What Conversational AI Is and Why It's Not Just a Chatbot

In 1966, Joseph Weizenbaum, a computer scientist at MIT, developed Eliza, the first chatbot, based on a constrained, predefined flow. Using a script, pattern matching, and replacement methodology, Eliza was able to mimic a psychotherapist's conversation. Eliza could fool people into thinking they were speaking to another human and pass a limited version of the Turing test, which determines whether a machine can behave intelligently indistinguishable from a human. However, Eliza was merely following rules and simulating the conversation with no real level of understanding.

A combination of machine learning and natural language processing technology that enables people to engage with computers in a manner akin to that of a human is what is generally referred to as conversational AI. Let's take a closer look at the development of conversational AI to further explain it. Conversational AI: What is it? It uses machine learning (ML), automatic voice recognition (ASR), advanced dialog management, and natural language processing (NLP) to have what might be considered real conversations. Deep learning is another technique that conversational AI utilizes to keep learning and getting better with each conversation. Unlike typical chatbots, which are constrained to pre-defined scripts and rules and are unable to answer with anything not already entered into its conversational flow, it is adaptable and may switch between topics, much like actual human speech.

Conversational AI takes in consumer feedback and learns from it in real-time so that it can answer the identical question at a later stage of a client's journey. Basic contact questions like delivery dates, tracking numbers, and shipping costs can be swiftly and readily resolved by deploying conversational AI chatbots, while more complicated or important customer service inquiries can be forwarded to actual customer service agents.

What is a conversational AI example? Giving chatbots capabilities so they can replicate human conversations and enhance the customer experience is one of today's most popular uses. The most common use of AI now is in customer support chatbots, according to an MIT Technology Review survey of 1,004 corporate leaders. Chatbots will continue to be the most popular application of AI by 2022, according to nearly three-quarters of those surveyed, followed by sales and marketing. Unsurprisingly, a Capgemini analysis titled AI and the Ethical Conundrum found that 54% of customers interact with businesses on a daily basis using AI-enabled tools including chatbots, digital assistants, facial recognition, and biometric scanners. Compared to only 30% in 2018, nearly 50% of those clients believed their interactions with AI were trustworthy. The usage of AI is becoming more commonplace in various fields and applications, and what was formerly unusual or unusual is starting to become the norm.

Customers aren't the only ones who are starting to trust conversational AI. Those who have established jobs use and trust conversational AI products in the workplace. According to Oracle and Future Workplace's annual AI at Work survey, 64% of employees would trust an AI chatbot more than their manager, and 50% have sought guidance from an AI chatbot rather than their boss. 26 percent of individuals surveyed believed that bots were better at providing objective information, and 34 percent believed that they were better at keeping to work schedules. Additionally, nearly 25% of workers claimed they have a satisfying relationship with AI at their place of employment, and 65% of workers expressed optimism, excitement, and gratitude about having AI bot "coworkers."

The issue of privacy and security may be raised in light of the two conversational AI instances mentioned above, in which users engage in private chats with a bot and possibly even divulge personal information. How secure is using conversational AI? Conversational AI is as secure as it is designed to be, like most things. Users need to have faith in both the firm that developed and advertised the technology they're utilizing as well as the technology itself. It will take some investigation into how a particular conversational AI program was created and how it works to determine whether it is safe to use.

Natural language understanding and machine learning-based conversational AI models are highly good at simulating human conversations and have established themselves as reliable channels of communication. Conversational AI is used by businesses to encourage customer interactions across several channels. As a result of these interactions, the technology picks up new information, improves, and provides insights into its users, fostering closer business-customer ties. These bots, however, have uses beyond just business. These bots are used by people to automate repetitive jobs, simplify routines, and discover information. In the end, they have integrated into people's routines.