Common Questions about Conversational AI, Answered

Conversational AI is an ever-growing field, but there is no doubt that it has already embedded itself in our lives. Be it for personal reasons (like asking Alexa to turn off the lights in the living room) or professional purposes (like interacting with a software’s customer support chatbot), most people engage with some sort of AI program on a daily basis.

Despite the increasing prevalence of conversational AI, many questions still exist about the concept, from the basics of what conversational AI actually is to how one can actually use it for customer service or otherwise. 

As interest and usage of conversational AI continues to grow, here is a rundown of the must-know facts about the technology.

What is conversational AI?

Conversational AI refers to a type of artificial intelligence (AI) that allows users to engage in back-and-forth conversations with computers. At its most sophisticated level, a human conversing with a conversational AI application would not be able to decipher that the other side of the conversation isn’t a human. 

How does conversational AI work?

Conversational AI functions using a variety of different technologies and concepts, one of which is natural language processing (NLP). NLP is the branch of artificial intelligence that enables computers to understand human language. By giving computers the ability to parse the intent and meaning of words and phrases, NLP also allows computers to respond to human language via sentences of their own.

Training an NLP model relies on feeding it a large corpus of data from which the AI technology can learn. For a customer service chatbot, for instance, an NLP model would learn from transcripts of existing conversations between customers and support agents at a brand. With enough data, the AI model will determine patterns and be able to extract the meaning and intent of questions, phrases, etc. It then uses this data to formulate responses designed to answer customer questions and solve problems. 

Because the technology behind conversational AI relies on existing data, the quality and accuracy of AI-based programs improves over time. 

What is an example of conversational AI?

One common example of conversational AI is a voice assistant—think Siri, Alexa, Google Home, etc. Smart speakers and home assistants have become virtually ubiquitous. A 2020 study found that 45% of Americans already owned a smart speaker, but their popularity is not limited to the United States. It’s estimated that, by 2024, there will be more voice assistants in use globally than people, with 8.4 billion units worldwide. 

Another widespread example of conversational AI is the chatbot. These days, it’s commonplace to navigate to a business’s website only to hear a familiar ‘ping’ sound accompanied by a small robot icon appearing in the bottom right corner. While not all chatbots are AI, many do use machine learning and NLP to help serve customers at the same standard that a human customer service representative would.

Because chatbots are the most widely used application of conversational AI in business, let’s dive in deeper.

What is a chatbot?

Put simply, a chatbot is any online application that enables humans to have a conversation with a computer. The world’s most sophisticated chatbots use AI and natural language processing to simulate human-like interactions. Depending on the needs of the business or organization using the bot, chatbots can be fairly simple and straightforward, or highly complex.

Are all chatbots AI?

Not all chatbots are based in AI, though it is a common misconception that they are. While many chatbots either function via AI or are advertised as doing so, many chatbots are actually what is known as rules-based. Rules-based chatbots use a designated script and flow that doesn’t change, regardless of the input from the customer. Most of the time, these rules-based chatbots function via the use of button inputs, similar to interactive voice response technology used at the beginning of phone calls with a business’s customer support department.

What are chatbots used for?

The purpose of chatbots can vary widely, but one of the most commonplace uses of chatbots is for customer service. Many websites install a chatbot on their website as a way to field incoming customer questions and requests, often with the intention of filtering these inquiries to then be assigned to a customer service representative.

More sophisticated chatbots, such as those based in AI, are often able to resolve customer issues or provide answers to questions without ever involving a human support agent. This is one of the key benefits of chatbots, as it helps reduce the time agents spend on repetitive, easily answered questions, giving them more bandwidth to handle sensitive or pressing customer requests that require a personalized touch. 

What is the difference between chatbots and conversational AI?

It’s a common misconception that chatbots and conversational AI are the same. While AI-based chatbots are a type of conversational AI, not all conversational AI takes the form of chatbots.

What are the benefits of conversational AI?

Because conversational AI most frequently is used to power conversations between customers and brands, we’ll focus on the customer service benefits of using the technology. For one, conversational AI benefits customers by being available 24/7. AI-based chatbots don’t need to sleep or take breaks, so they can continuously field questions through all hours of the day and night, even when agents are no longer available. Secondly, chatbots can handle multiple customer conversations at once without breaking a sweat, leading to reduced wait times to get assistance.

Businesses themselves benefit from implementing AI-based chatbots, as helping customers get answers faster leads to improved customer satisfaction and loyalty. Meanwhile, as we addressed earlier, agents no longer have to address as many tickets or incoming requests, as commonly asked questions and issues can be resolved by a chatbot instead. This not only improves the customer experience, but the agent experience as well—helping to deter turnover.

What does the future of conversational AI look like?

No one can say with 100% certainty what the future of conversational AI has in store, but we can make some educated guesses.

One failure of present-day AI is related to bias—not just in terms of the bias inherent in the datasets from which the AI pulls, but also in terms of what languages the end product is available in. When building AI-based chatbots, the vast majority of businesses, even those with global audiences, only focus on deploying an AI bot in English. This prevents non-English speaking customers from taking advantage of the aforementioned benefits of conversational AI, thereby hindering their experience with your brand.

Given that 75% of consumers from non-English speaking countries prefer to buy from brands that offer post-purchase support in their native language, excluding those who don’t speak English from the (literal) conversation is a massive oversight for brands with any sort of multilingual customer base. 

This is why we predict a major shift in conversational AI—one that is far more language-inclusive. We must start with the commonplace applications of conversational AI that exist today, such as chatbots and interactive voice response on the phone, but as AI-enabled conversational technology expands, these new applications must consider how to connect with customers beyond those who speak English.

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At Language I/O, we are leading the charge of making conversational AI go beyond English or any one language. Via turnkey integrations or our API, we turn existing chatbots into polyglots that can support customers in over 150 languages. To learn more, reach out to us for a demo.