Chatbots, virtual assistants, and other forms of conversational AI solutions have become increasingly popular in recent years. Each business has at least several opportunities to service online customers during the day, and conversational AI technology ensures that customer needs are satisfied in a consistent and timely manner.
Since conversational AI technology can initially seem overwhelming, this article will help you understand what conversational AI is and what it’s used for.
What is conversational AI?
Conversational AI is a branch of artificial intelligence that can imitate human conversations in real-time and improve user experience.
Two main components make conversational AI work.
Machine learning (ML)
Machine learning is a subfield of artificial intelligence that uses algorithms trained on data sets to create predictions and patterns without being explicitly programmed for specific tasks. The AI continuously improves itself by gathering more and more input, enabling more accurate responses.
Natural Language Processing (NLP)
NLP is another subfield of AI that involves analyzing and processing language to produce appropriate responses in human-computer interaction. It consists of input generation, input analysis, dialogue management, and reinforcement learning.
Natural Language Understanding (NLU) is a subfield of NLP that focuses on understanding the meaning behind words. It’s designed to recognize context, syntax, idiomatic expressions, sarcasm, and other aspects of the human language.
Examples of conversational AI
When people think about conversational AI examples, they usually mean conversational AI chatbots and virtual assistants because of their omnichannel deployment.
Chatbots are computer programs that are made to simulate human conversations. Unlike rule-based chatbots that generate responses by pre-defined rules, AI-powered chatbots use machine learning algorithms to learn from past interactions and continuously learn by engaging in conversations with users.
Chatbots can be found on various platforms like e-commerce websites and social media, and even messaging platforms like WhatsApp and Messenger.
AI Virtual Assistants
Similarly, virtual assistants use machine learning and NLP to understand commands and respond to users by giving appropriate responses or routing their requests to other channels.
They’re used on phones, smartwatches, smart speakers, etc., but they can also be used as chatbots to interact with customers in different industries. However, they offer more comprehensive and personalized services than chatbots and are trained for various tasks.
Possible uses of conversational AI
In the digital transformation era, conversational AI tools have plenty of use cases.
Online customer support
When used in online customer support services, conversational AI streamlines responses to customers and, as a result, increases customer engagement and improves end-to-end customer experience.
It’s available 24/7 and makes the contact center accessible even when human agents aren’t available. Through automation, conversational AI reduces costs and increases productivity by allotting a higher number of tasks.
In healthcare, conversational AI bots can improve patient satisfaction. They’re available 24 hours and can reduce patients’ stress and anxiety by providing more information about medical topics that concern them.
In addition, they can aid patients in finding suitable healthcare providers based on their symptoms or scheduling their appointments.
Internet of Things (IoT) devices
Conversational AI is present in your everyday interactive voice assistants, like Amazon Alexa, Apple Siri, Microsoft Cortana, etc. These devices use speech recognition and perform tasks based on context and speech patterns.
Since this involves unsupervised machine learning, there are often some errors, but their functions improve as the user continues to provide more input.
Retail and e-commerce uses
Conversational AI is valuable in retail because it enables personalized experiences based on customer data and input. The AI is able to remember customer preferences and provide recommendations or get better insight into what customers need and want.
In HR processes, Conversational AI platforms are used for recruitment, onboarding, and documentation. It can quickly filter through hundreds of CVs, provide all the necessary data to new members before they start working, and consistently update the records of all members.
Finance and banking
Like in online customer service, conversational AI bots can improve customer satisfaction and increase customer engagement in finance and banking.
In addition, bots can check customers’ balances across all accounts and prevent fraud by detecting fraudulent activity and using speech recognition software. Furthermore, by analyzing users’ data, they can also create spending plans to help customers decide how to use their money.
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What is the difference between chatbots and conversational AI?
Chatbots are computer programs made to simulate customer interactions, usually via messaging apps. Conversational AI is a broader term that refers to technology that enables natural conversations between humans and machines and includes chatbots, voice assistants, virtual agents, etc.
What are the benefits of conversational AI?
Conversational AI saves time, reduces costs, improves customer satisfaction, decreases the amount of work per employee in fast-paced environments, personalizes customer experiences, provides valuable assistance to individual users, and much more.
How do you know if AI is working well?
To test your AI, establish which algorithm it’s using first. Then train your AI by inputting data and allowing continuous learning. Monitor the performance during the data input stage. Once training is completed, test the AI.
What is the first step to building a conversational AI for your business?
The first step is defining why your business needs conversational AI. Conversational AI solutions should be used when you need to reduce the call volume for your support team and improve customer satisfaction or increase customer engagement. Still, they should not replace customer support altogether.