based communication
Omnichannel communication
Uses rules-based programming to identify keywords
Uses ASR and NLU to understand user's questions or needs
Responds from script
Formulates responses in real-time
Limited understanding/responses that may frustrate users who don't use the right keywords
Understands user's meaning and leverages contextual data from other interactions to respond to any query
Static solution
Dynamic solution that improves over time
What about conversational AI chatbots?
In a world where customer expectations are higher than ever, these intelligent tools have redefined how businesses engage, connect, and build trust. If you still rely on traditional AI-driven virtual agents, you’re just playing catch-up now.
Traditional virtual assistants were fine for their time. They were efficient and able to answer scripted questions based on keywords. But they were also frustrating, static, and, frankly, uninspiring. Customers don’t want to play a guessing game with a bot; they want fast, intelligent, human-like service.
That’s where conversational AI comes in. These systems are AI-powered by technologies and fundamentally shift how businesses interact with people. Conversational AI doesn’t wait for the customer to fit their question into a neat little box. Instead, AI-powered virtual agents listen, learn, and respond intuitively, contextually, and intelligently. This takes virtual assistants to the next level.
Conversational AI examples across industries
From retail to healthcare, finance to customer service, or insurance, businesses use conversational AI tools to achieve smarter, faster, and more meaningful customer interactions. Let’s examine how.
Conversational AI for customer service
AI is completely reshaping the customer service landscape, and it’s happening faster than most companies realize. Over the past 12 months, developments in AI have been so rapid that McKinsey called last year a “breakout year” for the technology.
Now, let’s talk about customer experience because it really is make or break. Customers don’t just wait for you to fix up after a bad interaction. They flee. A full 74% of people say they’re likely to take their business elsewhere after just one bad interaction.
Conversational AI has the potential to solve this problem at scale. It can help to create experiences that feel seamless, intuitive, and human.
Conversational AI for healthcare
Every interaction, from booking an appointment to paying a bill, shapes a patient’s experience of their care. Yet, fragmented systems and outdated processes often push patients away before they even step through the digital front door.
Conversational AI technology can make these interactions seamless, answering questions, offering guidance, and giving patients confidence every step of the way, all without adding extra stress to a healthcare provider's plate.
Take Demant, for instance, which has seen conversational AI transform how it connects with its customers. As a global leader in hearing healthcare, Demant faced the challenge of transitioning its traditional face-to-face services to a remote model almost overnight during the pandemic. With the help of Vonage conversational AI capabilities, Demant now offers remote consultations through Vonage Video and SMS APIs.
Conversational AI in retail
According to Invesp, 90% of customers expect consistent experience across all channels and devices.
Let that sink in for a moment. Today’s shoppers aren’t just sticking to one method of shopping. They’re on ecommerce sites, in-store, social media, texting support, and sometimes doing all of these simultaneously. They’re researching a product online, walking into a store to check it out, or scrolling on their phones to compare prices while standing in front of a shelf.
While they’re doing this, they expect fast, personalized experiences. Our research found that 38% of customers get frustrated when they don’t get offers or interactions that feel personal to them. Nothing feels worse than being treated like another number or sent irrelevant promotions, right?
Conversational AI doesn’t just create consistency for healthcare providers and their patients; it brings context, personalization, and connection to all users. Using conversational AI for sales and marketing might see a customer get a text with an offer that makes sense for them based on their preferences, sent in real time on the channel they choose. That’s the kind of experience that builds loyalty, turning an everyday interaction into a relationship.
Conversational AI for finance
You’re busy, on the go, and managing your finances between meetings, errands, or downtime. You no longer drive to a branch for financial updates or advice. You open WhatsApp, Facebook Messenger, or Instagram.
Now, imagine if your financial institution could meet you there. That’s conversational AI banking in action. It’s your financial team on demand, providing support, guidance, and clarity wherever you are. From helping onboard new customers, sending important transaction alerts, or answering questions about financial services, it makes you feel seen and understood.
Conversational virtual agents handle simple, repetitive inquiries (like payment reminders, product information, or basic FAQs), freeing your financial advisors to focus on higher-value, human relationships. These bots don’t just respond using generic responses, either; they represent your brand, mirroring your tone, values, and professionalism.
Conversational AI in insurance
People can now buy anything they like, any time they like, with just a single tap of their finger on a screen. A new pair of shoes, check. A streaming subscription, easy. A ride-sharing service, yes! This is raising the stakes for insurance companies.
Expectations are changing, and today’s consumers expect the same experiences they get when ordering a coffee or shopping online to apply to their financial interactions.
With conversational AI, insurers can meet customers where they are. Imagine being able to ask questions about a claim via an AI-powered virtual agent who transitions to a human agent when needed. This is the kind of interaction that builds trust and confidence.
Benefits of conversational AI
Virtual agents, voice assistants, and other similar AI applications offer you several benefits:
Improve customer service experience
Virtual agents and AI-enhanced voice assistants provide prompt, 24/7 service. Your customers can avoid phone trees and long wait times and get fast answers to questions of all kinds. Conversational AI technology can be used across channels, meeting customers where they are and with context from previous interactions. Meanwhile, human agents spend less time answering simple questions, giving them more time to help customers with complex needs.
Manage 1:1 conversations at scale
Conversational AI-backed virtual assistants can pull data from various sources, including customer relationship management platforms, customer profiles, and purchase history. They don't just understand what your customer is saying; they know who your customer is and how they've interacted with your brand in the past. The AI can use this information to personalize interactions, anticipate needs, make recommendations, and remember all this information for next time — and do it in multiple languages on a global scale.
Convert social messaging into a fully-fledged store
With the right integrations, virtual agents and voice assistants can complete secure transactions without redirecting them to an ecommerce site or live agent. If a customer is intrigued by your social messaging, they can engage your social media virtual assistant and complete a purchase without ever leaving the original social post.
Turn conversations into points of sale
After your AI handles whatever business your customer has in mind, it can take the opportunity to upsell or cross-sell products and complete those transactions on the spot. Say a customer has purchased your software and asks questions about how to use it. The AI can provide a tutorial and then recommend complementary software or additional functionality that might be useful for the customer.
Omnipresence across omnichannel
Whether a customer calls in and talks to your voice assistant, texts with an AI-driven virtual agent via SMS, or messages with a virtual assistant on any popular messaging app, the customer is talking to the same AI. It recognizes the customer, remembers the last interaction, and applies that context to the current one. It's a seamless omnichannel experience personalized for each unique customer.
Challenges of conversational AI
Let’s not sugarcoat it. It’s not as simple as just waltzing into the conversational AI market. Like any technology, it comes with its share of challenges and potential roadblocks you can’t ignore. However, if you face these hurdles head-on, your business will likely find success with its AI strategies.
Understanding intent
This is one of the biggest hurdles conversational AI faces. People communicate in all sorts of ways. They use slang, typos, context clues, different accents, you name it. Training AI to correctly interpret intent across these variations is tough.
Misunderstandings lead to frustration for users, which in turn leads to disengagement. Disengagement leads to your customers leaving you for your competition.
Ensure you’re taking every opportunity to train your AI to understand exactly what your customers mean.
Bias
AI learns from data. If that data contains bias, the AI will reflect that bias. Whether it’s racial, gender, or socio-economic bias, AI systems can unintentionally perpetuate stereotypes if they’re not monitored and corrected.
This is a massive ethical issue that businesses need to tackle head-on. To combat it, constantly fine-tune your AI to ensure fairness, inclusion, and neutrality.
Data privacy and security
Conversational AI gathers and processes massive amounts of customer data. That means there’s always a risk of breaches, leaks, or misuse.
Customers trust businesses with their information, and the fallout can be catastrophic if AI mishandles that trust. Compliance with laws like GDPR and CCPA is essential here.
How to choose the right conversational AI software
The conversational AI market is flooded with options, and while they all promise innovation, not every tool will fit your unique needs. How do you decide? Let’s dive into it:
Define your objectives
Before considering conversational AI software options, ask yourself: What do you want this AI to accomplish? Is it for customer support, lead generation, or improving customer engagement across multiple touchpoints? Clarity on your goals will narrow down your choices faster than anything else.
Consider the user experience
This is crucial. You’re not just choosing software for your team; you’re choosing it for your customers, too. Look for conversational AI technology that prioritizes intuitive user interactions. It should feel natural. A good AI flows, adapting to different conversation styles and intentions. Test the software and check how it responds in lots of different scenarios.
Don’t overlook data security and privacy
Customers trust you with their information. The AI software you choose must have the tools, encryption, and compliance policies to protect that trust.
Prioritize scalability and support
Your business isn’t static. Your conversational AI will need to grow with you as your operations grow. Nothing’s worse than investing in software only to discover it can’t handle increased demand or technical glitches. Research any conversational AI services' response times, training resources, and uptime guarantees.
What is the future of conversational AI?
With so many conversational AI use cases already being employed, the future of this technology is already here, and it’s shaping how businesses interact with customers for years to come. The experts have spoken, and trends are emerging — here’s what we’ve found:
Emotional quotient, or EQ
This is going to be everything. In the near future, AI-powered virtual agents won’t just be programmed to spit out responses; they’ll have empathy. They’ll need to feel human, at least through how they interact. Cathy Pearl, Design Manager for Google Assistant, is already pushing for diverse voices and personas in AI because emotions build trust. And, trust builds loyalty.
A more personalized customer experience through data.
Let us be clear. Personalization is no longer about a virtual agent greeting you by name and referencing your last order. The future of conversational AI will use customer preferences, choices, and interaction histories across every channel to create truly tailored conversations. Data will no longer just be collected. It will be used strategically to understand the customer, predict needs, and exceed expectations.
Multi-bot orchestration.
This is where things get fascinating. Imagine a single business managing multiple specialized virtual assistants, one for billing, one for mortgages, one for insurance… And more! A master virtual agent will act as the coordinator, routing users to the right bot at the right time and achieving unprecedented efficiency.
How to implement conversational AI with Vonage
Consider conversational AI technology programmable building blocks that can help you power successful customer interactions. You don't implement it by itself — you implement tools that have the technology built into them. For example, the Vonage Voice API lets you deploy self-service tools customized to your business, which can be added across channels, from your business phone system or contact center platform to your website, mobile app, and social media pages.
Vonage Conversational Commerce enhances omnichannel outreach with AI-driven, two-way conversations across social, messaging, and the web.
As you deploy voice assistants or AI-driven virtual assistants, consider the following:
Customer journey. Where do customers interact with your brand, and how can AI add value at each of these touchpoints?
Company goals. Are you implementing AI to improve sales, bolster digital marketing efforts, streamline customer service, or all of the above? Which tools can help you accomplish these goals?
Integrations. Which databases or key business applications have important data your AI can tap into to personalize the customer experience?
Live transfers. Perhaps the most important best practice for conversational AIs is giving customers the option to talk to a live person and to make that transfer as seamless as possible.
In short, prioritize your customers’ needs when formulating a business implementation strategy, and your AI will help you meet them.
Learn more about how we can help you use conversational AI to build intelligent, effective customer experiences.
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Still have questions about Conversational AI?
The process is pretty simple and follows a step-by-step approach:
1. Your first conversational AI flow begins with the START node. Consider this your entry point, the first thing your agent will recognize when interacting with users. Without this node connected properly to the rest of your flow, your AI won’t function.
2. Every great agent starts with a warm introduction, right? Add a Speak node to welcome users and let them know what your AI can do.
3. Once you’ve established a greeting, it’s time to let your virtual agent ask why a caller is reaching out. For this, use the Collect Input node.
4. Now that the AI can gather input, you must process it intelligently. Enter the Classification node. This is the smart part of the agent that helps categorize user intent.
5. Now, it’s time to define what happens next. Your agent’s actions depend on your use case.
6. Your flow is now built; it’s time to test it and iron out any issues.
For a full breakdown, visit our support page.
The cost of conversational AI can vary a lot. It depends on what you’re looking for and the specific conversational AI use case. Are you setting up a simple virtual agent? Perhaps you need a virtual agent? Or maybe a fully customized AI solution? Where you go to build it also plays a role, as different platforms have different pricing models.
Factors such as multiple channels, agents, and/or omnichannel conversation flows can also affect pricing, as can integrations with an enterprise's platform.
Not quite, even though they’re sometimes used interchangeably. A chatbot is a type of conversational AI, but not all conversational AI is a chatbot.
A chatbot (virtual agent) is a simpler, rule-based system designed to handle basic interactions, like answering questions or guiding users through a pre-set conversation flow. They work well for straightforward tasks but can be limited if a conversation takes an unexpected turn.
Conversational AI, on the other hand, uses advanced technologies like machine learning to understand context, remember previous interactions, and adapt to more complex conversations.
More advanced virtual agents can be powered by more advanced conversational AI tools, but this is just one part of conversational AI.
Conversational AI can potentially change how we interact with technology and each other. As with any new technology, ethical considerations and risks need to be addressed. These include bias, discrimination, privacy, and security.
The good news is that there are concrete steps we can take to ensure conversational AI is developed and used responsibly. These include conducting bias audits and working with brands that are compliant and protect data.
