What is Conversational AI? Examples and Benefits
What is conversational AI and how does it work?
These more advanced “chatbots” provide more humanized and personalized service. In addition to being able to generate natural-sounding language, they are also able to execute complex tasks like scheduling appointments and sending relevant follow-up information. Intelligent virtual agents help support customer services teams and provide customers with an exceptional experience. Conversational AI is the subset of artificial intelligence that leverages concepts like neural networks, machine learning, and NLP to facilitate human-like conversations with machines. The technology powers chatbots or virtual agents to have human-like conversations with users by recognizing user inputs and interpreting their meanings. Conversational AI is the technology that enables chatbots or virtual agents to have human-like conversations with users by recognizing user inputs and interpreting their meanings.
- Salesken’s conversational AI brings you the best and the latest technologies revolving around artificial intelligence to deliver a superior customer experience.
- Using various industry examples, we’ll uncover its capacities, from data collection to refining it through user feedback.
- Since they only serve a specific purpose, they are designed to follow a workflow designed by organisations and are relatively easy to build.
- The more customers interact with your business AI applications, the more data you’ll collect on your customer base.
On the surface, conversational artificial intelligence tools sound deceptively simple. However, there are many technological components working in tandem with each other to process, accurately understand, and generate responses in a human-like interaction and provide a smooth experience to customers. Primary components include machine learning and natural language processing.
Example 2 – Customer engagement automation
Ideally, you’ll select key metrics that reflect the tool’s intended impact on your team. Whether it’s automated resolutions, average response time, customer satisfaction (CSAT), or deflection rate, choose metrics relevant to your goals. ChatGPT is the popular chatbot from OpenAI, powered by their language model Generative Pre-trained Transformers (GPT) – which is actually behind many conversational AI platforms today. For example, the technology can streamline employee training, enhance onboarding procedures, and efficiently manage employee data updates. Conversational AI is trained on datasets containing samples of both written and spoken human language to understand how people communicate. Employees, customers, and partners are just a handful of the individuals served by your company.
These chatbots are programs to identify and analyze keywords to address any query. Keyword recognition-based chatbots use Natural Language Processing to decide how to respond to the customers. The most common examples of conversational AI chatbots are in the feedback and survey section. It displays options like conversational ai examples “Rate our service,” “Provide feedback,” “Request a callback,” and “Skip survey.” It is potent enough to solve more than 80% of the customers’ support queries. Button-based chatbots are trained to give specific outcomes for specific input. It will guide the customers with some options related to their queries.
Main differences between conversational AI and generative AI functionality
This will give you a better grasp of how to find the right conversational AI platform for your specific support needs. Some AI bots function as add-ons to your platform, while others are native to specific ones. If you’re considering a platform switch for advanced AI capabilities, the chatbot should be compatible with various support platforms. Rethinking processes in order to incorporate a conversational AI chatbot is exciting, but it also presents a significant challenge.