There has been an explosion, in recent years, of digital-based conversational products. The most commonly used are chatbots, which use decision trees to deliver static, pre-programmed messages. Chatbot spend is projected to increase from $2.8 billion in 2019 to $142 billion in 2024.

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The spectacular growth in chatbot spend and adoption can be put down to the fact that consumers don’t want to be put on hold or wait for a call back in a virtual line to contact someone when they have a question or problem.

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But chatbots are not the only source of growth for digital conversation products. Voice products - the most well known of which are Alexa, Siri, and Google Assistant - have also seen explosive adoption. These tools have mainly gained ground with consumers, although there are increasing enterprise applications.

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Computers never have to take time off and can do vastly more than any human being. As a result, they are able to increase by several orders of magnitude, the volume of items that a company can respond to. Because of this, they will form an enduring part of customer engagement.

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Conversational products, however, are not made equal. At the top of the technological pyramid is conversational artificial intelligence. Breakthroughs in machine learning technology and big data have enabled the development of products that move beyond decision trees and pre-programmed responses.

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We are now able to collect, store, and process large amounts of human conversation data. This data is then fed into machine learning algorithms which will decode the meaning of the conversation and generate a response in human language.

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But the capabilities of conversational AI do not end there. It’s not called “machine learning” for nothing. The algorithms that underpin all of this are not static but dynamic. Built into machine learning is the capability The technology is constantly refining itself, developing a better understanding and better responses.

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Customers don’t just want speed. They also care about quality. If the speed of a computer is used to deliver robotic, unhelpful speech, then the efficacy of that system is limited. Consumers will end up tired and frustrated, feeling as though they do not matter.

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Conversational AI offers the only solution that can deliver high quality, human conversations at the speed of a computer.

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