Understanding Conversational Artificial Intelligence

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Conversational AI simulates and automates natural conversation through messaging apps, speech-based assistants, and chatbots with an aim to personalize customer experiences. When automation and artificial intelligence are integrated, interactions can connect humans and machines. Conversational AI software enables long-running interactions via text and voice through Natural Language Processing (NLP).

Conversational AI solutions

Nowadays, text- and speech-based platforms have become popular mediums for interactive conversations. Messaging platforms have largely replaced email, voice calls, and face-to-face communication. Communicating on chat platforms is often easier, less intrusive, and faster than other communication channels. Consumers are also increasingly communicating with businesses through text-based chat platforms.

Increasing Need of AI

The increasing use of AI in text and voice messaging will enable the creation of unique conversation experiences and the complete automation of customer interactions. For effective conversational AI, customer experiences must be centered around messaging, chatbots, speech recognition, natural language processing, and artificial intelligence.

Conversational AI lowers customer acquisition costs (CAC) by servicing more customers without increasing staffing costs, offering engaging experiences in more places, boosting overall user experience, and improving collective intelligence. In traditional human-to-human interactions, customers benefit from the experience and knowledge of a single agent. However, with a conversational AI chatbot, customers can benefit from the knowledge and experience gained through every prior interaction ever had. Conversational AI uses several technologies, such as Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Advanced Dialog Management, and Machine Learning (ML), to understand and react to human interaction.

Conversational AI solutions also enable users to identify specific metrics that can be improved, such as CAC or LTV. Once the area of business is identified, analysts can focus on the drivers behind them, such as engagement, personalization, novelty, friction, and automation.


Conversational AI offers insight into when, where, and how businesses communicate with their customers across various channels. Using these solutions, management teams can boost user experience across their entire customer base on all platforms, devices, and channels. Once a business perfects the success of its chatbot on a pilot batch of users, it can extend its functionalities for all users and contexts.

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