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Why Conversational AI Is So Much More Than a Chatbot

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The history and use of conversational AI, and the ways conversational AI is being used outside of typical chatbots.

When people think of conversational AI, their first thought is often the chatbots that one encounters on many enterprise websites. While they would not be wrong, as that is one example of conversational AI, there are many other examples that are illustrative of the functionality and capabilities of AI technology. In this article we will discuss the history and use of conversational AI, as well as the ways conversational AI is being used outside of the typical chatbot.

The Difference Between Traditional Chatbots and Conversational AI

Chatbots made their debut in 1966 when a computer scientist at MIT, Joseph Weizenbaum, created Eliza, a chatbot that was based on a limited, predetermined flow. Eliza could simulate a psychotherapist's conversation through the use of a script, pattern matching, and substitution methodology. Although Eliza was able to pass a restricted version of Turing test, and fooled humans into thinking that they were talking to another human, it was simply following rules and simulating the conversation with no real level of understanding what was being said.

A decade later, a natural language program called PARRY was created by Kenneth Mark Colby at the Stanford Artificial Intelligence Laboratory. Although it was the first AI program to pass a full Turing test, it was still a rule-based, scripted program. In 1995, Richard Wallace created the Artificial Linguistic Internet Computer Entity, (ALICE), and it used what was called the Artificial Intelligence Markup Language (AIML), which itself was a derivative of XML. Like its predecessors, ALICE still relied upon rule matching input patterns in order to respond to human queries, and as such, none of them were using true conversational AI.

Conversational AI relies upon natural language processing (NLP), automatic speech recognition (ASR), advanced dialog management, and machine learning (ML), and is able to have what can be viewed as actual conversations. It also uses deep learning to continue to improve, and learn from each conversation. It is more flexible, and is able to jump from one topic to another, much like actual human conversations do, unlike traditional chatbots, which are limited to pre-defined scripts and rules, and cannot respond with anything that was not originally inserted into its conversational flow.

“Rule based or scripted chatbots are best suited for providing an interaction based solely on the most frequently asked questions. An ‘FAQ’ approach only supports very specific keywords being used,” said Eric Carrasquilla, senior vice president and general manager of Digital Engagement Solutions at CSG. “Conversational AI is ingesting the customer feedback and learning in real-time that value, which can be applied to the same question at a different point of a client’s journey.”

By using conversational AI-based chatbots, basic questions such as delivery dates, tracking numbers, and shipping fees can be easily and quickly taken care of, while more complex or serious customer service inquiries can be passed on to live customer service representatives. “The appropriate nature of timing can contribute to a higher success rate of solving customer problems on the first pass, instead of frustrating them with automated responses,” said Carrasquilla.

Related Article: How Conversational AI Works and What It Does

Conversational AI Is Effective and Trusted

Conversational AI is being used to provide functionality in chatbots that mimics human conversations — and it’s still the top use of conversational AI today. A 2020 MIT Technology Review survey of 1,004 business leaders revealed that customer service chatbots are the leading application of AI being used today. 73% of those polled said that by 2022, chatbots will remain the leading use of AI, followed by sales and marketing. Not surprisingly, a report from Capgemini, AI and the Ethical Conundrum, indicated that 54% of customers have daily AI-enabled interactions with businesses, including chatbots, digital assistants, facial recognition, and biometric scanners. 49% of those customers found their interactions with AI to be trustworthy, up from only 30% in 2018. What used to be irregular or unique is beginning to be the norm, and the use of AI is gaining acceptance in many industries and applications.

It’s not just customers that are beginning to trust conversational AI. Oracle and Future Workplace’s annual AI at Work report indicated that 64% of employees would trust an AI chatbot more than their manager and 50% have used an AI chatbot instead of going to their manager for advice. 26% of those polled indicated that bots are better at providing unbiased information and 34% said they were better at maintaining work schedules. Not only that, but 65% of employees said that they are optimistic, excited and grateful about having AI bot "co-workers" and nearly 25% indicated that they have a gratifying relationship with AI at their workplace.

The Washington Post recently reported on the trend of people turning to conversational AI, such as Replika and Microsoft’s Xiaoice, for emotional fulfillment and even romance. With the isolation, separation, and loneliness that the pandemic brought with it, and the advances in artificial intelligence, many people have found that an AI-based chatbot, and even AI voice chat, fulfills the need for communication with other humans. In fact, Xiaoice has 10 million active users in China.

Related Article: What’s Next for Conversational AI?

Conversational AI Is Omnichannel

Traditional chatbots are text-based, and are generally found on only one of a brand’s channels, typically its website. Conversational AI is omnichannel, and can be accessed and used through many different platforms and mediums, including text, voice, and video. “The pairing of intelligent conversational journeys with a fine-tuned AI application allows for smarter, smoother choices for customers when they reach out to connect with companies,” Carrasquilla suggested.

Learning Opportunities

Common examples include digital assistants such as Cortana, Google Home, and Siri, so-called smart speakers, such as Amazon Alexa, and Google Home, as well as virtual call center agents. According to a report from National Public Media, 24% of people over 18 (around 60 million people) own at least one smart speaker, and there are around 157 million smart speakers in U.S. households. Smart speakers account for approximately 69% of voice assistant users.

The use of smart speakers has facilitated the acceptance of conversational AI in the household. According to Google, 53% of people who own a smart speaker said it feels natural speaking to it, and many reported that it feels like talking to a friend. Several respondents told Google that they are even saying “please” and “thank you” to these devices.

Chris Radanovic, a conversational AI expert at LivePerson, told CMSWire that in his experience, using conversational AI applications, customers are able to connect with brands in the channels they use the most. “Intelligent virtual concierges and bots instantly greet them, answer their questions and carry out transactions, and if needed connect them to agents with all of the contextual data they’ve collected over the course of the conversation,” he said.

Related Article: Designing Effective Conversational AI

Conversational AI Facilitates Hyper-Personalization

Because of its ability to instantly access customer data in real time, conversational AI is able to facilitate the hyper-personalization that customers expect today. “Hyper-personalization combines AI and real-time data to deliver content that is specifically relevant to a customer.” Radanovic emphasized that consumers and brands are embracing conversational AI because it provides personalized experiences that are also much quicker and more convenient than traditional ways of interacting with businesses. Customers do not want to be waiting on hold for a phone call or clicking through tons of pages to find the right info.

According to Radanovic, conversational AI can be an effective way of eliminating pain points in the customer journey. “A giant source of frustration for consumers is repeating information they’ve already shared, like re-confirming a phone number or having to re-explain a problem to multiple agents. As brands adopt tools like LivePerson’s Conversational Cloud, which allows conversational AI to connect to conversation histories, customers’ previously stated intentions, and other data, the conversations they have with consumers feel far more personalized.”

Related Article: 4 Ways Conversational AI Is Improving the Customer Experience

Final Thoughts

Conversational AI is not only very effective at emulating human conversations, it has become a trusted form of communication. Today’s AI-based chatbots are worlds apart from the archaic chatbots we were used to seeing on enterprise websites. Brands are using conversational AI across all of their channels, providing hyper-personalized conversations with customers in real time.

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