The hype about chatbots was driving in 2016 when messaging apps counted more active monthly users for the first time than social networks and brought great expectations. 80% of companies wanted to use chatbots for customer service, marketing or sales by 2020. In this guest post, we will discuss whether this is really the case, where we actually find ourselves today with the state of conversational AI and what the future will probably bring.
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What does “conversational AI” actually mean?
The term conversational AI is not always used uniformly and therefore often leads to misunderstandings. Conversational AI is basically understood as application forms of AI technologies that enable automated, natural-language dialogues via systems such as chatbots or voice assistants. A German translation of the term could be “conversation AI” or “AI-powered, automated dialogue systems”.
Trend, technology & challenges in 2020
By now, the chatbot hype has normalized somewhat and we probably won’t have more conversations with bots as Gartner predicted than with our partners. Due to the advantages of an intelligent, automated and available 24/7 communication channel, more and more companies are using conversational AI to engage in dialogue with customers and prospects in addition to telephone or e-mail.
Chatbots for crises and customer service
Chatbots and voice assistants have already proven themselves this year and demonstrated what valuable contribution they make in times of crisis, for example, and how they can support such a massive communication and information need.
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In addition, companies benefit not only from automated 24/7 customer service, but also from higher Website interaction rates, automated lead generation, and efficient use of resources. The user’s perspective also shows that interest in using chatbots and overall customer satisfaction is increasing through the use of AI and automation.
Conversational AI instead of rule-based bots
In the meantime, the sometimes too high initial expectations of the technology have given way to more realistic assessments. Chatbots have evolved in many ways over the last few years and simple rule-based bots are now mostly replaced by conversational AI bots.
Language as a challenge
However, one of the biggest challenges remains — optimizing the quality of conversation between chatbots and voice assistants. Two essential topics have to be worked on: speech recognition and knowledge modeling.
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Austrian Patent Office’s “Albert” bot to help startups The user’s linguistic input must first be recognized and understood. Natural Language Understanding (NLU) is concerned with this task. This is about understanding the structure and meaning of human communication. The topic of knowledge preparation and modeling is even more important, but less often considered. This can only be used as input for natural language answers if the knowledge already existing in companies and expanded by users’ requests is processed accordingly.
One thing has definitely been shown over the last few years: just because a chatbot understands a question, can he not answering them yet. That’s why we at Onlim see the greatest need for action and optimization today in knowledge preparation and modeling.
Chatbots and voice assistants are more than just a new tool. It’s about a comprehensive transformation process that is changing the way we communicate, collect information and access knowledge in a sustainable way.
While text-based chatbots still dominate today, a clear trend towards the use of voice assistants will establish itself in the coming years. Juniper Research estimates that more than 8 billion active voice assistants will already be in use in 2023. In 2019, the figure was around 3.25 billion.
Companies will continue to increase interest in conversational AI solutions in the coming months. There will also be a rise in awareness that the structure or the Structuring your own knowledge base is a prerequisite for developing a company-specific chatbot.
In fact, completely new business models will emerge around voice and chatbots, which we are currently very difficult to estimate today. The sooner companies deal with these applications, the more likely they are to gain a concrete competitive advantage from them. Simple “copy & paste” is no longer so easy with this technology.
As Chief Revenue Officer at Onlim, Marc Isop is responsible for all marketing and sales activities. He has been working as a consultant and senior positions in the software and internet industry for 20 years and points to Onlim’s experience of more than 70 enterprise chatbot solutions for major customers from different industries.
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