Artificial intelligence has reached a stage where people can effortlessly interact with automated systems or conversational interfaces such as chatbots or voice assistants.
ResearchAndMarket estimates that the global Conversational AI market will grow from 4.8 billion USD in 2020 to 13.9 billion USD in 2025. This shows the enormous momentum that Conversational AI has already gained and the importance it will have in the future.
Let’s explore why it is worthwhile for companies to invest in chatbots and voice assistants now.
What does Conversational AI actually mean and how does it work?
Conversational AI is a form of application of AI technologies that enable automated, natural language based dialogues via systems such as chatbots or voice assistants. Successful Conversational AI is in place when a user can ask a question – whether via text or voice – and receives a correct and natural language based answer in real-time.
The technological foundations for Conversational AI are speech recognition and knowledge modeling. First of all, the user’s input must be recognized and understood. The discipline of Natural Language Understanding (NLU) deals with this task. It is about understanding the structure and meaning of human communication. Equally important, but less often considered is the subject of knowledge processing and modeling. Internal company data and knowledge as well as user-generated knowledge has to be specifically prepared and modeled to serve as a basis for Conversational AI.
How do companies benefit from chatbots and voice assistants?
Thanks to the advantages of these intelligent, automated communication channels that are available around the clock, more and more companies are using Conversational AI to interact with customers and prospects in addition to telephone or email.
Companies benefit not only from automated 24/7 customer service, but also from higher interaction rates on their websites, automated lead generation, and efficient use of resources. Moreover, when using chatbots or voice assistants, companies are taking the communication habits of their customers into account leading to improved customer satisfaction. Basically, they provide relevant information at the right touch points and, thus, create a personal and intuitive customer experience. In addition, chatbots offer a wide range of possible use cases from customer service, marketing, and sales to HR and are not limited to just one industry.
Another area of application that is often overlooked is the internal use of Conversational AI. By structuring and preparing the internal data and knowledge of a company, e.g. in the form of a knowledge graph, chatbots and voice assistants can access this knowledge and make it available in natural language. This can simplify the provision and flow of information in companies for decision-makers as well as for employees.
Why is Conversational AI a mandatory topic for companies right now?
This year, chatbots and voice assistants have already proven themselves and shown what a valuable contribution they can make in times of crisis and how they can support such a massive need for communication and information.
Chatbots and voice assistants are more than just hype. They have developed in many ways over the past few years and today work is being done on speech recognition and knowledge modeling in order to further improve the quality of the automated conversations. At Onlim, we see the greatest need for action and optimization in knowledge processing and modeling. As we like to say, just because a chatbot understands a question, doesn’t mean it can answer it correctly.
Conversational AI entails a comprehensive transformational process. The way we communicate, obtain information and access knowledge will change permanently. Interest in Conversational AI solutions will continue to grow. In particular, there will be a clear trend towards the use of voice assistants over the next few years. New business models around voice and chatbots. The earlier companies deal with Conversational AI, the greater the likelihood of gaining a competitive advantage from them.
You can learn more about how knowledge graphs help to build the basis for meaningful conversations between humans and machines in this whitepaper.