What Is Conversational AI: Examples, Benefits, Use Cases

All About Conversational AI: Examples and Use Cases

example of conversational ai

Since conversational AI relies on machine learning and constantly bettering itself, it will let you automate highly personalized customer service resolutions. If you’re only thinking about chatbots, voice assistants, and automated email responders, think again. Conversational AI uses multiple technologies to converse with customers in natural, human-like language. Natural language processing (NLP) is an AI technology that breaks down human language such that the machine can understand and take the next steps. Soon after implementation, businesses using CAI suffer from a lack of customers using chatbots to interact with them.

example of conversational ai

Aside from security testing, conversational AI chatbots also apply to employee education, creating a more structured and personalized experience for every participant. Conversational AI can monitor employee scores, keep track of their overall course progress, and generate reports pointing out their performance—but that’s not all. In some cases, conversational AI can manage online lessons for employees, test their knowledge, and engage in automated conversations.

Conversational AI applications and examples in business

By February 2021, the use of telehealth options was reported to be 38 times higher than before the pandemic, with nearly 40% of patients expressing their readiness to continue using virtual health services. Such conversational AI platforms can assist customers with a wide range of requests—from changing their pin code and checking account balance to handling lost card reports or processing a payment. Meanwhile, conversational assistants keep track of every interaction, enabling more accurate customer behavior analysis. As a result, the company is more informed about the needs of every segment of its target audience and can personalize its client interactions. Before we elaborate on the specifics of conversational AI, let’s get one thing out of the way—conversational AI and chatbots aren’t the same thing.

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In an ideal world, every one of your customers would get a thorough customer service experience. But the reality is that some customers are going to come to you with inquiries far simpler than others. A chatbot or virtual assistant is a great way to ensure everyone’s needs are attended to without overextending yourself and your team. The post-production support helps to avoid this, with AI trainers identifying potential data drift risks and supplying the conversational AI chatbots with new data or adjusting them to respond to disruptive situations. With a team ready to decipher new experiences to a conversational AI platform, stakeholders can rest assured that their workflow, clients, and employees remain resilient to potential changes. Additionally, sometimes chatbots are not programmed to answer the broad range of user inquiries.

Measuring KPIs to Improve Customer Experience

Whatever questions they might have, there is a useful and knowledgeable assistant that is accessible 24/7. With more time on their hands, HR managers can concentrate on improving employee satisfaction rates and gathering more feedback from every worker. The latter is necessary for making impactful changes and keeping up with ever-growing employee expectations. Challenges like these prompted major players like Wells Fargo and Fidelity Investments to switch from massive call centers to a more automated approach.

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This will help you understand what’s interesting about each AI chatbot and use it to your advantage. One way to reduce uncertainty and boost trust is to ensure people are in on the decisions AI systems make. Department of Defense, which requires that for all AI decision-making, a human must be either in the loop or on the loop. In the loop means the AI system makes a recommendation but a human is required to initiate an action.

What are the Types of Conversational AI Suited for your Business

This creates continuity within the customer experience, and it allows valuable human resources to be available for more complex queries. Moreover, conversational intelligence can be trained to recognize and respond to individual customers’ preferences and habits, thereby providing personalized recommendations and enhancing customer engagement. By reducing the need for large teams of human customer support agents, implementing conversational AI can save money while improving response times and accuracy. Conversational AI creates human-like interactions with your customers through highly developed machine learning. By providing past customer experience data, along with continuous analysis of recent interactions, conversational AI can learn to better help your customers and your support team.

  • Of the many AI conversational platforms we looked into for this article, Cognigy was perfectly suited to handle customers from different demographics, speaking different languages, and needing different solutions.
  • This helps the system improve both its understanding of human speech and its ability to construct the right replies.
  • Conversational AI speeds up the customer care process within business hours and beyond, so your support efforts continue 24/7.
  • Conversational AI (artificial intelligence) today is probably the closest technology has come to mimicking human interactions.
  • Before we elaborate on the specifics of conversational AI, let’s get one thing out of the way—conversational AI and chatbots aren’t the same thing.

As conversational AI technology becomes more mainstream—and more advanced—bringing it into your team’s workflow will become a crucial way to keep your organization ahead of the competition. We have all dialed “0” to reach a human agent, or typed “I’d like to talk to a person” when interacting with a bot. In any industry example of conversational ai where users input confidential details into an AI conversation, their data could be susceptible to breaches that would expose their information, and impact trust. And in both of these industries, AI can serve as a starting point for users before routing them to the appropriate department or person to talk to.

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Direct engagement with these systems provides a more personalized experience for consumers who want customer support, too. Thanks to its ability to learn from specific customer interactions, Conversational AI helps companies improve their brand loyalty rates while boosting operational efficiencies. Let’s take the simple example of a customer asking a company chatbot about its hours of operation. The customer’s speech travels through the NLP technology which cleans up and deciphers the customer’s language to determine precisely what she is saying. In text-based interactions, NLP technologies can correct grammatical and spelling errors, identify synonyms, and break down the texted request into programming code that is easier to understand by the virtual agent. A familiar use case is virtual call center agents for customer support, which is what Normandin’s company Waterfield Tech handles.


The most advanced function of this tech is using machine learning to learn over time. This helps the system improve both its understanding of human speech and its ability to construct the right replies. There will always need to be human agents ready to handle more complex cases, or provide that element of human conversation that even AI can’t. But as AI develops to handle a wider variety of queries, it’ll help customers get the help they need more quickly while freeing up agents for the bigger tasks.

In fact, in a Q Sprout pulse survey of 255 social marketers, 82% of marketers who have integrated AI and ML into their workflow have already achieved positive results. The recent rise of tools like ChatGPT has made the idea of a robot assistant more tangible than it was even a year ago. With exciting new tools like conversational AI, it’s already here, and it’s changing the way we work for the better. The boost in customer engagement without increasing costs results in increased revenue, as customers stay loyal to a company giving importance to timely engagement. Conversational AI, this way, simplifies the long, often complicated, process of getting new customers.

example of conversational ai

But it can also help with more complex issues, like providing suggestions for ways a user can spend their money. Conversational AI speeds up the customer care process within business hours and beyond, so your support efforts continue 24/7. Virtual agents on social or on a company’s website can juggle multiple customers and queries at once, quickly. And with access to a customer’s order and interaction history, customers receive a seamless experience across channels. SurveySparrow, the popular online survey tool, comes with a no-code chatbot that makes them one of the best AI conversational platforms to use.

Jasper Chat

Conversational AI solutions like Heyday make these recommendations based on what’s in the customer’s cart and their purchase inquiries (e.g., the category they’re interested in). Since physicians find themselves under immense workload, they need to optimize their time as much as possible. This means they must swiftly identify emergencies, prioritize patients, and ensure that the right expert is assigned to the right case. Such an approach is possible with max data insights, transparency, and instant communication. Conversational AI hits all these boxes by connecting professionals and patients. Although physicians fear that their work would be overshadowed by telehealthcare service providers, leveraging the elements of virtual health is detrimental to overcoming post-pandemic challenges.

example of conversational ai

Of these AI-powered solutions, chatbots and intelligent virtual assistants top the list and their adoption is expected to double in the next 2-5 years. Not every customer is going to have an issue that conversational AI can handle. Make sure you have agents on standby, ready to jump in when a more complex inquiry comes in. If you’re unsure of other phrases that your customers may use, then you may want to partner with your analytics and support teams. If your chatbot analytics tools have been set up appropriately, analytics teams can mine web data and investigate other queries from site search data.

It enables brands to have more meaningful one-on-one conversations with their customers, leading to more insights into customers and hence more sales. As consumers move away from traditional brick-and-mortar financial institutions, CAI can help these organisations provide a smooth online banking experience. This reduces the load on customer support agents, who can then take up complex queries and deliver delightful experiences.

example of conversational ai

The AI can make tailored recommendations, offer promotions, and deliver personalised service by analysing customer data and behaviour. Conversational AI has emerged as a powerful tool, revolutionising how businesses interact with customers and employees. In this post, we will share our top three conversational AI examples https://www.metadialog.com/ making a big impact in the business world. Salesken’s AI chatbot works beyond traditional chatbot’s capabilities to understand the customer’s intent, emotion, and sentiment. There is an inherent demand for effortless, immediate resolutions and technologies that can be established to improve intra-teams across channels.

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